repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
onnxruntime | onnxruntime/python/tools/transformers/models/sam2/prompt_encoder.py | .py | # -------------------------------------------------------------------------
# Copyright (R) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
import logging
import torch
from sam2.modeling.sam2_base import SAM2Bas... | 190 | 8,341 |
onnxruntime | onnxruntime/python/tools/transformers/models/sam2/nvtx_helper.py | .py | # -------------------------------------------------------------------------
# Copyright (R) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
import nvtx
from cuda import cudart
class NvtxHelper:
def __init__... | 34 | 1,279 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/cache_helper.py | .py | import packaging.version as pv
import torch
from transformers import __version__ as transformers_version
from transformers.cache_utils import DynamicCache, EncoderDecoderCache
def is_cache_dynamic_registered(fast: bool = False) -> bool:
"""
Tells class :class:`DynamicCache` can be
serialized and deseriali... | 73 | 2,334 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/onnx_export_serialization.py | .py | from typing import Any
import torch
from transformers.cache_utils import DynamicCache, MambaCache
############
# MambaCache
############
# self.conv_states: torch.Tensor = torch.zeros(
# config.num_hidden_layers,
# self.max_batch_size,
# self.intermediate_size,
# self.conv_kernel_size,
# device=... | 125 | 3,757 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/__init__.py | .py | from dataclasses import fields, is_dataclass
from typing import Any
import numpy as np
import packaging.version as pv
import torch
from transformers import __version__ as transformers_version
from transformers.cache_utils import DynamicCache, EncoderDecoderCache
from .onnx_export_errors import (
bypass_export_som... | 464 | 15,780 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/onnx_export_errors.py | .py | import contextlib
import pprint
from collections.abc import Callable
from typing import Any
from .onnx_export_serialization import (
flatten_dynamic_cache,
flatten_mamba_cache,
flatten_with_keys_dynamic_cache,
flatten_with_keys_mamba_cache,
unflatten_dynamic_cache,
unflatten_mamba_cache,
)
from... | 472 | 18,236 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/patch_inputs.py | .py | import inspect
from typing import Any
import torch
from transformers.cache_utils import DynamicCache
from . import string_type
from .cache_helper import make_dynamic_cache
def _process_cache(k: str, v):
assert k != "position_ids" or isinstance(k, torch.Tensor), (
f"Unexpected type for parameter {k!r} {s... | 167 | 6,629 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/patches/patch_torch.py | .py | import inspect
import os
from collections.abc import Callable, Sequence
from typing import Any
import torch
from torch._subclasses.fake_tensor import FakeTensorMode
def _catch_produce_guards_and_solve_constraints(
previous_function: Callable,
fake_mode: "FakeTensorMode",
gm: "torch.fx.GraphModule",
d... | 324 | 14,034 |
onnxruntime | onnxruntime/python/tools/transformers/models/torch_export_patches/patches/patch_transformers.py | .py | import inspect
import sys
from dataclasses import dataclass
from typing import Any
import torch
from transformers.cache_utils import Cache, DynamicCache, StaticCache
from transformers.generation.utils import GenerationMixin
from transformers.modeling_attn_mask_utils import AttentionMaskConverter
def _patch_make_caus... | 475 | 20,997 |
onnxruntime | onnxruntime/python/tools/transformers/models/bert/eval_squad.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
#
# This script evaluates accuracy of ONNX models for question-answering... | 330 | 12,026 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/llama_parity.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
from __f... | 344 | 11,557 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/dist_settings.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import o... | 58 | 1,602 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/llama_torch.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import l... | 48 | 1,685 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/benchmark.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import a... | 701 | 26,594 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/convert_to_onnx.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
from __f... | 1,067 | 42,292 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/llama_inputs.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
from __f... | 505 | 20,222 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/quant_kv_dataloader.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import a... | 109 | 4,851 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/benchmark_all.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import a... | 489 | 15,305 |
onnxruntime | onnxruntime/python/tools/transformers/models/llama/benchmark_e2e.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
# This ... | 609 | 24,869 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_helper.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import j... | 1,039 | 50,551 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/benchmark.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 586 | 21,862 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_chain.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 335 | 14,904 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_encoder_decoder_init.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 373 | 16,461 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_decoder.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 466 | 21,428 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/convert_to_onnx.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 732 | 25,880 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_inputs.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 381 | 15,661 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/benchmark_all.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 527 | 18,842 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_encoder.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 166 | 6,208 |
onnxruntime | onnxruntime/python/tools/transformers/models/whisper/whisper_jump_times.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import ... | 480 | 19,560 |
onnxruntime | onnxruntime/python/tools/layering/layer_annotate.py | .py | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import argparse
import logging
import pathlib
import onnx
def get_logger(name, level=logging.DEBUG):
logging.basicConfig(format="%(asctime)s %(name)s [%(levelname)s] - %(message)s")
logger = logging.getLogger(name)... | 166 | 5,571 |
onnxruntime | onnxruntime/python/tools/profile_explorer/profile_explorer.py | .py | #!/usr/bin/python
import argparse
import fnmatch
import json
import subprocess as sp
from collections import defaultdict
import pandas as pd
def _demangle(name, demangler="c++filt"):
try:
with sp.Popen([demangler, name], stdin=sp.PIPE, stdout=sp.PIPE) as proc:
out, _ = proc.communicate()
... | 330 | 11,595 |
onnxruntime | onnxruntime/python/datasets/__init__.py | .py | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""
Short examples used in the documentation.
"""
import os
def get_example(name):
"""
Retrieves the absolute file name of an example.
"""
this = os.path.abspath(os.path.dirname(__file__))
full = os.path... | 19 | 455 |
onnxruntime | onnxruntime/python/torch_cpp_extensions/setup.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
import os
from setuptools import setup
from torch.utils import cpp_exte... | 20 | 668 |
onnxruntime | onnxruntime/python/torch_cpp_extensions/aten_op_executor/setup.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
import os
from setuptools import setup
from torch.utils import cpp_exte... | 17 | 588 |
onnxruntime | onnxruntime/python/torch_cpp_extensions/aten_op_executor/__init__.py | .py | import threading
from functools import wraps
from onnxruntime.capi import _pybind_state as _C
def run_once_aten_op_executor(f):
"""
Decorator to run a function only once.
:param f: function to be run only once during execution time despite the number of calls
:return: The original function with the p... | 34 | 1,174 |
onnxruntime | onnxruntime/python/torch_cpp_extensions/ort_torch_ext/__init__.py | .py | import threading
from functools import wraps
import torch # noqa: F401
from onnxruntime.capi import _pybind_state as _C
from .aten_op_executor import execute_aten_operator_address, is_tensor_argument_address
def run_once_aten_op_executor(f):
"""
Decorator to run a function only once.
:param f: functio... | 38 | 1,213 |
onnxruntime | onnxruntime/python/backend/backend_rep.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
"""
Implements ONNX's backend API.
"""
from onnx.backend.base import Bac... | 77 | 2,825 |
onnxruntime | onnxruntime/python/backend/backend.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
"""
Implements ONNX's backend API.
"""
import os
import unittest
import... | 215 | 10,233 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/RuntimeOptimizationRecordContainerEntry.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class RuntimeOptimizationRecordContainerEntry(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n =... | 92 | 3,741 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/OperatorSetId.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class OperatorSetId(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(fl... | 68 | 2,032 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/StringStringEntry.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class StringStringEntry(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Ge... | 68 | 2,080 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/DimensionValueType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
class DimensionValueType(object):
UNKNOWN = 0
VALUE = 1
PARAM = 2
| 9 | 166 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/NodesToOptimizeIndices.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
# nodes to consider for a runtime optimization
# see corresponding type in onnxruntime/core/graph/runtime_optimization_record.h
class NodesToOptimiz... | 161 | 5,984 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/KernelTypeStrResolver.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class KernelTypeStrResolver(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encod... | 79 | 2,789 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/SequenceType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class SequenceType(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(fla... | 59 | 1,771 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/DeprecatedNodeIndexAndKernelDefHash.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
# deprecated: no longer using kernel def hashes
class DeprecatedNodeIndexAndKernelDefHash(object):
__slots__ = ['_tab']
@classmethod
de... | 69 | 2,458 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/DimensionValue.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class DimensionValue(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(f... | 81 | 2,494 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/RuntimeOptimizations.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class RuntimeOptimizations(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode... | 80 | 2,721 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/NodeEdge.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class NodeEdge(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuf... | 127 | 4,057 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/ArgType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
class ArgType(object):
INPUT = 0
OUTPUT = 1
| 8 | 140 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/FloatProperty.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class FloatProperty(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(fl... | 68 | 2,008 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Attribute.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Attribute(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbu... | 338 | 10,850 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/DeprecatedKernelCreateInfos.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
# deprecated: no longer using kernel def hashes
class DeprecatedKernelCreateInfos(object):
__slots__ = ['_tab']
@classmethod
def GetRoo... | 121 | 4,528 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Model.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Model(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuffer... | 224 | 7,440 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/__init__.py | .py | from os.path import dirname, basename, isfile, join, splitext
import glob
modules = glob.glob(join(dirname(__file__), "*.py"))
__all__ = [splitext(basename(f))[0] for f in modules if isfile(f) and not f.endswith('__init__.py')]
from . import *
| 7 | 245 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/ValueInfo.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class ValueInfo(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbu... | 85 | 2,571 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Graph.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Graph(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuffer... | 321 | 10,719 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/PropertyBag.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class PropertyBag(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flat... | 153 | 4,947 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/TypeInfo.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class TypeInfo(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuf... | 84 | 2,516 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Checkpoint.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Checkpoint(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatb... | 126 | 4,217 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/DeprecatedSubGraphSessionState.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
# deprecated: no longer using kernel def hashes
class DeprecatedSubGraphSessionState(object):
__slots__ = ['_tab']
@classmethod
def Get... | 73 | 2,610 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/KernelTypeStrArgsEntry.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class KernelTypeStrArgsEntry(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.enco... | 92 | 3,102 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/TensorTypeAndShape.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class TensorTypeAndShape(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.G... | 72 | 2,255 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Shape.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Shape(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuffer... | 79 | 2,274 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/DeprecatedSessionState.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
# deprecated: no longer using kernel def hashes
class DeprecatedSessionState(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(c... | 97 | 3,582 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/AttributeType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
class AttributeType(object):
UNDEFINED = 0
FLOAT = 1
INT = 2
STRING = 3
TENSOR = 4
GRAPH = 5
FLOATS = 6
INTS = 7
STRINGS = 8
TENSORS = 9
GRAPHS = 10
SPARSE_TENSOR = 11
SPARSE_TENSO... | 19 | 328 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/TensorDataType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
class TensorDataType(object):
UNDEFINED = 0
FLOAT = 1
UINT8 = 2
INT8 = 3
UINT16 = 4
INT16 = 5
INT32 = 6
INT64 = 7
STRING = 8
BOOL = 9
FLOAT16 = 10
DOUBLE = 11
UINT32 = 12
UINT6... | 27 | 474 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/TypeInfoValue.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
class TypeInfoValue(object):
NONE = 0
tensor_type = 1
sequence_type = 2
map_type = 3
| 10 | 189 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/EdgeEnd.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class EdgeEnd(object):
__slots__ = ['_tab']
@classmethod
def SizeOf(cls):
return 12
# EdgeEnd
def Init(self, buf, pos)... | 33 | 1,105 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/RuntimeOptimizationRecord.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
# a single runtime optimization
# see corresponding type in onnxruntime/core/graph/runtime_optimization_record.h
class RuntimeOptimizationRecord(obj... | 106 | 3,962 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/OpIdKernelTypeStrArgsEntry.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class OpIdKernelTypeStrArgsEntry(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.... | 92 | 3,296 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/InferenceSession.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class InferenceSession(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get... | 89 | 3,037 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/NodeType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
class NodeType(object):
Primitive = 0
Fused = 1
| 8 | 144 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Dimension.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Dimension(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbu... | 72 | 2,191 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/StringProperty.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class StringProperty(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(f... | 68 | 2,043 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/ParameterOptimizerState.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class ParameterOptimizerState(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.enc... | 92 | 3,127 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/SparseTensor.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class SparseTensor(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(fla... | 115 | 3,692 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/ArgTypeAndIndex.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class ArgTypeAndIndex(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(... | 68 | 2,026 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/MapType.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class MapType(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuff... | 72 | 2,123 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/OptimizerGroup.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class OptimizerGroup(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(f... | 118 | 4,018 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/IntProperty.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class IntProperty(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flat... | 68 | 1,970 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Node.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Node(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuffers... | 318 | 10,401 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/ModuleState.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class ModuleState(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flat... | 142 | 4,853 |
onnxruntime | onnxruntime/core/flatbuffers/ort_flatbuffers_py/fbs/Tensor.py | .py | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: fbs
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class Tensor(object):
__slots__ = ['_tab']
@classmethod
def GetRootAs(cls, buf, offset=0):
n = flatbuffers.encode.Get(flatbuffe... | 204 | 6,599 |
onnxruntime | onnxruntime/core/flatbuffers/schema/compile_schema.py | .py | #!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import argparse
import pathlib
import shutil
import subprocess
import tempfile
SCRIPT_DIR = pathlib.Path(__file__).parent.resolve()
def update_schema_names(schema_path: pathlib.Path, updated_schema_p... | 150 | 6,249 |
onnxruntime | onnxruntime/core/mlas/lib/sve/gen_sve_asm.py | .py | #!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""Freeze SVE intrinsics translation units into KleidiAI-style machine code.
Compiles an SVE intrinsics reference TU with gcc, extracts the requested
extern "C" functions from the object file, and emits... | 205 | 7,665 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/dump_mlprogram_model.py | .py | import sys
import coremltools as ct
if len(sys.argv) < 2:
print(f"Usage: {sys.argv[0]} <path to model.mlmodel in ML Package>")
print("If generated by onnxruntime this will be <ML Package root>/Data/com.microsoft.onnxruntime/model.mlmodel")
print(
"The ML Package created by the CoreML EP can saved ... | 35 | 1,205 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/resize_test.py | .py | import coremltools as ct
import numpy as np
from coremltools.converters.mil import Builder as mb
target = ct.target.iOS15
x_shape = (1, 1, 3, 6)
use_scale = False # set this to test upsample vs resize
@mb.program(input_specs=[mb.TensorSpec(shape=x_shape)], opset_version=target)
def prog(x):
global use_scale ... | 52 | 1,268 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/div_test.py | .py | import coremltools as ct
import numpy as np
from coremltools.converters.mil import Builder as mb
from coremltools.models import datatypes
from coremltools.models.neural_network import NeuralNetworkBuilder
from coremltools.models.utils import save_spec
input_dim = (1,)
output_dim = (1,)
def mlprogram():
target = ... | 104 | 2,868 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/convtranspose_test.py | .py | import coremltools as ct
import numpy as np
from coremltools.converters.mil import Builder as mb
target = ct.target.iOS15
x_shape = (1, 3, 4, 4)
w_shape = (3, 3, 3, 3)
@mb.program(input_specs=[mb.TensorSpec(shape=x_shape)], opset_version=target)
def prog(x):
weight = mb.const(name="weight", val=np.ones(w_shape,... | 43 | 1,364 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/gridsample_test.py | .py | import coremltools as ct
import numpy as np
from coremltools.converters.mil import Builder as mb
target = ct.target.iOS15
x_shape = (2, 2, 3, 2)
grid_shape = (2, 3, 2, 2)
@mb.program(input_specs=[mb.TensorSpec(shape=x_shape), mb.TensorSpec(shape=grid_shape)], opset_version=target)
def prog(x, grid):
sampling = ... | 115 | 2,850 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/concat_test.py | .py | import coremltools as ct
import numpy as np
from coremltools.converters.mil import Builder as mb
target = ct.target.iOS15
a_shape = (1, 1, 3, 3)
@mb.program(
input_specs=[mb.TensorSpec(shape=a_shape), mb.TensorSpec(shape=a_shape), mb.TensorSpec(shape=a_shape)],
opset_version=target,
)
def prog(x, y, z):
... | 34 | 767 |
onnxruntime | onnxruntime/core/providers/coreml/mlprogram_test_scripts/depthtospace_test.py | .py | import coremltools as ct
import numpy as np
from coremltools.converters.mil import Builder as mb
target = ct.target.iOS15
# replicate example from https://github.com/onnx/onnx/blob/main/docs/Operators.md#depthtospace
# to prove CoreML mode is DCR
x_shape = (1, 8, 2, 3)
@mb.program(input_specs=[mb.TensorSpec(shape=x... | 52 | 1,508 |
onnxruntime | onnxruntime/core/providers/vsinpu/patches/test_scripts/compare_cosine_sim.py | .py | import sys
import numpy as np
from numpy.linalg import norm
def read_values(filename):
with open(filename) as file:
values = np.array([float(line.strip()) for line in file])
return values
def cosine_similarity(vec1, vec2):
return np.dot(vec1, vec2) / (norm(vec1) * norm(vec2))
if __name__ == "... | 30 | 650 |
onnxruntime | onnxruntime/core/providers/vsinpu/patches/test_scripts/compare_topn.py | .py | import sys
def read_values(filename):
with open(filename) as file:
values = [(float(line.strip()), i + 1) for i, line in enumerate(file)]
return values
def top_n(values, N):
return sorted(values, key=lambda x: x[0], reverse=True)[:N]
def compare_files(cpu_file, npu_file, N):
cpu_values = r... | 35 | 835 |
onnxruntime | onnxruntime/test/run_benchmark.py | .py | #!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
from __future__ import annotations
import argparse
import dataclasses
import json
import pathlib
import subprocess
import sys
import tempfile
def warn(message: str):
print(f"WARNING: {message}",... | 202 | 5,708 |
onnxruntime | onnxruntime/test/platform/apple/generate_ipa_export_options_plist.py | .py | import argparse
plist_file_content = """
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>method</key>
<string>development</string>
<key>teamID</key>
<string>{team_id}</string>... | 55 | 1,778 |
onnxruntime | onnxruntime/test/contrib_ops/multihead_attention_op_test_data_gen.py | .py | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
# Running this script in Linux like the following
# CUBLAS_WORKSPACE_CO... | 565 | 19,050 |
onnxruntime | onnxruntime/test/contrib_ops/attention_lstm_data_gen.py | .py | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import tensorflow as tf
batchSize = 2 # noqa: N816
memMaxStep = 3 # noqa: N816
memDepth = 3 # noqa: N816
queryMaxStep = 4 # noqa: N816
queryDepth = 3 # noqa: N816
am_attn_size: int = 2
cell_hidden_size = 3
aw_attn_size... | 425 | 11,825 |
onnxruntime | onnxruntime/test/autoep/tools/print_onnx_metadata.py | .py | #!/usr/bin/env python3
import argparse
import json
from pathlib import Path
from typing import Any
import onnx
def model_metadata_to_dict(model: onnx.ModelProto) -> dict[str, Any]:
custom_metadata = {entry.key: entry.value for entry in model.metadata_props}
graph = model.graph
info = {
"ir_vers... | 56 | 1,640 |
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