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flash-attn4

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kernels-bot commited on 8 days ago

Commit

e265b9a

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1 Parent(s): 148d93b

Uploaded using `kernel-builder`.

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Files changed (5) hide show

README.md +2 -3
build/torch-cuda/_ops.py +3 -6
build/torch-cuda/metadata.json +6 -5
build/torch-cuda/metadata.json.sigstore +1 -1
build/torch-cuda/symbols.json +343 -0

README.md CHANGED Viewed

@@ -12,13 +12,12 @@ This is the repository card of kernels-community/flash-attn4 that has been pushe
 from kernels import get_kernel
 kernel_module = get_kernel("kernels-community/flash-attn4", version=1)
-_private_for_testing = kernel_module._private_for_testing
-_private_for_testing(...)
 ```
 ## Available functions
-- `_private_for_testing`
 - `flash_attn_func`
 - `flash_attn_varlen_func`

 from kernels import get_kernel
 kernel_module = get_kernel("kernels-community/flash-attn4", version=1)
+flash_attn_func = kernel_module.flash_attn_func
+flash_attn_func(...)
 ```
 ## Available functions
 - `flash_attn_func`
 - `flash_attn_varlen_func`

build/torch-cuda/_ops.py CHANGED Viewed

@@ -4,11 +4,8 @@ def get_backend() -> str:
     """Detect the backend by inspecting torch."""
     import torch
-    if hasattr(torch.backends, "tpu"):
-        # torch_tpu sets torch.backends.tpu when it is imported (via
-        # torch's device-backend autoload), regardless of whether TPU
-        # hardware is present — analogous to torch.version.cuda being
-        # set on CUDA builds without a GPU.
         return "tpu"
     elif hasattr(torch, "neuron"):
         # Needs to be sorted before specific Torch builds, since Neuron
@@ -28,7 +25,7 @@ def get_backend() -> str:
 def _find_ops_name() -> str:
     kernel_name = "flash_attn4"
-    unique_id = "d8eaf3c"
     backend = get_backend()
     return f"_{kernel_name}_{backend}_{unique_id}"

     """Detect the backend by inspecting torch."""
     import torch
+    acc = torch.accelerator.current_accelerator() if hasattr(torch, "accelerator") else None
+    if acc is not None and acc.type == "tpu":
         return "tpu"
     elif hasattr(torch, "neuron"):
         # Needs to be sorted before specific Torch builds, since Neuron
 def _find_ops_name() -> str:
     kernel_name = "flash_attn4"
+    unique_id = "fe2bb66"
     backend = get_backend()
     return f"_{kernel_name}_{backend}_{unique_id}"

build/torch-cuda/metadata.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "name": "flash-attn4",
-  "id": "_flash_attn4_cuda_d8eaf3c",
   "version": 1,
   "kernels-minver": "0.14.0",
   "license": "BSD-3-Clause",
@@ -18,7 +18,7 @@
     "algorithm": "sha256",
     "files": {
       "__init__.py": "9nhmToMqhkzqb88qdOhfpDICvN3LHSZhEM8HXa7VlcU=",
-      "_ops.py": "PVG5218SwxBt8nM52gD8xBjus4sHeK7/H9pZkvPRxCc=",
       "_private_for_testing.py": "QXVDjtjb5NEXpgkZ93UyWJgHbrhi757Jlc8lkkTKETw=",
       "ampere_helpers.py": "ytrBcKfaN54nw20EQ2BIDXEM+ojQgtrSud7NWOSEcRE=",
       "barrier.py": "dnr4B6p1IbjRXubJU09HRaetIiSw2iuBbMScy56mwRk=",
@@ -73,6 +73,7 @@
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       "sm100_hd256_2cta_fmha_forward.py": "aJ0icWUbC3D2iLlj8SDXb+eaM0/U4mljFlIaH8iEZd4=",
       "softmax.py": "eCMvLFCXjlrgm0s24D5rrdbFFRMyah1ESWjB3BEgLu4=",
       "testing.py": "M0K0R1EmZm5b/wUDFs0qWGhS98gusj/SEXJHDMQKFf8=",
       "tile_scheduler.py": "ELRFy6rI+J+8Z2fMDLxYrCiuUMSaBLa4h10dIe27bmA=",
       "topk_gather_kv.py": "WchMfXog4eIIIOhTKu0vE5k3dfn41jVqrl9wtafJvRw=",
@@ -81,12 +82,12 @@
   },
   "provenance": {
     "kernel-builder": {
-      "version": "0.17.0-dev0",
-      "commit": "a7f0afdb29a6a3372b1d47180cc0c182454c5e3b",
       "dirty": false
     },
     "kernel": {
-      "commit": "d8eaf3cbe010f4795d0b0c4b0103862387ccdc97",
       "dirty": false
     }
   }

 {
   "name": "flash-attn4",
+  "id": "_flash_attn4_cuda_fe2bb66",
   "version": 1,
   "kernels-minver": "0.14.0",
   "license": "BSD-3-Clause",
     "algorithm": "sha256",
     "files": {
       "__init__.py": "9nhmToMqhkzqb88qdOhfpDICvN3LHSZhEM8HXa7VlcU=",
+      "_ops.py": "8hlPAUtGYqw/G4b8+0+ISwpDNXBEv/vFUAvreZZCZJs=",
       "_private_for_testing.py": "QXVDjtjb5NEXpgkZ93UyWJgHbrhi757Jlc8lkkTKETw=",
       "ampere_helpers.py": "ytrBcKfaN54nw20EQ2BIDXEM+ojQgtrSud7NWOSEcRE=",
       "barrier.py": "dnr4B6p1IbjRXubJU09HRaetIiSw2iuBbMScy56mwRk=",
       "sm100_hd256_2cta_fmha_backward_dqkernel.py": "SKQ8lUEl1P4ZcsHiMaGBqQJFL2o0oZTJhF8oOx6iXDs=",
       "sm100_hd256_2cta_fmha_forward.py": "aJ0icWUbC3D2iLlj8SDXb+eaM0/U4mljFlIaH8iEZd4=",
       "softmax.py": "eCMvLFCXjlrgm0s24D5rrdbFFRMyah1ESWjB3BEgLu4=",
+      "symbols.json": "0HMhyU/quAYAqu1USFWSJTBCCekIJ6CaTDl6+Kj4tBE=",
       "testing.py": "M0K0R1EmZm5b/wUDFs0qWGhS98gusj/SEXJHDMQKFf8=",
       "tile_scheduler.py": "ELRFy6rI+J+8Z2fMDLxYrCiuUMSaBLa4h10dIe27bmA=",
       "topk_gather_kv.py": "WchMfXog4eIIIOhTKu0vE5k3dfn41jVqrl9wtafJvRw=",
   },
   "provenance": {
     "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
       "dirty": false
     },
     "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
       "dirty": false
     }
   }

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build/torch-cuda/symbols.json ADDED Viewed

	@@ -0,0 +1,343 @@

+{
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+  "module": "_flash_attn4_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "flash_attn_func",
+      "qualname": "flash_attn_func",
+      "module": "_flash_attn4_cuda_fe2bb66.interface",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
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+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "v",
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+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "qv",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "gather_kv_indices",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "softmax_scale",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "float | None"
+          },
+          {
+            "name": "causal",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          },
+          {
+            "name": "window_size",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "(None, None)",
+            "annotation": "Tuple[int | None, int | None]"
+          },
+          {
+            "name": "learnable_sink",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "softcap",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "0.0",
+            "annotation": "float"
+          },
+          {
+            "name": "num_splits",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          },
+          {
+            "name": "pack_gqa",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "bool | None"
+          },
+          {
+            "name": "deterministic",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          },
+          {
+            "name": "score_mod",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "Callable | None"
+          },
+          {
+            "name": "score_mod_bwd",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "Callable | None"
+          },
+          {
+            "name": "mask_mod",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "Callable | None"
+          },
+          {
+            "name": "aux_tensors",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "list | None"
+          },
+          {
+            "name": "aux_scalars",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "tuple | None"
+          },
+          {
+            "name": "block_sparse_tensors",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "_flash_attn4_cuda_fe2bb66.block_sparsity.BlockSparseTensorsTorch | None"
+          },
+          {
+            "name": "block_sparse_tensors_bwd",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "_flash_attn4_cuda_fe2bb66.block_sparsity.BlockSparseTensorsTorch | None"
+          },
+          {
+            "name": "return_lse",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": null
+      }
+    },
+    {
+      "name": "flash_attn_varlen_func",
+      "qualname": "flash_attn_varlen_func",
+      "module": "_flash_attn4_cuda_fe2bb66.interface",
+      "kind": "function",
+      "doc": "Tensor arguments:\n    q:  (total_q, nheads,   hdim)   or (batch, seqlen_q, nheads,   hdim)\n    k:  (total_k, nheads_k, hdim)   or (batch, seqlen_k, nheads_k, hdim)\n    v:  (total_k, nheads_k, hdim_v) or (batch, seqlen_k, nheads_k, hdim_v)\n    qv: (total_q, nheads,   hdim_v) or (batch, seqlen_q, nheads,   hdim_v)\n    cu_seqlens_q: (batch + 1)       or seqused_q: (batch)\n    cu_seqlens_k: (batch + 1)       or seqused_k: (batch)\n    gather_kv_indices: (total_q, gather_kv_length) or\n                       (batch, seqlen_q, gather_kv_length)\n    page_table: (batch, max_num_pages_per_seq)\n\nReturn:\n   out: (total_q, nheads, hdim) or (batch, seqlen_q, nheads, hdim)\n   lse: (nheads, total_q)       or (batch, nheads, seqlen_q) if not has_qv (standard)\n        (total_q, nheads)       or (batch, seqlen_q, nheads) if has_qv\n\nExplanation of some optional arguments & decisions:\n\nqv: we write the MLA weight absorbed formula as\n    O = softmax(scale * (Q @ K.T + Qv @ V.T)) @ V\n    where Q = q_pe, Qv = q_nope, K = pe_cache, V = kv_cache.\n\nlse return shape: with Qv, MQA with nheads at least divisible by 4 is typical,\n    so we arrange for nheads as the contiguous mode for better vectorization.\n\ngather_kv_indices: used for topk sparsity with MLA absorption kernel.\n\nmin_seqlen_k: for varlen, specifies the minimum kv sequence length for any batch.\n    Used with gather_kv_indices to determine if we need oob masking.\n\nscheduler_metadata: optional tensors used by certain tile schedulers, for optimization\n    and functionality. computed in get_scheduler_metadata.\n\nseqlen_k_per_split: when using dynamic (per-batch) num_splits, can set a fixed seqlen_k to be\n    covered per split for bitwise reproducibility.\n\ndisable_scheduler_metadata: if True, ignores scheduler_metadata if it is passed and skips\n    computing metadata fresh.",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "v",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "qv",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "cu_seqlens_q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "cu_seqlens_k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "max_seqlen_q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "int | None"
+          },
+          {
+            "name": "max_seqlen_k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "int | None"
+          },
+          {
+            "name": "min_seqlen_k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "int | None"
+          },
+          {
+            "name": "seqused_q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "seqused_k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "gather_kv_indices",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "page_table",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "softmax_scale",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "float | None"
+          },
+          {
+            "name": "causal",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          },
+          {
+            "name": "window_size",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "(None, None)",
+            "annotation": "Tuple[int | None, int | None]"
+          },
+          {
+            "name": "learnable_sink",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "torch.Tensor | None"
+          },
+          {
+            "name": "softcap",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "0.0",
+            "annotation": "float"
+          },
+          {
+            "name": "num_splits",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          },
+          {
+            "name": "pack_gqa",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "bool | None"
+          },
+          {
+            "name": "deterministic",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          },
+          {
+            "name": "score_mod",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "Callable | None"
+          },
+          {
+            "name": "score_mod_bwd",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "Callable | None"
+          },
+          {
+            "name": "mask_mod",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "Callable | None"
+          },
+          {
+            "name": "block_sparse_tensors",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "_flash_attn4_cuda_fe2bb66.block_sparsity.BlockSparseTensorsTorch | None"
+          },
+          {
+            "name": "aux_tensors",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "list | None"
+          },
+          {
+            "name": "aux_scalars",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "tuple | None"
+          },
+          {
+            "name": "return_lse",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          },
+          {
+            "name": "scheduler_metadata",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "_flash_attn4_cuda_fe2bb66.prepare_scheduler.SchedulerMetadataTensorsTorch | None"
+          },
+          {
+            "name": "seqlen_k_per_split",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "None",
+            "annotation": "int | None"
+          },
+          {
+            "name": "disable_scheduler_metadata",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "False",
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": null
+      }
+    }
+  ],
+  "layers": []
+}