diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/__init__.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..c5d956de3e62b277e2009fa90410d2795ae6a9ab Binary files /dev/null and b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/__init__.cpython-310.pyc differ diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/autoheuristic.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/autoheuristic.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..8341ea59f398fa560ad351b9f990c060bb695726 Binary files /dev/null and b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/autoheuristic.cpython-310.pyc differ diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/autoheuristic_utils.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/autoheuristic_utils.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..d4887343dd2f24413b11b091f37bfb22f75dc47b Binary files /dev/null and b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/autoheuristic_utils.cpython-310.pyc differ diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/learned_heuristic_controller.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/learned_heuristic_controller.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..072215d6bd8b67e52ea0ac0ecc877ebdeb898495 Binary files /dev/null and b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/learned_heuristic_controller.cpython-310.pyc differ diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/learnedheuristic_interface.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/learnedheuristic_interface.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..bea197177b25958424094fa9739bbbf6ba4d0033 Binary files /dev/null and b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/__pycache__/learnedheuristic_interface.cpython-310.pyc differ diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MMRankingA100.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MMRankingA100.py new file mode 100644 index 0000000000000000000000000000000000000000..6a8cce6f870b1bc6bcda58e267b6d50feec56717 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MMRankingA100.py @@ -0,0 +1,296 @@ +# flake8: noqa: B950 +# fmt: off +# This file was generated by AutoHeuristic. Do not modify it manually! +# To regenerate this file, take a look at the steps in the README.md file inside torchgen/_autoheuristic/mm/ +from typing import List, Optional, Tuple + +from torch._inductor.autoheuristic.autoheuristic_utils import ( + AHContext, + AHMetadata, + Choice, +) +from torch._inductor.autoheuristic.learnedheuristic_interface import ( + LearnedHeuristicDecision, +) + + +class MMRankingA100(LearnedHeuristicDecision): + + def __init__(self) -> None: + self.choices: List[Choice] = [] + self.fill_choices() + + def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: + return ( + metadata.name == self.get_name() + and metadata.shared_memory == 166912 + and str(metadata.device_capa) == "(8, 0)" + ) + + def get_confidence_threshold(self) -> float: + return 0.0 + + def get_choice(self, idx: int) -> Optional[str]: + if idx < len(self.choices): + return self.choices[idx] + return None + + def fill_choices(self) -> None: + self.choices.append('extern_mm') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=128_BLOCK-N=16_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=128_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=128_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=16_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=16_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=16_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=32_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=128_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=1') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=32_numstages=1_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=32_numstages=3_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=64_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=16_numstages=5_numwarps=1') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=16_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=16_numstages=1_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=16_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=32_numstages=1_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=32_BLOCK-N=16_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=32_BLOCK-N=16_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=64_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=128_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=16_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=64_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=128_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=16_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=5_numwarps=4') + + def get_name(self) -> str: + return 'mm' + + def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]: + if context.get_value('arith_intensity') <= 52.6245059967041: + if context.get_value('n') <= 34.0: + if context.get_value('n') <= 18.0: + if context.get_value('k*n') <= 312.0: + return [(0.093, 12), (0.081, 16), (0.081, 148), (0.070, 10), (0.070, 17), (0.070, 149), (0.070, 151), (0.070, 150), (0.070, 14), (0.058, 11), (0.058, 15), (0.058, 13), (0.058, 122), (0.047, 121), (0.035, 123), (0.012, 92)] + else: + if context.get_value('k') <= 40.0: + return [(0.083, 42), (0.083, 46), (0.083, 44), (0.083, 40), (0.083, 128), (0.067, 45), (0.067, 43), (0.067, 41), (0.067, 169), (0.067, 171), (0.067, 168), (0.067, 129), (0.067, 170), (0.033, 103), (0.017, 121)] + else: + return [(0.112, 137), (0.104, 136), (0.101, 0), (0.081, 1), (0.073, 135), (0.069, 67), (0.066, 187), (0.058, 41), (0.050, 71), (0.046, 68), (0.046, 70), (0.031, 44), (0.027, 43), (0.027, 170), (0.019, 189), (0.019, 188), (0.015, 169), (0.015, 171), (0.012, 115), (0.012, 168), (0.012, 69), (0.004, 103)] + else: + if context.get_value('mat1_stride_0') <= 20.0: + return [(0.069, 0), (0.059, 157), (0.059, 22), (0.059, 153), (0.059, 155), (0.059, 25), (0.059, 23), (0.059, 19), (0.044, 21), (0.044, 18), (0.044, 152), (0.044, 158), (0.044, 154), (0.044, 156), (0.044, 20), (0.044, 124), (0.044, 24), (0.030, 125), (0.029, 126), (0.015, 97), (0.015, 95), (0.015, 96), (0.010, 2), (0.010, 75)] + else: + if context.get_value('k') <= 68.0: + return [(0.087, 72), (0.087, 74), (0.087, 73), (0.086, 76), (0.077, 75), (0.067, 192), (0.058, 190), (0.048, 47), (0.048, 193), (0.048, 49), (0.048, 51), (0.048, 191), (0.038, 53), (0.019, 133), (0.019, 50), (0.019, 175), (0.019, 172), (0.019, 48), (0.019, 174), (0.010, 173), (0.010, 177), (0.010, 52), (0.010, 54), (0.010, 178), (0.010, 176)] + else: + return [(0.154, 52), (0.154, 72), (0.102, 75), (0.087, 49), (0.087, 73), (0.086, 51), (0.057, 176), (0.045, 2), (0.038, 191), (0.038, 178), (0.038, 190), (0.029, 173), (0.029, 76), (0.026, 138), (0.013, 139), (0.013, 140), (0.003, 0)] + else: + if context.get_value('k') <= 35.0: + if context.get_value('k') <= 18.0: + if context.get_value('m*n') <= 19505152.0: + return [(0.151, 159), (0.140, 160), (0.129, 164), (0.055, 127), (0.051, 29), (0.044, 161), (0.044, 147), (0.040, 146), (0.040, 31), (0.037, 145), (0.026, 28), (0.022, 90), (0.022, 93), (0.022, 94), (0.022, 100), (0.022, 125), (0.022, 158), (0.022, 157), (0.011, 87), (0.011, 88), (0.011, 89), (0.011, 91), (0.011, 95), (0.011, 96), (0.011, 98), (0.011, 99)] + else: + return [(0.069, 7), (0.069, 5), (0.067, 147), (0.066, 8), (0.061, 145), (0.058, 146), (0.052, 124), (0.049, 29), (0.049, 159), (0.046, 31), (0.043, 157), (0.041, 9), (0.041, 4), (0.040, 6), (0.035, 164), (0.035, 160), (0.026, 158), (0.017, 125), (0.017, 28), (0.017, 32), (0.017, 162), (0.017, 27), (0.017, 30), (0.017, 161), (0.009, 33), (0.009, 26), (0.009, 163), (0.006, 0)] + else: + if context.get_value('n') <= 68.0: + return [(0.101, 182), (0.101, 59), (0.088, 57), (0.076, 184), (0.076, 61), (0.076, 179), (0.076, 62), (0.076, 58), (0.063, 180), (0.063, 60), (0.051, 56), (0.050, 181), (0.025, 130), (0.025, 177), (0.025, 183), (0.013, 178), (0.013, 55)] + else: + return [(0.089, 180), (0.079, 60), (0.066, 35), (0.066, 181), (0.066, 38), (0.066, 58), (0.066, 179), (0.066, 57), (0.062, 184), (0.053, 37), (0.044, 166), (0.040, 55), (0.040, 39), (0.040, 36), (0.040, 165), (0.040, 167), (0.027, 177), (0.027, 34), (0.022, 159)] + else: + if context.get_value('m*n') <= 309760.0: + return [(0.298, 0), (0.097, 140), (0.080, 83), (0.072, 86), (0.044, 84), (0.036, 178), (0.036, 117), (0.036, 82), (0.032, 120), (0.032, 85), (0.028, 119), (0.024, 130), (0.024, 109), (0.020, 108), (0.020, 118), (0.012, 104), (0.012, 116), (0.012, 141), (0.012, 144), (0.008, 105), (0.008, 106), (0.008, 111), (0.008, 114), (0.008, 107), (0.008, 132), (0.004, 101), (0.004, 102), (0.004, 110), (0.004, 112), (0.004, 113), (0.004, 131)] + else: + if context.get_value('n') <= 72.0: + return [(0.227, 77), (0.118, 78), (0.102, 194), (0.086, 80), (0.059, 57), (0.054, 81), (0.049, 196), (0.048, 197), (0.048, 59), (0.043, 79), (0.032, 195), (0.027, 180), (0.022, 3), (0.021, 141), (0.016, 60), (0.016, 142), (0.011, 183), (0.011, 0), (0.011, 144)] + else: + return [(0.140, 186), (0.132, 185), (0.109, 63), (0.085, 65), (0.078, 37), (0.077, 35), (0.062, 197), (0.047, 194), (0.046, 165), (0.046, 57), (0.039, 78), (0.039, 79), (0.039, 66), (0.039, 64), (0.016, 195), (0.008, 159)] + else: + if str(context.get_value('using_tf32')) != 'False': + if context.get_value('m*n') <= 815360.0: + if context.get_value('k') <= 1184.0: + return [(0.218, 140), (0.205, 0), (0.154, 144), (0.115, 141), (0.051, 185), (0.051, 104), (0.039, 78), (0.038, 116), (0.026, 165), (0.026, 130), (0.026, 178), (0.013, 57), (0.013, 195), (0.013, 167), (0.013, 186)] + else: + return [(0.901, 0), (0.030, 144), (0.030, 134), (0.016, 3), (0.006, 78), (0.006, 77), (0.002, 57), (0.002, 194), (0.002, 59), (0.002, 60), (0.002, 143)] + else: + if context.get_value('arith_intensity') <= 187.23922729492188: + if context.get_value('mat1_stride_0') <= 198.0: + return [(0.273, 63), (0.158, 37), (0.152, 35), (0.127, 57), (0.097, 165), (0.053, 185), (0.031, 0), (0.028, 64), (0.014, 60), (0.014, 78), (0.009, 55), (0.008, 134), (0.005, 34), (0.005, 167), (0.005, 179), (0.005, 65), (0.005, 66), (0.005, 186), (0.005, 194), (0.002, 166)] + else: + return [(0.296, 63), (0.235, 0), (0.132, 64), (0.074, 37), (0.069, 78), (0.051, 185), (0.051, 35), (0.030, 57), (0.020, 77), (0.016, 194), (0.008, 66), (0.007, 65), (0.003, 3), (0.003, 165), (0.003, 141), (0.001, 134), (0.001, 166)] + else: + return [(0.405, 0), (0.246, 37), (0.177, 63), (0.145, 35), (0.005, 185), (0.005, 65), (0.005, 64), (0.004, 57), (0.003, 66), (0.002, 165), (0.001, 78), (0.001, 55)] + else: + return [(0.357, 0), (0.112, 165), (0.101, 57), (0.094, 179), (0.086, 64), (0.074, 167), (0.067, 60), (0.064, 159), (0.033, 35), (0.007, 195), (0.002, 180), (0.001, 34), (0.001, 166), (0.001, 78)] diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MMRankingH100.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MMRankingH100.py new file mode 100644 index 0000000000000000000000000000000000000000..e794b8e646f3af299d4f5566a0bcd2fe1f22e6d6 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MMRankingH100.py @@ -0,0 +1,321 @@ +# flake8: noqa: B950 +# fmt: off +# This file was generated by AutoHeuristic. Do not modify it manually! +# To regenerate this file, take a look at the steps in the README.md file inside torchgen/_autoheuristic/mm/ +from typing import List, Optional, Tuple + +from torch._inductor.autoheuristic.autoheuristic_utils import ( + AHContext, + AHMetadata, + Choice, +) +from torch._inductor.autoheuristic.learnedheuristic_interface import ( + LearnedHeuristicDecision, +) + + +class MMRankingH100(LearnedHeuristicDecision): + + def __init__(self) -> None: + self.choices: List[Choice] = [] + self.fill_choices() + + def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: + return ( + metadata.name == self.get_name() + and metadata.shared_memory == 232448 + and str(metadata.device_capa) == "(9, 0)" + ) + + def get_confidence_threshold(self) -> float: + return 0.0 + + def get_choice(self, idx: int) -> Optional[str]: + if idx < len(self.choices): + return self.choices[idx] + return None + + def fill_choices(self) -> None: + self.choices.append('extern_mm') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=128_BLOCK-N=16_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=128_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=128_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=16_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=16_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=2_numwarps=8') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=16_numstages=3_numwarps=4') + 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self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=32_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=16_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=16_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=16_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=5_numwarps=4') + + def get_name(self) -> str: + return 'mm' + + def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]: + if context.get_value('arith_intensity') <= 29.89772129058838: + if context.get_value('n') <= 34.0: + if context.get_value('n') <= 18.0: + if context.get_value('k*n') <= 432.0: + if context.get_value('arith_intensity') <= 7.8700292110443115: + return [(0.098, 128), (0.098, 129), (0.098, 127), (0.073, 14), (0.073, 16), (0.073, 12), (0.073, 154), (0.073, 156), (0.073, 157), (0.073, 155), (0.049, 10), (0.049, 94), (0.049, 95), (0.048, 96)] + else: + return [(0.091, 154), (0.073, 10), (0.073, 15), (0.073, 13), (0.073, 11), (0.073, 17), (0.073, 16), (0.073, 14), (0.073, 12), (0.055, 127), (0.054, 157), (0.054, 156), (0.054, 155), (0.036, 129), (0.036, 128), (0.018, 41), (0.018, 43)] + else: + if context.get_value('k') <= 40.0: + return [(0.070, 39), (0.069, 45), (0.069, 41), (0.069, 43), (0.069, 111), (0.069, 112), (0.056, 38), (0.056, 40), (0.056, 42), (0.056, 44), (0.056, 174), (0.056, 173), (0.056, 175), (0.056, 134), (0.056, 172), (0.056, 135), (0.014, 154), (0.014, 127)] + else: + return [(0.147, 144), (0.119, 143), (0.087, 142), (0.083, 0), (0.073, 191), (0.059, 69), (0.050, 67), (0.046, 70), (0.041, 1), (0.036, 174), (0.032, 43), (0.032, 123), (0.028, 40), (0.027, 42), (0.027, 173), (0.023, 175), (0.018, 66), (0.014, 192), (0.014, 193), (0.014, 139), (0.014, 68), (0.014, 127)] + else: + if context.get_value('mat1_stride_0') <= 40.0: + if context.get_value('mat1_stride_0') <= 20.0: + return [(0.109, 23), (0.109, 21), (0.109, 20), (0.088, 0), (0.087, 131), (0.066, 18), (0.065, 130), (0.065, 132), (0.065, 159), (0.065, 160), (0.065, 161), (0.065, 158), (0.022, 22), (0.022, 19)] + else: + return [(0.065, 46), (0.064, 52), (0.064, 50), (0.064, 48), (0.064, 51), (0.064, 49), (0.064, 47), (0.064, 53), (0.064, 181), (0.064, 177), (0.064, 179), (0.064, 176), (0.038, 130), (0.038, 136), (0.026, 182), (0.026, 178), (0.026, 180), (0.026, 137), (0.025, 158), (0.013, 114), (0.013, 113)] + else: + if context.get_value('mat1_stride_0') <= 68.0: + return [(0.138, 140), (0.125, 195), (0.100, 71), (0.100, 74), (0.100, 196), (0.100, 194), (0.100, 197), (0.075, 75), (0.062, 72), (0.062, 73), (0.012, 180), (0.012, 51), (0.012, 182)] + else: + return [(0.124, 180), (0.124, 182), (0.114, 75), (0.103, 74), (0.093, 51), (0.093, 71), (0.072, 72), (0.062, 194), (0.052, 145), (0.052, 195), (0.021, 48), (0.021, 50), (0.021, 47), (0.020, 124), (0.010, 147), (0.010, 146), (0.010, 46)] + else: + if context.get_value('k') <= 18.0: + if context.get_value('m*k') <= 528.0: + return [(0.097, 88), (0.087, 92), (0.077, 90), (0.058, 105), (0.058, 103), (0.058, 104), (0.058, 99), (0.058, 100), (0.058, 106), (0.058, 93), (0.057, 91), (0.057, 97), (0.057, 98), (0.057, 101), (0.048, 102), (0.029, 87), (0.029, 89)] + else: + if context.get_value('n') <= 80.0: + return [(0.057, 161), (0.057, 130), (0.057, 24), (0.056, 164), (0.056, 163), (0.056, 166), (0.056, 168), (0.056, 30), (0.056, 28), (0.056, 26), (0.056, 25), (0.056, 27), (0.056, 29), (0.056, 31), (0.042, 131), (0.028, 99), (0.028, 101), (0.028, 100), (0.028, 167), (0.028, 165), (0.028, 133)] + else: + return [(0.110, 164), (0.108, 163), (0.106, 168), (0.069, 161), (0.066, 151), (0.060, 152), (0.055, 165), (0.050, 27), (0.050, 29), (0.048, 131), (0.043, 153), (0.037, 133), (0.037, 130), (0.028, 8), (0.028, 5), (0.027, 7), (0.026, 26), (0.016, 162), (0.012, 9), (0.007, 4), (0.005, 100), (0.005, 6), (0.005, 24)] + else: + if context.get_value('k') <= 36.0: + if context.get_value('n') <= 68.0: + return [(0.097, 184), (0.097, 56), (0.086, 186), (0.086, 183), (0.086, 188), (0.086, 58), (0.086, 60), (0.065, 54), (0.043, 187), (0.043, 185), (0.043, 57), (0.043, 61), (0.032, 55), (0.032, 130), (0.032, 59), (0.011, 181), (0.011, 163), (0.011, 136), (0.011, 138)] + else: + return [(0.117, 184), (0.117, 170), (0.117, 169), (0.107, 183), (0.106, 188), (0.075, 181), (0.064, 130), (0.064, 56), (0.053, 171), (0.032, 57), (0.032, 59), (0.032, 185), (0.011, 163), (0.011, 32), (0.011, 37), (0.011, 34), (0.011, 33), (0.011, 35), (0.011, 36), (0.011, 54)] + else: + if context.get_value('mat2_stride_0') <= 384.0: + return [(0.244, 0), (0.061, 76), (0.061, 79), (0.030, 3), (0.030, 183), (0.030, 189), (0.030, 187), (0.030, 64), (0.030, 190), (0.030, 62), (0.030, 198), (0.030, 201), (0.030, 77), (0.030, 200), (0.030, 80), (0.030, 199), (0.030, 78), (0.030, 184), (0.020, 86), (0.020, 84), (0.020, 120), (0.020, 81), (0.020, 121), (0.020, 85), (0.020, 122), (0.010, 83), (0.010, 118), (0.010, 119), (0.010, 82)] + else: + return [(0.274, 83), (0.171, 86), (0.152, 0), (0.071, 85), (0.061, 125), (0.050, 84), (0.020, 109), (0.020, 117), (0.020, 81), (0.020, 118), (0.020, 121), (0.020, 108), (0.020, 115), (0.020, 116), (0.010, 110), (0.010, 120), (0.010, 103), (0.010, 107), (0.010, 119), (0.010, 122)] + else: + if context.get_value('arith_intensity') <= 56.995582580566406: + if context.get_value('n') <= 68.0: + if context.get_value('k*n') <= 4448.0: + if context.get_value('m*n') <= 29626368.0: + return [(0.107, 198), (0.107, 200), (0.107, 201), (0.107, 199), (0.106, 76), (0.106, 79), (0.064, 197), (0.063, 56), (0.043, 184), (0.043, 187), (0.042, 80), (0.042, 77), (0.042, 183), (0.021, 78)] + else: + return [(0.073, 201), (0.073, 198), (0.073, 200), (0.073, 199), (0.073, 197), (0.073, 56), (0.073, 58), (0.073, 79), (0.073, 76), (0.072, 59), (0.072, 78), (0.072, 77), (0.072, 80), (0.018, 184), (0.018, 55), (0.018, 54)] + else: + if context.get_value('k') <= 348.0: + return [(0.206, 76), (0.183, 77), (0.169, 198), (0.160, 199), (0.053, 59), (0.046, 56), (0.038, 3), (0.030, 148), (0.030, 58), (0.030, 187), (0.023, 184), (0.015, 0), (0.008, 55), (0.008, 54)] + else: + return [(0.146, 198), (0.145, 199), (0.145, 148), (0.126, 0), (0.084, 76), (0.084, 77), (0.042, 80), (0.042, 79), (0.021, 149), (0.021, 150), (0.021, 3), (0.014, 46), (0.014, 74), (0.014, 75), (0.014, 124), (0.014, 194), (0.014, 195), (0.007, 145), (0.007, 146), (0.007, 2), (0.007, 72), (0.007, 147), (0.007, 71)] + else: + if context.get_value('m') <= 3264.0: + return [(0.247, 147), (0.115, 197), (0.066, 199), (0.066, 201), (0.066, 198), (0.049, 0), (0.049, 169), (0.049, 171), (0.033, 140), (0.033, 125), (0.033, 114), (0.016, 126), (0.016, 183), (0.016, 184), (0.016, 185), (0.016, 182), (0.016, 188), (0.016, 78), (0.016, 148), (0.016, 138), (0.016, 77), (0.016, 56), (0.016, 59)] + else: + if context.get_value('k') <= 62.5: + return [(0.226, 190), (0.226, 189), (0.122, 62), (0.122, 64), (0.055, 77), (0.055, 78), (0.037, 198), (0.036, 201), (0.036, 33), (0.024, 163), (0.018, 56), (0.018, 35), (0.018, 169), (0.006, 171)] + else: + return [(0.162, 35), (0.118, 33), (0.096, 189), (0.096, 190), (0.088, 169), (0.074, 62), (0.073, 56), (0.066, 171), (0.051, 198), (0.051, 201), (0.044, 59), (0.037, 64), (0.029, 63), (0.007, 0), (0.007, 77)] + else: + if context.get_value('m*n') <= 1097728.0: + return [(0.403, 0), (0.179, 141), (0.134, 150), (0.086, 147), (0.051, 148), (0.048, 3), (0.024, 189), (0.020, 199), (0.017, 64), (0.010, 65), (0.010, 77), (0.007, 114), (0.003, 138), (0.003, 59), (0.003, 182)] + else: + if context.get_value('m*n') <= 3244032.0: + return [(0.295, 189), (0.176, 64), (0.157, 65), (0.090, 0), (0.069, 62), (0.059, 63), (0.046, 77), (0.039, 169), (0.023, 199), (0.020, 35), (0.013, 33), (0.010, 171), (0.003, 141)] + else: + if context.get_value('n') <= 136.0: + return [(0.197, 189), (0.197, 63), (0.161, 77), (0.157, 62), (0.061, 33), (0.044, 65), (0.039, 35), (0.039, 64), (0.030, 169), (0.026, 0), (0.017, 199), (0.017, 148), (0.009, 56), (0.004, 3)] + else: + return [(0.460, 0), (0.145, 62), (0.138, 63), (0.081, 35), (0.047, 33), (0.043, 189), (0.023, 64), (0.018, 77), (0.013, 169), (0.009, 65), (0.009, 56), (0.005, 32), (0.005, 59), (0.002, 183), (0.002, 163)] diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MixedMMA100.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MixedMMA100.py new file mode 100644 index 0000000000000000000000000000000000000000..9a9ea693a96dcc01efac82eb3cf092db4c5f8629 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MixedMMA100.py @@ -0,0 +1,150 @@ +# flake8: noqa: B950 +# fmt: off +# This file was generated by AutoHeuristic. Do not modify it manually! +# To regenerate this file, take a look at the steps in the README.md file inside torchgen/_autoheuristic/mixed_mm/ +from typing import List, Optional, Tuple + +from torch._inductor.autoheuristic.autoheuristic_utils import ( + AHContext, + AHMetadata, + Choice, +) +from torch._inductor.autoheuristic.learnedheuristic_interface import ( + LearnedHeuristicDecision, +) + + +class MixedMMA100(LearnedHeuristicDecision): + + def __init__(self) -> None: + self.choices: List[Choice] = [] + self.fill_choices() + + def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: + return ( + metadata.name == self.get_name() + and metadata.shared_memory == 166912 + and str(metadata.device_capa) == "(8, 0)" + ) + + def get_confidence_threshold(self) -> float: + return 0.0 + + def get_choice(self, idx: int) -> Optional[str]: + if idx < len(self.choices): + return self.choices[idx] + return None + + def fill_choices(self) -> None: + self.choices.append('extern_fallback_mixed_mm') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=256_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=256_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=128_numstages=4_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=8') + + def get_name(self) -> str: + return 'mixed_mm' + + def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]: + if str(context.get_value('1LEQmLEQ16')) != 'True': + if context.get_value('m') <= 32.5: + if context.get_value('n') <= 6976.0: + if context.get_value('n') <= 3520.0: + if context.get_value('m*n') <= 37632.0: + return None + else: + return [(1.000, 13)] + else: + if context.get_value('m*k') <= 452352.0: + return [(0.590, 13), (0.256, 8), (0.103, 7), (0.051, 11)] + else: + return [(0.778, 8), (0.222, 13)] + else: + if context.get_value('k*n') <= 102776832.0: + if context.get_value('n') <= 14656.0: + return [(1.000, 11)] + else: + return [(0.889, 11), (0.111, 13)] + else: + return [(1.000, 11)] + else: + if context.get_value('m*n') <= 446464.0: + if context.get_value('m*n') <= 223424.0: + if context.get_value('mat1_stride_0') <= 3968.0: + return None + else: + return None + else: + if context.get_value('m*n') <= 346112.0: + return [(0.960, 16), (0.040, 7)] + else: + return [(0.750, 16), (0.136, 14), (0.114, 7)] + else: + if str(context.get_value('33LEQmLEQ64')) != 'True': + if context.get_value('n') <= 6976.0: + return [(1.000, 14)] + else: + return [(0.753, 2), (0.222, 1), (0.015, 7), (0.007, 16), (0.004, 12)] + else: + if context.get_value('n') <= 13888.0: + return [(0.710, 14), (0.275, 21), (0.014, 12)] + else: + return [(0.374, 19), (0.339, 20), (0.106, 21), (0.101, 16), (0.066, 17), (0.009, 14), (0.004, 18)] + else: + if context.get_value('n') <= 3520.0: + if context.get_value('arith_intensity') <= 3.994754433631897: + if str(context.get_value('mat2_dtype')) != 'torch.uint8': + if context.get_value('m*k') <= 18944.0: + return [(0.577, 5), (0.423, 6)] + else: + return [(0.988, 5), (0.012, 6)] + else: + if context.get_value('arith_intensity') <= 2.9899919033050537: + return None + else: + return None + else: + if context.get_value('arith_intensity') <= 7.956453561782837: + if context.get_value('k*n') <= 9244032.0: + return [(0.822, 5), (0.178, 6)] + else: + return [(0.977, 5), (0.023, 0)] + else: + if context.get_value('m*k') <= 978944.0: + return [(1.000, 5)] + else: + return [(0.971, 5), (0.029, 0)] + else: + if context.get_value('n') <= 13632.0: + if context.get_value('n') <= 6976.0: + return [(1.000, 6)] + else: + if context.get_value('k') <= 3968.0: + return [(0.617, 3), (0.111, 5), (0.099, 7), (0.086, 9), (0.062, 6), (0.025, 8)] + else: + return [(0.779, 8), (0.119, 5), (0.053, 7), (0.035, 6), (0.013, 3)] + else: + if context.get_value('k*n') <= 39518208.0: + return [(0.385, 4), (0.327, 3), (0.192, 6), (0.038, 7), (0.038, 10), (0.019, 5)] + else: + if context.get_value('n') <= 20800.0: + return [(0.821, 6), (0.121, 7), (0.029, 4), (0.014, 5), (0.007, 3), (0.007, 8)] + else: + return [(0.530, 7), (0.386, 6), (0.046, 8), (0.021, 3), (0.015, 4), (0.002, 5)] diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MixedMMH100.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MixedMMH100.py new file mode 100644 index 0000000000000000000000000000000000000000..b4552c5257e73ddb6699e1040c758997aa96c062 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_MixedMMH100.py @@ -0,0 +1,149 @@ +# flake8: noqa: B950 +# fmt: off +# This file was generated by AutoHeuristic. Do not modify it manually! +# To regenerate this file, take a look at the steps in the README.md file inside torchgen/_autoheuristic/mixed_mm/ +from typing import List, Optional, Tuple + +from torch._inductor.autoheuristic.autoheuristic_utils import ( + AHContext, + AHMetadata, + Choice, +) +from torch._inductor.autoheuristic.learnedheuristic_interface import ( + LearnedHeuristicDecision, +) + + +class MixedMMH100(LearnedHeuristicDecision): + + def __init__(self) -> None: + self.choices: List[Choice] = [] + self.fill_choices() + + def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: + return ( + metadata.name == self.get_name() + and metadata.shared_memory == 232448 + and str(metadata.device_capa) == "(9, 0)" + ) + + def get_confidence_threshold(self) -> float: + return 0.0 + + def get_choice(self, idx: int) -> Optional[str]: + if idx < len(self.choices): + return self.choices[idx] + return None + + def fill_choices(self) -> None: + self.choices.append('extern_fallback_mixed_mm') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=32_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=128_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=32_numstages=2_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=2') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=256_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=256_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=128_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=16_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=32_numstages=2_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=32_BLOCK-K=32_BLOCK-N=64_numstages=5_numwarps=8') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=128_numstages=4_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=32_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=128_BLOCK-N=64_numstages=5_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=128_numstages=3_numwarps=4') + self.choices.append('type=triton_BLOCK-M=64_BLOCK-K=64_BLOCK-N=64_numstages=3_numwarps=8') + + def get_name(self) -> str: + return 'mixed_mm' + + def get_best_choices(self, context: AHContext) -> Optional[List[tuple[float, int]]]: + if context.get_value('arith_intensity') <= 15.988086223602295: + if context.get_value('n') <= 25280.0: + if context.get_value('n') <= 1344.0: + if context.get_value('mat1_stride_0') <= 7808.0: + return [(0.581, 7), (0.419, 6)] + else: + if context.get_value('m*n') <= 7680.0: + return [(0.875, 0), (0.125, 6)] + else: + return [(0.833, 0), (0.167, 7)] + else: + if context.get_value('n') <= 8512.0: + if str(context.get_value('mat2_dtype')) != 'torch.int8': + return [(0.763, 6), (0.237, 7)] + else: + return [(0.725, 7), (0.275, 6)] + else: + if str(context.get_value('mat1_dtype')) != 'torch.bfloat16': + return [(0.736, 7), (0.197, 9), (0.048, 6), (0.014, 8), (0.005, 10)] + else: + return [(0.473, 7), (0.398, 6), (0.097, 9), (0.032, 10)] + else: + if context.get_value('n') <= 42254.0: + if context.get_value('n') <= 33856.0: + if context.get_value('k*n') <= 68157440.0: + return [(0.370, 4), (0.370, 5), (0.074, 7), (0.074, 8), (0.074, 11), (0.037, 6)] + else: + return [(0.916, 8), (0.036, 7), (0.036, 9), (0.012, 4)] + else: + return [(0.659, 5), (0.341, 6)] + else: + if context.get_value('k*n') <= 326052992.0: + if context.get_value('n') <= 55232.0: + return [(0.571, 6), (0.321, 7), (0.036, 4), (0.036, 8), (0.036, 9)] + else: + return [(0.506, 6), (0.325, 8), (0.104, 7), (0.039, 5), (0.026, 9)] + else: + if context.get_value('n') <= 57024.0: + return [(0.462, 9), (0.385, 7), (0.115, 6), (0.038, 8)] + else: + return [(0.598, 8), (0.223, 9), (0.107, 6), (0.071, 7)] + else: + if context.get_value('m*n') <= 543936.0: + if str(context.get_value('17LEQmLEQ32')) != 'True': + if context.get_value('m*n') <= 262272.0: + if context.get_value('n') <= 1592.5: + return [(0.860, 0), (0.140, 9)] + else: + return None + else: + if context.get_value('m*k') <= 1294336.0: + return [(0.833, 17), (0.150, 18), (0.017, 15)] + else: + return [(0.917, 17), (0.083, 8)] + else: + if context.get_value('n') <= 12416.0: + if context.get_value('m*n') <= 43008.0: + return None + else: + return [(0.853, 14), (0.147, 9)] + else: + return [(0.625, 12), (0.375, 14)] + else: + if context.get_value('m') <= 32.5: + if context.get_value('mat2_stride_1') <= 6656.0: + if context.get_value('n') <= 69184.0: + return [(0.611, 12), (0.361, 14), (0.028, 13)] + else: + return [(1.000, 12)] + else: + if context.get_value('mat2_stride_1') <= 20864.0: + return [(1.000, 12)] + else: + return [(0.958, 12), (0.042, 9)] + else: + if context.get_value('m*n') <= 1085440.0: + if context.get_value('n') <= 9152.0: + return [(1.000, 18)] + else: + return [(0.780, 18), (0.160, 16), (0.060, 20)] + else: + if context.get_value('m') <= 67.0: + return [(0.650, 16), (0.203, 19), (0.122, 18), (0.016, 20), (0.008, 1)] + else: + return [(0.561, 3), (0.185, 16), (0.096, 20), (0.083, 19), (0.076, 2)] diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_PadMMA100.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_PadMMA100.py new file mode 100644 index 0000000000000000000000000000000000000000..b61f8a9dd1e99056864a9dddc663b090f6971214 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/_PadMMA100.py @@ -0,0 +1,109 @@ +# flake8: noqa: B950 +# fmt: off +# This file was generated by AutoHeuristic. Do not modify it manually! +# To regenerate this file, take a look at the steps in the README.md file inside torchgen/_autoheuristic/pad_mm/ +from torch._inductor.autoheuristic.autoheuristic_utils import AHContext, AHMetadata, Choice, CHOICE_COL +from torch._inductor.autoheuristic.learnedheuristic_interface import ( + LearnedHeuristicRegression, +) + + +class PadMMA100(LearnedHeuristicRegression): + + def __init__(self) -> None: + pass + + def check_precondition(self, metadata: AHMetadata, context: AHContext,) -> bool: + return ( + metadata.name == self.get_name() + and metadata.shared_memory == 166912 + and str(metadata.device_capa) == "(8, 0)" + ) + + def get_feedback(self, context: AHContext, choice: Choice) -> float: + context.context_dict[CHOICE_COL] = choice + return self.predict(context) + + def get_confidence_threshold(self) -> float: + return 1.7025303314066 + + def get_name(self) -> str: + return 'pad_mm' + + def predict(self, context: AHContext) -> float: + if str(context.get_value('choice')) != 'pad': + if str(context.get_value('using_tf32')) != 'False': + if context.get_value('m*n') <= 4171264.0: + if context.get_value('m*k') <= 3999308.0: + return 1.8751469764071178 + else: + if str(context.get_value('n_multiple_32')) != 'True': + return 0.9117231355626345 + else: + return 1.1607689608873861 + else: + if str(context.get_value('n_multiple_2')) != 'True': + if str(context.get_value('using_tf32')) != 'True': + return 0.7430382200435992 + else: + return 0.8531269794448678 + else: + if str(context.get_value('k_multiple_2')) != 'True': + return 0.7577181972719917 + else: + return 0.8977349440424219 + else: + if context.get_value('m*n') <= 1299712.0: + return 1.1669723418995592 + else: + if context.get_value('mat2_stride_1') <= 45217.5: + if context.get_value('m*n') <= 55884158.0: + return 1.0262769936909601 + else: + return 1.0022677428470845 + else: + if context.get_value('m') <= 18478.0: + return 1.1127066261894312 + else: + return 1.0337740659894263 + else: + if str(context.get_value('mat1_dtype')) != 'torch.float32': + if str(context.get_value('n_multiple_2')) != 'False': + if str(context.get_value('k_multiple_2')) != 'True': + if context.get_value('mat1_stride_0') <= 561.0: + return 1.2900382135142956 + else: + return 1.5761737616057887 + else: + if context.get_value('num_dims_needs_padding') <= 1.5: + return 1.0472263310239422 + else: + return 1.1727673465762514 + else: + if context.get_value('k') <= 28238.5: + if context.get_value('k/(m*n)') <= 0.00026227018679492176: + return 1.6770542505397175 + else: + return 1.3974785435105923 + else: + if str(context.get_value('mat1_dtype')) != 'torch.bfloat16': + return 1.3952699800111992 + else: + return 1.5759286511628336 + else: + if str(context.get_value('using_tf32')) != 'False': + if context.get_value('m*n') <= 14119424.0: + return 0.8875772670422478 + else: + if str(context.get_value('mat2_innermost_needs_padding')) != 'True': + return 1.1467728924377265 + else: + return 1.215842963532998 + else: + if context.get_value('arith_intensity') <= 396.8774871826172: + return 0.89940161869551 + else: + if context.get_value('mat2_stride_1') <= 45217.5: + return 0.9964328169353532 + else: + return 0.9493479238294826 diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/__init__.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/__pycache__/_MMRankingA100.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/autoheuristic/artifacts/__pycache__/_MMRankingA100.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..689bfdf26bf7afe1f4169308f84ed31ca79a8a2d Binary 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E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_2, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_2, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, bmm_default_2, Ignored()) +view_default_7 = CallFunction(aten.view.default, convert_element_type_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_2, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +view_default_8 = CallFunction(aten.view.default, fma_default, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, view_default_9, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, div_Tensor_2, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_10_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_2, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_2, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_10_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_2, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +view_default_8 = CallFunction(aten.view.default, convert_element_type_default_3, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, view_default_9, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, div_Tensor_2, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_10_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_10_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_11.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_11.py new file mode 100644 index 0000000000000000000000000000000000000000..6aa39474c67dd677008c8e7e9266cc875a153196 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_11.py @@ -0,0 +1,204 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale'), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_7, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_11_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale'), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_11_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_3, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_4, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_11_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_11_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_12.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_12.py new file mode 100644 index 0000000000000000000000000000000000000000..87302d1bab3694a33eac14e263dca86c9f702c75 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_12.py @@ -0,0 +1,220 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, KeywordArg('inv_scale_factor')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_12_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_12_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_5, KeywordArg('inv_scale_factor')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_12_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_12_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_13.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_13.py new file mode 100644 index 0000000000000000000000000000000000000000..d465c1cb4e22b14bfbbdd35d5ed28a43af891523 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_13.py @@ -0,0 +1,130 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, KeywordArg('query'), permute_default, _users=2) +amax_default = CallFunction(aten.amax.default, bmm_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, bmm_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, mul_Tensor_1, KeywordArg('value')) +neg_default = CallFunction(aten.neg.default, div_Tensor) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, KeywordArg('tangents_1'), permute_default_1) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, bmm_default_2, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4, _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, fma_default, permute_default_2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, fma_default) +permute_default_4 = CallFunction(aten.permute.default, bmm_default_4, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, mul_Tensor_1, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, KeywordArg('tangents_1')) +_sfdp_pattern_13_training = MultiOutputPattern([bmm_default_1, + bmm_default_3, + permute_default_4, + bmm_default_5, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +bmm_default = CallFunction(aten.bmm.default, KeywordArg('query'), permute_default, _users=2) +amax_default = CallFunction(aten.amax.default, bmm_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, bmm_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +_sfdp_pattern_13_inference = CallFunction(aten.bmm.default, div_Tensor, KeywordArg('value'), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, KeywordArg('query'), permute_default) +convert_element_type_default = CallFunction(prims.convert_element_type.default, bmm_default, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, mul_Tensor_1, KeywordArg('value')) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, KeywordArg('tangents_1'), permute_default_1) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, bmm_default_2, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, convert_element_type_default_5, permute_default_2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, convert_element_type_default_5) +permute_default_4 = CallFunction(aten.permute.default, bmm_default_4, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, mul_Tensor_1, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, KeywordArg('tangents_1')) +_sfdp_pattern_13_half_training = MultiOutputPattern([bmm_default_1, + bmm_default_3, + permute_default_4, + bmm_default_5, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +bmm_default = CallFunction(aten.bmm.default, KeywordArg('query'), permute_default) +convert_element_type_default = CallFunction(prims.convert_element_type.default, bmm_default, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +_sfdp_pattern_13_half_inference = CallFunction(aten.bmm.default, convert_element_type_default_1, KeywordArg('value'), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_14.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_14.py new file mode 100644 index 0000000000000000000000000000000000000000..f102038e82c6d5858b8b334e956d87c7e86a9d22 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_14.py @@ -0,0 +1,210 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_7, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_14_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_14_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_3, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_4, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_14_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_14_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_15.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_15.py new file mode 100644 index 0000000000000000000000000000000000000000..e1cbb0df340bab14188ec9d5f04a29035dba8d84 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_15.py @@ -0,0 +1,230 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored(), _users=2) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor, _users=2) +amax_default = CallFunction(aten.amax.default, where_self, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, where_self, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_3 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +view_default_6 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +scalar_tensor_default = CallFunction(aten.scalar_tensor.default, Ignored(), dtype=Ignored(), layout=torch.strided, device=Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_7 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_7, permute_default_4) +view_default_8 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_8, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +where_self_1 = CallFunction(aten.where.self, expand_default, scalar_tensor_default, fma_default) +div_Tensor_2 = CallFunction(aten.div.Tensor, where_self_1, KeywordArg('inv_scale')) +view_default_9 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_2, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_9, permute_default_5) +view_default_10 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_9) +view_default_11 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_11, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_7) +view_default_12 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_12, Ignored()) +_sfdp_pattern_15_training = MultiOutputPattern([view_default_6, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None +]) + + +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored()) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor, _users=2) +amax_default = CallFunction(aten.amax.default, where_self, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, where_self, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_3 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +_sfdp_pattern_15_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored(), _users=2) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor) +convert_element_type_default = CallFunction(prims.convert_element_type.default, where_self, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +view_default_6 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +scalar_tensor_default = CallFunction(aten.scalar_tensor.default, Ignored(), dtype=Ignored(), layout=torch.strided, device=Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_7 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_7, permute_default_4) +view_default_8 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_8, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_3, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +where_self_1 = CallFunction(aten.where.self, expand_default, scalar_tensor_default, convert_element_type_default_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, where_self_1, KeywordArg('inv_scale')) +view_default_9 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_2, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_9, permute_default_5) +view_default_10 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_9) +view_default_11 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_11, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_7) +view_default_12 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_12, Ignored()) +_sfdp_pattern_15_half_training = MultiOutputPattern([view_default_6, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None +]) + + +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored()) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor) +convert_element_type_default = CallFunction(prims.convert_element_type.default, where_self, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +_sfdp_pattern_15_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_16.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_16.py new file mode 100644 index 0000000000000000000000000000000000000000..3a15abb9088ff5ffe8cd9af43df11ccc0d5bc143 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_16.py @@ -0,0 +1,599 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_16_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_16_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_16_bs1_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_16_bs1_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_5, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_16_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_16_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_5, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_16_half_bs1_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_16_half_bs1_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_2, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_1, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_3, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_16_half_mask_fp32_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_16_half_mask_fp32_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_2, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_1, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_3, KeywordArg('inv_scale')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_16_half_mask_fp32_bs1_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale')) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_16_half_mask_fp32_bs1_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_17.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_17.py new file mode 100644 index 0000000000000000000000000000000000000000..812708907b3414e2c864ed36b98f2199e63ae5d2 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_17.py @@ -0,0 +1,246 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored(), _users=2) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor, _users=2) +amax_default = CallFunction(aten.amax.default, where_self, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, where_self, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +view_default_6 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +scalar_tensor_default = CallFunction(aten.scalar_tensor.default, Ignored(), dtype=Ignored(), layout=torch.strided, device=Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_7 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_7, permute_default_4) +view_default_8 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_8, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +where_self_1 = CallFunction(aten.where.self, expand_default, scalar_tensor_default, fma_default) +div_Tensor_2 = CallFunction(aten.div.Tensor, where_self_1, KeywordArg('inv_scale')) +view_default_9 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_2, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_9, permute_default_5) +view_default_10 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_9) +view_default_11 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_11, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_7) +view_default_12 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_12, Ignored()) +_sfdp_pattern_17_training = MultiOutputPattern([view_default_6, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored()) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor, _users=2) +amax_default = CallFunction(aten.amax.default, where_self, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, where_self, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_3 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +_sfdp_pattern_17_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored(), _users=2) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor) +convert_element_type_default = CallFunction(prims.convert_element_type.default, where_self, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +view_default_6 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +scalar_tensor_default = CallFunction(aten.scalar_tensor.default, Ignored(), dtype=Ignored(), layout=torch.strided, device=Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_7 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_7, permute_default_4) +view_default_8 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_8, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +where_self_1 = CallFunction(aten.where.self, expand_default, scalar_tensor_default, convert_element_type_default_5) +div_Tensor_2 = CallFunction(aten.div.Tensor, where_self_1, KeywordArg('inv_scale')) +view_default_9 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_2, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_9, permute_default_5) +view_default_10 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_9) +view_default_11 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_11, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_7) +view_default_12 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_12, Ignored()) +_sfdp_pattern_17_half_training = MultiOutputPattern([view_default_6, + permute_default_6, + permute_default_9, + permute_default_11, + None, + None, + None +]) + + +eq_Scalar = CallFunction(aten.eq.Scalar, KeywordArg('attn_mask'), Ignored()) +view_default = CallFunction(aten.view.default, eq_Scalar, Ignored()) +expand_default = CallFunction(aten.expand.default, view_default, Ignored()) +full_default = CallFunction(aten.full.default, [], Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_2, memory_format=torch.contiguous_format) +view_default_2 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default_1, view_default_2) +view_default_3 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_3, KeywordArg('inv_scale')) +where_self = CallFunction(aten.where.self, expand_default, full_default, div_Tensor) +convert_element_type_default = CallFunction(prims.convert_element_type.default, where_self, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_4 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_4, memory_format=torch.contiguous_format) +view_default_5 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_4, view_default_5) +_sfdp_pattern_17_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_2.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_2.py new file mode 100644 index 0000000000000000000000000000000000000000..f28da434ef0c85ca3d80095e68c052e8dc19dd2d --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_2.py @@ -0,0 +1,174 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, mul_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, mul_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, view_default_7, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_1, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_1) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, fma_default, KeywordArg('scale_factor')) +view_default_8 = CallFunction(aten.view.default, mul_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_2_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, mul_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, mul_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_2_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_1, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_1) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, KeywordArg('scale_factor')) +view_default_8 = CallFunction(aten.view.default, mul_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_2_half_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_2_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_21.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_21.py new file mode 100644 index 0000000000000000000000000000000000000000..ad27e6eb6bb8eba84a7c435b41cdbafae621e271 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_21.py @@ -0,0 +1,217 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +view_default_3 = CallFunction(aten.view.default, add_Tensor, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_4, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_4, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_8 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_6, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_8, permute_default_4) +view_default_9 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_9, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +view_default_10 = CallFunction(aten.view.default, fma_default, Ignored()) +view_default_11 = CallFunction(aten.view.default, view_default_10, Ignored()) +view_default_12 = CallFunction(aten.view.default, view_default_11, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_12, permute_default_5) +view_default_13 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_13, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_12) +view_default_14 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_14, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_8) +view_default_15 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_15, Ignored()) +_sfdp_pattern_21_training = MultiOutputPattern([view_default_7, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +view_default_3 = CallFunction(aten.view.default, add_Tensor, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_4, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_4, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +_sfdp_pattern_21_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, convert_element_type_default, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, view_default_4, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default_1, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default_1, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_2, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_8 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_6, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_8, permute_default_4) +view_default_9 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_9, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_3, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +view_default_10 = CallFunction(aten.view.default, convert_element_type_default_4, Ignored()) +view_default_11 = CallFunction(aten.view.default, view_default_10, Ignored()) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, view_default_11, Ignored()) +convert_element_type_default_6 = CallFunction(prims.convert_element_type.default, convert_element_type_default_5, Ignored()) +view_default_12 = CallFunction(aten.view.default, convert_element_type_default_6, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_12, permute_default_5) +view_default_13 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_13, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_12) +view_default_14 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_14, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_8) +view_default_15 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_15, Ignored()) +_sfdp_pattern_21_half_training = MultiOutputPattern([view_default_7, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, convert_element_type_default, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, view_default_4, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default_1, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default_1, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_2, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +_sfdp_pattern_21_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_22.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_22.py new file mode 100644 index 0000000000000000000000000000000000000000..41a433e405433a1434c10700830ea8c81747a72b --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_22.py @@ -0,0 +1,229 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +view_default_3 = CallFunction(aten.view.default, add_Tensor, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_4, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_4, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_8 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_6, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_8, permute_default_4) +view_default_9 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_9, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +view_default_10 = CallFunction(aten.view.default, fma_default, Ignored()) +view_default_11 = CallFunction(aten.view.default, view_default_10, Ignored()) +view_default_12 = CallFunction(aten.view.default, view_default_11, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_12, permute_default_5) +view_default_13 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_13, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_12) +view_default_14 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_14, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_8) +view_default_15 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_15, Ignored()) +_sfdp_pattern_22_training = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +view_default_3 = CallFunction(aten.view.default, add_Tensor, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_4, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_4, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +_sfdp_pattern_22_inference = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, convert_element_type_default, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, view_default_4, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default_1, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default_1, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_2, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_8 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_6, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_8, permute_default_4) +view_default_9 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_9, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_3, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +view_default_10 = CallFunction(aten.view.default, convert_element_type_default_4, Ignored()) +view_default_11 = CallFunction(aten.view.default, view_default_10, Ignored()) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, view_default_11, Ignored()) +convert_element_type_default_6 = CallFunction(prims.convert_element_type.default, convert_element_type_default_5, Ignored()) +view_default_12 = CallFunction(aten.view.default, convert_element_type_default_6, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_12, permute_default_5) +view_default_13 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_13, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_12) +view_default_14 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_14, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_8) +view_default_15 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_15, Ignored()) +_sfdp_pattern_22_half_training = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, view_default_2, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, convert_element_type_default, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, view_default_4, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default_1, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default_1, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_2, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +_sfdp_pattern_22_half_inference = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3 +]) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_23.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_23.py new file mode 100644 index 0000000000000000000000000000000000000000..dc6f27cd284924601b6119ae5ea245bed4188962 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_23.py @@ -0,0 +1,225 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, view_default_2, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_4, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_4, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_8 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_6, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_8, permute_default_4) +view_default_9 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_9, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +view_default_10 = CallFunction(aten.view.default, fma_default, Ignored()) +view_default_11 = CallFunction(aten.view.default, view_default_10, Ignored()) +view_default_12 = CallFunction(aten.view.default, view_default_11, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_12, permute_default_5) +view_default_13 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_13, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_12) +view_default_14 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_14, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_8) +view_default_15 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_15, Ignored()) +_sfdp_pattern_23_training = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3, + permute_default_6, + permute_default_9, + permute_default_11 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, view_default_2, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_4, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_4, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +_sfdp_pattern_23_inference = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, view_default_2, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, convert_element_type_default_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_4, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default_2, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default_2, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_3, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_8 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_6, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_8, permute_default_4) +view_default_9 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, view_default_9, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_4, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +view_default_10 = CallFunction(aten.view.default, convert_element_type_default_5, Ignored()) +view_default_11 = CallFunction(aten.view.default, view_default_10, Ignored()) +convert_element_type_default_6 = CallFunction(prims.convert_element_type.default, view_default_11, Ignored()) +convert_element_type_default_7 = CallFunction(prims.convert_element_type.default, convert_element_type_default_6, Ignored()) +view_default_12 = CallFunction(aten.view.default, convert_element_type_default_7, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_12, permute_default_5) +view_default_13 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_13, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_12) +view_default_14 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_14, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_5, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_8) +view_default_15 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_15, Ignored()) +_sfdp_pattern_23_half_training = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3, + permute_default_6, + permute_default_9, + permute_default_11 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, view_default_2, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, convert_element_type_default_1, Ignored()) +view_default_4 = CallFunction(aten.view.default, view_default_3, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_4, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default_2, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default_2, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_3, Ignored()) +view_default_5 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_6 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_5, view_default_6) +view_default_7 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +_sfdp_pattern_23_half_inference = MultiOutputPattern([view_default_7, + permute_default_1, + permute_default_3 +]) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_3.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_3.py new file mode 100644 index 0000000000000000000000000000000000000000..2c7f7519ad0570d2c2f700d4081c9b7253d16657 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_3.py @@ -0,0 +1,190 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, KeywordArg('inv_scale_factor')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_3_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_3_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_5, KeywordArg('inv_scale_factor')) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_3_half_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, KeywordArg('inv_scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_3_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_4.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_4.py new file mode 100644 index 0000000000000000000000000000000000000000..dc9cfd506f950415f4f90b49edf83815432a641c --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_4.py @@ -0,0 +1,190 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, mul_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, mul_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_2, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_3) +mul_Tensor_5 = CallFunction(aten.mul.Tensor, mul_Tensor_4, div_Tensor, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_5, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_5) +mul_Tensor_6 = CallFunction(aten.mul.Tensor, fma_default, KeywordArg('scale_factor')) +view_default_8 = CallFunction(aten.view.default, mul_Tensor_6, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_4_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor'), _users=2) +amax_default = CallFunction(aten.amax.default, mul_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, mul_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_4_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_2, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_3) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_4, Ignored()) +mul_Tensor_5 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_5, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_5) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +mul_Tensor_6 = CallFunction(aten.mul.Tensor, convert_element_type_default_5, KeywordArg('scale_factor')) +view_default_8 = CallFunction(aten.view.default, mul_Tensor_6, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_4_half_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_2, KeywordArg('scale_factor')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_4_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_5.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_5.py new file mode 100644 index 0000000000000000000000000000000000000000..f211e56b17a0a19c05bcb0efc681ed2623f4edf7 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_5.py @@ -0,0 +1,178 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, view_default_7, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_5_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_5_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_3, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_4, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_5_half_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_5_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_6.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_6.py new file mode 100644 index 0000000000000000000000000000000000000000..01304bf415163909c5ec5b03064ce064697e1de9 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_6.py @@ -0,0 +1,194 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_6_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask'), _users=2) +amax_default = CallFunction(aten.amax.default, add_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, add_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +expand_default_2 = CallFunction(aten.expand.default, div_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_6_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored(), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored(), _users=2) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, convert_element_type_default_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, mul_Tensor_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, convert_element_type_default_1, Ignored(), _users=2) +neg_default = CallFunction(aten.neg.default, convert_element_type_default_2) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_1) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, view_default_7, mul_Tensor_2) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, mul_Tensor_3, Ignored()) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, convert_element_type_default_4, convert_element_type_default_2, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_5 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_5, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_2 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_2) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_3, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_4 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_5 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_5, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +_sfdp_pattern_6_half_training = MultiOutputPattern([view_default_5, + view_default_9, + permute_default_4, + view_default_11, + None, + None +]) + + +expand_default = CallFunction(aten.expand.default, KeywordArg('query'), Ignored()) +view_default = CallFunction(aten.view.default, expand_default, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default, Ignored()) +view_default_1 = CallFunction(aten.view.default, expand_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +add_Tensor = CallFunction(aten.add.Tensor, div_Tensor, KeywordArg('attn_mask')) +convert_element_type_default = CallFunction(prims.convert_element_type.default, add_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +expand_default_3 = CallFunction(aten.expand.default, KeywordArg('value'), Ignored()) +view_default_4 = CallFunction(aten.view.default, expand_default_3, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_6_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_7.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_7.py new file mode 100644 index 0000000000000000000000000000000000000000..b463c7e64a6130dd85063f5fb88c2317c392c8f2 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_7.py @@ -0,0 +1,221 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, bmm_default_2, Ignored()) +view_default_7 = CallFunction(aten.view.default, convert_element_type_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_2, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_7_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_7_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_2, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_4, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_7_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_7_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_8.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_8.py new file mode 100644 index 0000000000000000000000000000000000000000..3faff67089b17ad370d4d7642539c7ce3fd5d235 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_8.py @@ -0,0 +1,205 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, bmm_default_2, Ignored()) +view_default_7 = CallFunction(aten.view.default, convert_element_type_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_2, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +div_Tensor_2 = CallFunction(aten.div.Tensor, fma_default, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_8_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, div_Tensor, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, div_Tensor, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_8_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +mul_Tensor = CallFunction(aten.mul.Tensor, convert_element_type_default_2, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, convert_element_type_default_3, Ignored()) +view_default_8 = CallFunction(aten.view.default, div_Tensor_2, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, view_default_9, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_8_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11 +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +expand_default = CallFunction(aten.expand.default, permute_default, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, view_default_2, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_8_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_9.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_9.py new file mode 100644 index 0000000000000000000000000000000000000000..3bf77120e836a5b577ea8a335f00bd63fd27163a --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/_sfdp_pattern_9.py @@ -0,0 +1,221 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_2, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_2, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, bmm_default_2, Ignored()) +view_default_7 = CallFunction(aten.view.default, convert_element_type_default_1, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_2, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +view_default_8 = CallFunction(aten.view.default, fma_default, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, view_default_9, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, div_Tensor_2, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_9_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, view_default_2, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, view_default_2, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_9_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) + + +rand_default = CallFunction(aten.rand.default, Ignored(), dtype=Ignored(), device=Ignored(), pin_memory=False) +gt_Scalar = CallFunction(aten.gt.Scalar, rand_default, KeywordArg('dropout_p'), _users=2) +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored(), _users=2) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored(), _users=2) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList, _users=3) +mul_Tensor = CallFunction(aten.mul.Tensor, gt_Scalar, div_Tensor_1) +mul_Tensor_1 = CallFunction(aten.mul.Tensor, mul_Tensor, Ignored()) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, mul_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored(), _users=2) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored(), _users=2) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +view_default_5 = CallFunction(aten.view.default, bmm_default_1, Ignored()) +neg_default = CallFunction(aten.neg.default, div_Tensor_1) +view_default_6 = CallFunction(aten.view.default, KeywordArg('tangents_1'), Ignored(), _users=2) +permute_default_4 = CallFunction(aten.permute.default, view_default_4, Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, view_default_6, permute_default_4) +view_default_7 = CallFunction(aten.view.default, bmm_default_2, Ignored()) +convert_element_type_default_2 = CallFunction(prims.convert_element_type.default, view_default_7, Ignored()) +convert_element_type_default_3 = CallFunction(prims.convert_element_type.default, gt_Scalar, Ignored()) +mul_Tensor_2 = CallFunction(aten.mul.Tensor, convert_element_type_default_3, Ignored()) +mul_Tensor_3 = CallFunction(aten.mul.Tensor, convert_element_type_default_2, mul_Tensor_2) +mul_Tensor_4 = CallFunction(aten.mul.Tensor, mul_Tensor_3, div_Tensor_1, _users=2) +sum_dim_IntList_1 = CallFunction(aten.sum.dim_IntList, mul_Tensor_4, Ignored(), True) +fma_default = CallFunction(prims.fma.default, neg_default, sum_dim_IntList_1, mul_Tensor_4) +convert_element_type_default_4 = CallFunction(prims.convert_element_type.default, fma_default, Ignored()) +view_default_8 = CallFunction(aten.view.default, convert_element_type_default_4, Ignored(), _users=2) +permute_default_5 = CallFunction(aten.permute.default, view_default_1, Ignored()) +bmm_default_3 = CallFunction(aten.bmm.default, view_default_8, permute_default_5) +view_default_9 = CallFunction(aten.view.default, bmm_default_3, Ignored()) +div_Tensor_2 = CallFunction(aten.div.Tensor, view_default_9, Ignored()) +permute_default_6 = CallFunction(aten.permute.default, div_Tensor_2, Ignored()) +permute_default_7 = CallFunction(aten.permute.default, view_default, Ignored()) +bmm_default_4 = CallFunction(aten.bmm.default, permute_default_7, view_default_8) +view_default_10 = CallFunction(aten.view.default, bmm_default_4, Ignored()) +permute_default_8 = CallFunction(aten.permute.default, view_default_10, Ignored()) +permute_default_9 = CallFunction(aten.permute.default, permute_default_8, Ignored()) +permute_default_10 = CallFunction(aten.permute.default, view_default_3, Ignored()) +bmm_default_5 = CallFunction(aten.bmm.default, permute_default_10, view_default_6) +view_default_11 = CallFunction(aten.view.default, bmm_default_5, Ignored()) +permute_default_11 = CallFunction(aten.permute.default, view_default_11, Ignored()) +_sfdp_pattern_9_half_training = MultiOutputPattern([view_default_5, + permute_default_6, + permute_default_9, + permute_default_11, + None +]) + + +permute_default = CallFunction(aten.permute.default, KeywordArg('query'), Ignored()) +div_Tensor = CallFunction(aten.div.Tensor, permute_default, Ignored()) +expand_default = CallFunction(aten.expand.default, div_Tensor, Ignored()) +clone_default = CallFunction(aten.clone.default, expand_default, memory_format=torch.contiguous_format) +view_default = CallFunction(aten.view.default, clone_default, Ignored()) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('key'), Ignored()) +permute_default_2 = CallFunction(aten.permute.default, permute_default_1, Ignored()) +expand_default_1 = CallFunction(aten.expand.default, permute_default_2, Ignored()) +clone_default_1 = CallFunction(aten.clone.default, expand_default_1, memory_format=torch.contiguous_format) +view_default_1 = CallFunction(aten.view.default, clone_default_1, Ignored()) +bmm_default = CallFunction(aten.bmm.default, view_default, view_default_1) +view_default_2 = CallFunction(aten.view.default, bmm_default, Ignored()) +convert_element_type_default = CallFunction(prims.convert_element_type.default, view_default_2, Ignored(), _users=2) +amax_default = CallFunction(aten.amax.default, convert_element_type_default, Ignored(), True) +sub_Tensor = CallFunction(aten.sub.Tensor, convert_element_type_default, amax_default) +exp_default = CallFunction(aten.exp.default, sub_Tensor, _users=2) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, exp_default, Ignored(), True) +div_Tensor_1 = CallFunction(aten.div.Tensor, exp_default, sum_dim_IntList) +convert_element_type_default_1 = CallFunction(prims.convert_element_type.default, div_Tensor_1, Ignored()) +expand_default_2 = CallFunction(aten.expand.default, convert_element_type_default_1, Ignored()) +view_default_3 = CallFunction(aten.view.default, expand_default_2, Ignored()) +permute_default_3 = CallFunction(aten.permute.default, KeywordArg('value'), Ignored()) +expand_default_3 = CallFunction(aten.expand.default, permute_default_3, Ignored()) +clone_default_2 = CallFunction(aten.clone.default, expand_default_3, memory_format=torch.contiguous_format) +view_default_4 = CallFunction(aten.view.default, clone_default_2, Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, view_default_3, view_default_4) +_sfdp_pattern_9_half_inference = CallFunction(aten.view.default, bmm_default_1, Ignored(), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/addmm_pattern.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/addmm_pattern.py new file mode 100644 index 0000000000000000000000000000000000000000..70d672442170905a411de63187a5b579b286bf73 --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/addmm_pattern.py @@ -0,0 +1,53 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +addmm_default = CallFunction(aten.addmm.default, KeywordArg('input'), KeywordArg('mat1'), KeywordArg('mat2'), beta=KeywordArg('beta'), alpha=KeywordArg('alpha')) +mul_Scalar = CallFunction(aten.mul.Scalar, KeywordArg('tangents_1'), KeywordArg('beta')) +sum_dim_IntList = CallFunction(aten.sum.dim_IntList, mul_Scalar, Ignored(), True) +view_default = CallFunction(aten.view.default, sum_dim_IntList, Ignored()) +permute_default = CallFunction(aten.permute.default, KeywordArg('mat2'), Ignored()) +mm_default = CallFunction(aten.mm.default, KeywordArg('tangents_1'), permute_default) +mul_Scalar_1 = CallFunction(aten.mul.Scalar, mm_default, KeywordArg('alpha')) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('mat1'), Ignored()) +mm_default_1 = CallFunction(aten.mm.default, permute_default_1, KeywordArg('tangents_1')) +mul_Scalar_2 = CallFunction(aten.mul.Scalar, mm_default_1, KeywordArg('alpha')) +addmm_pattern_training = MultiOutputPattern([addmm_default, + view_default, + mul_Scalar_1, + mul_Scalar_2, + None, + None +]) + + +addmm_pattern_inference = CallFunction(aten.addmm.default, KeywordArg('input'), KeywordArg('mat1'), KeywordArg('mat2'), beta=KeywordArg('beta'), alpha=KeywordArg('alpha'), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/bmm_pattern.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/bmm_pattern.py new file mode 100644 index 0000000000000000000000000000000000000000..7b5ac59d6f06c97523e071e9b3ea78516ff09c0e --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/bmm_pattern.py @@ -0,0 +1,45 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +bmm_default = CallFunction(aten.bmm.default, KeywordArg('mat1'), KeywordArg('mat2')) +permute_default = CallFunction(aten.permute.default, KeywordArg('mat2'), Ignored()) +bmm_default_1 = CallFunction(aten.bmm.default, KeywordArg('tangents_1'), permute_default) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('mat1'), Ignored()) +bmm_default_2 = CallFunction(aten.bmm.default, permute_default_1, KeywordArg('tangents_1')) +bmm_pattern_training = MultiOutputPattern([bmm_default, + bmm_default_1, + bmm_default_2 +]) + + +bmm_pattern_inference = CallFunction(aten.bmm.default, KeywordArg('mat1'), KeywordArg('mat2'), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/mm_pattern.py b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/mm_pattern.py new file mode 100644 index 0000000000000000000000000000000000000000..058a2f881e3a52cb147cfd3fa0ef2bbd0a25945a --- /dev/null +++ b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/fx_passes/serialized_patterns/mm_pattern.py @@ -0,0 +1,45 @@ +# mypy: ignore-errors + +# noqa: F401, E501 +# This is an auto-generated file. Please do not modify it by hand. +# To re-generate, run: +# cd ~/pytorch && python torchgen/fuse/gen_patterns.py + +import torch +import torch._inductor +import operator + +aten = torch.ops.aten +prims = torch.ops.prims + +from torch._inductor.pattern_matcher import ( + Arg, + CallFunction, + CallFunctionVarArgs, + CallMethod, + CallMethodVarArgs, + CallModule, + CallModuleVarArgs, + ExclusiveKeywordArg, + Ignored, + KeywordArg, + ListOf, + MultiOutputPattern, + PatternExpr, + RepeatedExpr, + _TargetArgsExpr, + _TargetExpr, + _TargetExprVarArgs, +) +mm_default = CallFunction(aten.mm.default, KeywordArg('mat1'), KeywordArg('mat2')) +permute_default = CallFunction(aten.permute.default, KeywordArg('mat2'), Ignored()) +mm_default_1 = CallFunction(aten.mm.default, KeywordArg('tangents_1'), permute_default) +permute_default_1 = CallFunction(aten.permute.default, KeywordArg('mat1'), Ignored()) +mm_default_2 = CallFunction(aten.mm.default, permute_default_1, KeywordArg('tangents_1')) +mm_pattern_training = MultiOutputPattern([mm_default, + mm_default_1, + mm_default_2 +]) + + +mm_pattern_inference = CallFunction(aten.mm.default, KeywordArg('mat1'), KeywordArg('mat2'), _users=0) diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/kernel/__pycache__/__init__.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/kernel/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..4713021032d7ec147f77e8550074a39a3d3ccc12 Binary files /dev/null and b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/kernel/__pycache__/__init__.cpython-310.pyc differ diff --git a/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/kernel/__pycache__/bmm.cpython-310.pyc b/data/tefig/envs/olmes-eval/lib/python3.10/site-packages/torch/_inductor/kernel/__pycache__/bmm.cpython-310.pyc new file mode 100644 index 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