Kernels:

kernels-community
/

flash-attn3

Trusted publisher

Kernel card Files Files and versions

xet

Community

hf download hf://kernels-community/flash-attn3@v1/README.md

by Pq234 - opened Jul 6

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+88

-1271

This PR is in draft mode

Files changed (22) hide show

README.md +4 -6
build/torch-stable-abi29-cu126-aarch64-linux/__init__.py +0 -17
build/torch-stable-abi29-cu126-aarch64-linux/_ops.py +0 -9
build/torch-stable-abi29-cu126-aarch64-linux/flash_attn_config.py +0 -7
build/torch-stable-abi29-cu126-aarch64-linux/flash_attn_interface.py +0 -1127
build/torch-stable-abi29-cu126-aarch64-linux/metadata.json +0 -36
build/torch-stable-abi29-cu126-aarch64-linux/metadata.json.sigstore +0 -1
build/torch-stable-abi29-cu126-x86_64-linux/{_flash_attn3_cuda_0f52d9d.abi3.so → _flash_attn3_cuda_47281f5.abi3.so} +2 -2
build/torch-stable-abi29-cu126-x86_64-linux/_ops.py +3 -3
build/torch-stable-abi29-cu126-x86_64-linux/flash_attn3/__init__.py +26 -0
build/torch-stable-abi29-cu126-x86_64-linux/metadata.json +4 -15
build/torch-stable-abi29-cu126-x86_64-linux/metadata.json.sigstore +1 -1
build/torch-stable-abi29-cu128-x86_64-linux/{_flash_attn3_cuda_8a730d9.abi3.so → _flash_attn3_cuda_47281f5.abi3.so} +1 -1
build/torch-stable-abi29-cu128-x86_64-linux/_ops.py +3 -3
build/torch-stable-abi29-cu128-x86_64-linux/metadata.json +3 -14
build/torch-stable-abi29-cu128-x86_64-linux/metadata.json.sigstore +1 -1
build/torch-stable-abi29-cu130-x86_64-linux/_flash_attn3_cuda_0f52d9d.abi3.so +0 -3
build/{torch-stable-abi29-cu126-aarch64-linux/_flash_attn3_cuda_addf474.abi3.so → torch-stable-abi29-cu130-x86_64-linux/_flash_attn3_cuda_47281f5.abi3.so} +2 -2
build/torch-stable-abi29-cu130-x86_64-linux/_ops.py +3 -3
build/torch-stable-abi29-cu130-x86_64-linux/flash_attn3/__init__.py +26 -0
build/torch-stable-abi29-cu130-x86_64-linux/metadata.json +4 -15
build/torch-stable-abi29-cu130-x86_64-linux/metadata.json.sigstore +1 -1

README.md CHANGED Viewed

@@ -11,22 +11,20 @@ This is the repository card of kernels-community/flash-attn3 that has been pushe
 # make sure `kernels` is installed: `pip install -U kernels`
 from kernels import get_kernel
-kernel_module = get_kernel("kernels-community/flash-attn3", version=2)
-add_op_namespace_prefix = kernel_module.add_op_namespace_prefix
-add_op_namespace_prefix(...)
 ```
 ## Available functions
-- `add_op_namespace_prefix`
 - `flash_attn_combine`
 - `flash_attn_func`
 - `flash_attn_qkvpacked_func`
 - `flash_attn_varlen_func`
 - `flash_attn_with_kvcache`
 - `get_scheduler_metadata`
-- `ops`
 ## Benchmarks
-Benchmarking script is available for this kernel. Run `kernels benchmark kernels-community/flash-attn3 --version 2`.

 # make sure `kernels` is installed: `pip install -U kernels`
 from kernels import get_kernel
+kernel_module = get_kernel("kernels-community/flash-attn3", version=1)
+flash_attn_combine = kernel_module.flash_attn_combine
+flash_attn_combine(...)
 ```
 ## Available functions
 - `flash_attn_combine`
 - `flash_attn_func`
 - `flash_attn_qkvpacked_func`
 - `flash_attn_varlen_func`
 - `flash_attn_with_kvcache`
 - `get_scheduler_metadata`
 ## Benchmarks
+Benchmarking script is available for this kernel. Run `kernels benchmark kernels-community/flash-attn3 --version 1`.

build/torch-stable-abi29-cu126-aarch64-linux/__init__.py DELETED Viewed

@@ -1,17 +0,0 @@
-from .flash_attn_interface import (
-    flash_attn_combine,
-    flash_attn_func,
-    flash_attn_qkvpacked_func,
-    flash_attn_varlen_func,
-    flash_attn_with_kvcache,
-    get_scheduler_metadata,
-)
-__all__ = [
-    "flash_attn_combine",
-    "flash_attn_func",
-    "flash_attn_qkvpacked_func",
-    "flash_attn_varlen_func",
-    "flash_attn_with_kvcache",
-    "get_scheduler_metadata",
-]

build/torch-stable-abi29-cu126-aarch64-linux/_ops.py DELETED Viewed

@@ -1,9 +0,0 @@
-import torch
-from . import _flash_attn3_cuda_addf474
-ops = torch.ops._flash_attn3_cuda_addf474
-def add_op_namespace_prefix(op_name: str):
-    """
-    Prefix op by namespace.
-    """
-    return f"_flash_attn3_cuda_addf474::{op_name}"

build/torch-stable-abi29-cu126-aarch64-linux/flash_attn_config.py DELETED Viewed

@@ -1,7 +0,0 @@
-# Auto-generated by flash attention 3 setup.py
-CONFIG = {'build_flags': {'FLASHATTENTION_DISABLE_BACKWARD': False, 'FLASHATTENTION_DISABLE_SPLIT': False, 'FLASHATTENTION_DISABLE_PAGEDKV': False, 'FLASHATTENTION_DISABLE_APPENDKV': False, 'FLASHATTENTION_DISABLE_LOCAL': False, 'FLASHATTENTION_DISABLE_SOFTCAP': False, 'FLASHATTENTION_DISABLE_PACKGQA': False, 'FLASHATTENTION_DISABLE_FP16': False, 'FLASHATTENTION_DISABLE_FP8': False, 'FLASHATTENTION_DISABLE_VARLEN': False, 'FLASHATTENTION_DISABLE_CLUSTER': False, 'FLASHATTENTION_DISABLE_HDIM64': False, 'FLASHATTENTION_DISABLE_HDIM96': False, 'FLASHATTENTION_DISABLE_HDIM128': False, 'FLASHATTENTION_DISABLE_HDIM192': False, 'FLASHATTENTION_DISABLE_HDIM256': False, 'FLASHATTENTION_DISABLE_SM8x': False, 'FLASHATTENTION_ENABLE_VCOLMAJOR': False, 'FLASH_ATTENTION_DISABLE_HDIMDIFF64': False, 'FLASH_ATTENTION_DISABLE_HDIMDIFF192': False}}
-def show():
-    from pprint import pprint
-    pprint(CONFIG)

build/torch-stable-abi29-cu126-aarch64-linux/flash_attn_interface.py DELETED Viewed

@@ -1,1127 +0,0 @@
-# Copyright (c) 2023, Tri Dao.
-from typing import Optional, Union, List, Tuple
-import torch
-import torch.nn as nn
-from ._ops import ops as flash_attn_3_cuda
-from ._ops import add_op_namespace_prefix
-def maybe_contiguous(x):
-    return x.contiguous() if x is not None and x.stride(-1) != 1 else x
-def round_multiple(x, m):
-    return (x + m - 1) // m * m
-def round_up_headdim(head_size: int) -> int:
-    from .flash_attn_config import CONFIG
-    if not CONFIG["build_flags"]["FLASHATTENTION_DISABLE_HDIM64"]:
-        if head_size <= 64:
-            return 64
-    if not CONFIG["build_flags"]["FLASHATTENTION_DISABLE_HDIM96"]:
-        if head_size <= 96:
-            return 96
-    if not CONFIG["build_flags"]["FLASHATTENTION_DISABLE_HDIM128"]:
-        if head_size <= 128:
-            return 128
-    if not CONFIG["build_flags"]["FLASHATTENTION_DISABLE_HDIM192"]:
-        if head_size <= 192:
-            return 192
-    if not CONFIG["build_flags"]["FLASHATTENTION_DISABLE_HDIM256"]:
-        if head_size <= 256:
-            return 256
-    return 256
-@torch.library.custom_op(add_op_namespace_prefix("_flash_attn_forward"), mutates_args=(), device_types="cuda")
-def _flash_attn_forward(
-    q: torch.Tensor,
-    k: torch.Tensor,
-    v: torch.Tensor,
-    k_new: Optional[torch.Tensor] = None,
-    v_new: Optional[torch.Tensor] = None,
-    qv: Optional[torch.Tensor] = None,
-    out_: Optional[torch.Tensor] = None,
-    cu_seqlens_q: Optional[torch.Tensor] = None,
-    cu_seqlens_k: Optional[torch.Tensor] = None,
-    cu_seqlens_k_new: Optional[torch.Tensor] = None,
-    seqused_q: Optional[torch.Tensor] = None,
-    seqused_k: Optional[torch.Tensor] = None,
-    max_seqlen_q: Optional[int] = None,
-    max_seqlen_k: Optional[int] = None,
-    page_table: Optional[torch.Tensor] = None,
-    kv_batch_idx: Optional[torch.Tensor] = None,
-    leftpad_k: Optional[torch.Tensor] = None,
-    rotary_cos: Optional[torch.Tensor] = None,
-    rotary_sin: Optional[torch.Tensor] = None,
-    seqlens_rotary: Optional[torch.Tensor] = None,
-    q_descale: Optional[torch.Tensor] = None,
-    k_descale: Optional[torch.Tensor] = None,
-    v_descale: Optional[torch.Tensor] = None,
-    softmax_scale: Optional[float] = None,
-    causal: bool = False,
-    window_size_left: int = -1,
-    window_size_right: int = -1,
-    attention_chunk: int = 0,
-    softcap: float = 0.0,
-    rotary_interleaved: bool = True,
-    scheduler_metadata: Optional[torch.Tensor] = None,
-    num_splits: int = 1,
-    pack_gqa: Optional[bool] = None,
-    sm_margin: int = 0,
-) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
-    q, k, k_new, v_new = [maybe_contiguous(x) for x in (q, k, k_new, v_new)]
-    v = v.contiguous() if v.stride(-1) != 1 and v.stride(-3) != 1 else v
-    cu_seqlens_q, cu_seqlens_k, cu_seqlens_k_new = [
-        maybe_contiguous(x) for x in (cu_seqlens_q, cu_seqlens_k, cu_seqlens_k_new)
-    ]
-    seqused_q, seqused_k = [maybe_contiguous(x) for x in (seqused_q, seqused_k)]
-    page_table, kv_batch_idx, leftpad_k = [
-        maybe_contiguous(x) for x in (page_table, kv_batch_idx, leftpad_k)
-    ]
-    rotary_cos, rotary_sin = [maybe_contiguous(x) for x in (rotary_cos, rotary_sin)]
-    seqlens_rotary = maybe_contiguous(seqlens_rotary)
-    out, softmax_lse, out_accum, softmax_lse_accum = flash_attn_3_cuda.fwd(
-        q,
-        k,
-        v,
-        k_new,
-        v_new,
-        qv,
-        out_,
-        cu_seqlens_q,
-        cu_seqlens_k,
-        cu_seqlens_k_new,
-        seqused_q,
-        seqused_k,
-        max_seqlen_q,
-        max_seqlen_k,
-        page_table,
-        kv_batch_idx,
-        leftpad_k,
-        rotary_cos,
-        rotary_sin,
-        seqlens_rotary,
-        q_descale,
-        k_descale,
-        v_descale,
-        softmax_scale,
-        causal,
-        window_size_left,
-        window_size_right,
-        attention_chunk,
-        softcap,
-        rotary_interleaved,
-        scheduler_metadata,
-        num_splits,
-        pack_gqa,
-        sm_margin,
-    )
-    if out_accum is None:
-        out_accum = torch.tensor([], device=out.device)
-    if softmax_lse_accum is None:
-        softmax_lse_accum = torch.tensor([], device=out.device)
-    return out, softmax_lse, out_accum, softmax_lse_accum
-@torch.library.register_fake(add_op_namespace_prefix("_flash_attn_forward"))
-def _flash_attn_forward_fake(
-    q: torch.Tensor,
-    k: torch.Tensor,
-    v: torch.Tensor,
-    k_new: Optional[torch.Tensor] = None,
-    v_new: Optional[torch.Tensor] = None,
-    qv: Optional[torch.Tensor] = None,
-    out_: Optional[torch.Tensor] = None,
-    cu_seqlens_q: Optional[torch.Tensor] = None,
-    cu_seqlens_k: Optional[torch.Tensor] = None,
-    cu_seqlens_k_new: Optional[torch.Tensor] = None,
-    seqused_q: Optional[torch.Tensor] = None,
-    seqused_k: Optional[torch.Tensor] = None,
-    max_seqlen_q: Optional[int] = None,
-    max_seqlen_k: Optional[int] = None,
-    page_table: Optional[torch.Tensor] = None,
-    kv_batch_idx: Optional[torch.Tensor] = None,
-    leftpad_k: Optional[torch.Tensor] = None,
-    rotary_cos: Optional[torch.Tensor] = None,
-    rotary_sin: Optional[torch.Tensor] = None,
-    seqlens_rotary: Optional[torch.Tensor] = None,
-    q_descale: Optional[torch.Tensor] = None,
-    k_descale: Optional[torch.Tensor] = None,
-    v_descale: Optional[torch.Tensor] = None,
-    softmax_scale: Optional[float] = None,
-    causal: bool = False,
-    window_size_left: int = -1,
-    window_size_right: int = -1,
-    attention_chunk: int = 0,
-    softcap: float = 0.0,
-    rotary_interleaved: bool = True,
-    scheduler_metadata: Optional[torch.Tensor] = None,
-    num_splits: int = 1,
-    pack_gqa: Optional[bool] = None,
-    sm_margin: int = 0,
-) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
-    """
-    Symbolic fake implementation of flash attention forward.
-    Returns tensors with the correct shapes and dtypes without actual computation.
-    """
-    # Determine if we're in varlen mode
-    is_varlen_q = cu_seqlens_q is not None
-    # Get dimensions from query tensor
-    if is_varlen_q:
-        # varlen mode: q is (total_q, num_heads, head_size)
-        total_q, num_heads, head_size = q.shape
-        batch_size = cu_seqlens_q.shape[0] - 1
-        if max_seqlen_q is None:
-            raise ValueError("max_seqlen_q must be provided if cu_seqlens_q is provided")
-        seqlen_q = max_seqlen_q
-    else:
-        # batch mode: q is (batch_size, seqlen_q, num_heads, head_size)
-        batch_size, seqlen_q, num_heads, head_size = q.shape
-        total_q = batch_size * q.shape[1]
-    # Get value head dimension
-    head_size_v = v.shape[-1]
-    # Determine output dtype (FP8 inputs produce BF16 outputs)
-    q_type = q.dtype
-    if q_type == torch.float8_e4m3fn:
-        out_dtype = torch.bfloat16
-    else:
-        out_dtype = q_type
-    # Create output tensor
-    if out_ is not None:
-        # If out_ is provided, _flash_attn_forward becomes non-functional
-        raise TypeError("Tracing (torch.compile/torch.export) with pre-allocated output tensor is not supported.")
-    if is_varlen_q:
-        out = torch.empty((total_q, num_heads, head_size_v), dtype=out_dtype, device=q.device)
-    else:
-        out = torch.empty((batch_size, seqlen_q, num_heads, head_size_v), dtype=out_dtype, device=q.device)
-    # Create softmax_lse tensor
-    if is_varlen_q:
-        softmax_lse = torch.empty((num_heads, total_q), dtype=torch.float32, device=q.device)
-    else:
-        softmax_lse = torch.empty((batch_size, num_heads, seqlen_q), dtype=torch.float32, device=q.device)
-    # TODO(guilhermeleobas): Implement "get_num_splits"
-    # There's an heuristic to compute num_splits when "num_splits <= 0"
-    # assert that num_splits is > 0 for now
-    if num_splits <= 0:
-        raise ValueError(f"tracing (torch.compile/torch.export) with num_splits <= 0 not supported. Got {num_splits=}")
-    if num_splits > 1:
-        if is_varlen_q:
-            out_accum = torch.empty((num_splits, num_heads, total_q, head_size_v), dtype=torch.float32, device=q.device)
-            softmax_lse_accum = torch.empty((num_splits, num_heads, total_q), dtype=torch.float32, device=q.device)
-        else:
-            out_accum = torch.empty((num_splits, batch_size, num_heads, seqlen_q, head_size_v), dtype=torch.float32, device=q.device)
-            softmax_lse_accum = torch.empty((num_splits, batch_size, num_heads, seqlen_q), dtype=torch.float32, device=q.device)
-    else:
-        # Tensors are not set when num_splits < 1
-        out_accum = torch.tensor([], device=out.device)
-        softmax_lse_accum = torch.tensor([], device=out.device)
-    return out, softmax_lse, out_accum, softmax_lse_accum
-@torch.library.custom_op(add_op_namespace_prefix("_flash_attn_backward"), mutates_args=("dq", "dk", "dv"), device_types="cuda")
-def _flash_attn_backward(
-    dout: torch.Tensor,
-    q: torch.Tensor,
-    k: torch.Tensor,
-    v: torch.Tensor,
-    out: torch.Tensor,
-    softmax_lse: torch.Tensor,
-    cu_seqlens_q: Optional[torch.Tensor] = None,
-    cu_seqlens_k: Optional[torch.Tensor] = None,
-    sequed_q: Optional[torch.Tensor] = None,
-    sequed_k: Optional[torch.Tensor] = None,
-    max_seqlen_q: Optional[int] = None,
-    max_seqlen_k: Optional[int] = None,
-    dq: Optional[torch.Tensor] = None,
-    dk: Optional[torch.Tensor] = None,
-    dv: Optional[torch.Tensor] = None,
-    softmax_scale: Optional[float] = None,
-    is_causal: bool = False,
-    window_size_left: int = -1,
-    window_size_right: int = -1,
-    softcap: float = 0.0,
-    deterministic: bool = False,
-    sm_margin: int = 0,
-) -> torch.Tensor:
-    # dq, dk, dv are allocated by us so they should already be contiguous
-    dout, q, k, v, out = [maybe_contiguous(x) for x in (dout, q, k, v, out)]
-    softmax_d, *rest = flash_attn_3_cuda.bwd(
-        dout,
-        q,
-        k,
-        v,
-        out,
-        softmax_lse,
-        dq,
-        dk,
-        dv,
-        cu_seqlens_q,
-        cu_seqlens_k,
-        sequed_q,
-        sequed_k,
-        max_seqlen_q,
-        max_seqlen_k,
-        softmax_scale,
-        is_causal,
-        window_size_left,
-        window_size_right,
-        softcap,
-        deterministic,
-        sm_margin,
-    )
-    return softmax_d
-@torch.library.register_fake(add_op_namespace_prefix("_flash_attn_backward"))
-def _flash_attn_backward_fake(
-    dout: torch.Tensor,
-    q: torch.Tensor,
-    k: torch.Tensor,
-    v: torch.Tensor,
-    out: torch.Tensor,
-    softmax_lse: torch.Tensor,
-    cu_seqlens_q: Optional[torch.Tensor] = None,
-    cu_seqlens_k: Optional[torch.Tensor] = None,
-    sequed_q: Optional[torch.Tensor] = None,
-    sequed_k: Optional[torch.Tensor] = None,
-    max_seqlen_q: Optional[int] = None,
-    max_seqlen_k: Optional[int] = None,
-    dq: Optional[torch.Tensor] = None,
-    dk: Optional[torch.Tensor] = None,
-    dv: Optional[torch.Tensor] = None,
-    softmax_scale: Optional[float] = None,
-    is_causal: bool = False,
-    window_size_left: int = -1,
-    window_size_right: int = -1,
-    softcap: float = 0.0,
-    deterministic: bool = False,
-    sm_margin: int = 0,
-) -> torch.Tensor:
-    is_varlen_q = cu_seqlens_q is not None
-    is_varlen_k = cu_seqlens_q is not None
-    is_varlen = is_varlen_q or is_varlen_k or sequed_q is not None or sequed_k is not None
-    if not is_varlen_q:
-        batch_size = q.size(0)
-        seqlen_q = q.size(1)
-        seqlen_k = k.size(1)
-        total_q = batch_size * q.size(1)
-    else:
-        batch_size = cu_seqlens_q.size(0) - 1
-        total_q = q.size(0)
-        seqlen_q = max_seqlen_q
-        seqlen_k = max_seqlen_k
-    if window_size_left >= seqlen_k - 1:
-        window_size_left = -1
-    if window_size_right >= seqlen_q - 1:
-        window_size_right = -1
-    if is_causal:
-        window_size_right = 0
-    is_causal = window_size_left < 0 and window_size_right == 0
-    head_size = q.size(-1)
-    head_size_v = v.size(-1)
-    head_size_rounded = round_up_headdim(max(head_size, head_size_v))
-    # Hopper gpus uses cuda compute capabilities 9.0
-    cap = torch.cuda.get_device_capability(q.device)
-    arch = cap[0] * 10 + cap[1]
-    is_local = (window_size_left >= 0 or window_size_right >= 0) and not is_causal
-    if head_size_rounded <= 64:
-        kBlockM_sm90 = 96 if (is_causal and softcap > 0.0) else 128
-    elif head_size_rounded <= 96:
-        kBlockM_sm90 = 64
-    elif head_size_rounded <= 128:
-        kBlockM_sm90 = 64 if (is_causal or is_local or softcap > 0.0) else 80
-    else:
-        kBlockM_sm90 = 64
-    kBlockM_sm80 = 128 if head_size_rounded <= 64 else 64
-    kBlockM_sm86 = 64 if head_size_rounded <= 192 else 32
-    if arch >= 90:
-        kBlockM = kBlockM_sm90
-    elif arch == 86 or arch == 89:
-        kBlockM = kBlockM_sm86
-    else:
-        kBlockM = kBlockM_sm80
-    num_heads = q.shape[-2]
-    seqlen_q_rounded = round_multiple(seqlen_q, kBlockM)
-    total_q_padded_rounded = round_multiple(total_q + batch_size * kBlockM, kBlockM)
-    dq = torch.empty_like(q) if dq is None else dq
-    dk = torch.empty_like(k) if dk is None else dk
-    dv = torch.empty_like(v) if dv is None else dv
-    if not is_varlen:
-        softmax_d = torch.empty((batch_size, num_heads, seqlen_q_rounded), dtype=torch.float32, device=q.device)
-    else:
-        softmax_d = torch.empty((num_heads, total_q_padded_rounded), dtype=torch.float32, device=q.device)
-    return softmax_d
-def setup_context(ctx, inputs, output):
-    q, k, v = inputs[:3]
-    out, softmax_lse, _, _ = output
-    ctx.save_for_backward(q, k, v, out, softmax_lse)
-    ctx.softmax_scale = inputs[-11]
-    ctx.causal = inputs[-10]
-    ctx.window_size = [inputs[-9], inputs[-8]]
-    ctx.attention_chunk = inputs[-7]
-    ctx.softcap = inputs[-6]
-    ctx.sm_margin = inputs[-1]
-def _backward(ctx, dout, *grads):
-    q, k, v, out, softmax_lse = ctx.saved_tensors
-    dq, dk, dv = torch.empty_like(q), torch.empty_like(k), torch.empty_like(v)
-    _flash_attn_backward(
-        dout,
-        q,
-        k,
-        v,
-        out,
-        softmax_lse,
-        None, None, # cu_seqlens_q, cu_seqlens_k,
-        None, None, # sequed_q, sequed_k,
-        None, None, # max_seqlen_q, max_seqlen_k,
-        dq,
-        dk,
-        dv,
-        ctx.softmax_scale,
-        ctx.causal,
-        ctx.window_size[0],
-        ctx.window_size[1],
-        ctx.softcap,
-        False, # deterministic
-        ctx.sm_margin,
-    )
-    return dq, dk, dv, *((None,) * 21)
-_flash_attn_forward.register_autograd(_backward, setup_context=setup_context)
-class FlashAttnQKVPackedFunc(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        qkv,
-        softmax_scale,
-        causal,
-        q_descale=None, k_descale=None, v_descale=None,
-        window_size=(-1, -1),
-        attention_chunk=0,
-        softcap=0.0,
-        deterministic=False,
-        num_heads_q=None,
-        sm_margin=0,
-        return_softmax=False,
-    ):
-        if softmax_scale is None:
-            softmax_scale = qkv.shape[-1] ** (-0.5)
-        if qkv.dim() == 5:
-            assert qkv.shape[-3] == 3
-            q, k, v = qkv.unbind(dim=-3)
-        else:
-            assert qkv.dim() == 4
-            assert num_heads_q is not None
-            num_heads_k = (qkv.shape[2] - num_heads_q) // 2
-            assert num_heads_k * 2 + num_heads_q == qkv.shape[2]
-            q, k, v = qkv.split([num_heads_q, num_heads_k, num_heads_k], dim=-2)
-        out, softmax_lse, *rest = _flash_attn_forward(
-            q,
-            k,
-            v,
-            None, None,  # k_new, v_new
-            None,  # qv
-            None,  # out
-            None, None, None,   # cu_seqlens_q/k/k_new
-            None, None,   # seqused_q/k
-            None, None,   # max_seqlen_q/k
-            None, None, None,   # page_table, kv_batch_idx, leftpad_k,
-            None, None, None,  # rotary_cos/sin, seqlens_rotary
-            q_descale, k_descale, v_descale,
-            softmax_scale,
-            causal=causal,
-            window_size_left=window_size[0],
-            window_size_right=window_size[1],
-            attention_chunk=attention_chunk,
-            softcap=softcap,
-            sm_margin=sm_margin,
-        )
-        # ctx.save_for_backward(q, k, v, out_padded, softmax_lse)
-        ctx.save_for_backward(q, k, v, out, softmax_lse)
-        ctx.softmax_scale = softmax_scale
-        ctx.causal = causal
-        ctx.window_size = window_size
-        ctx.attention_chunk = attention_chunk
-        ctx.softcap = softcap
-        ctx.deterministic = deterministic
-        ctx.ndim = qkv.dim()
-        ctx.sm_margin = sm_margin
-        return (out, softmax_lse) if return_softmax else out
-    @staticmethod
-    def backward(ctx, dout, *args):
-        q, k, v, out, softmax_lse = ctx.saved_tensors
-        assert ctx.attention_chunk == 0, "FA3 backward does not support attention_chunk"
-        if ctx.ndim == 5:
-            qkv_shape = q.shape[:-2] + (3, *q.shape[-2:])
-            dqkv = torch.empty(qkv_shape, dtype=q.dtype, device=q.device)
-            dq, dk, dv = dqkv.unbind(dim=-3)
-        else:
-            num_heads_q = q.shape[2]
-            num_heads_k = k.shape[2]
-            qkv_shape = q.shape[:-2] + (num_heads_q + num_heads_k * 2, *q.shape[-1:])
-            dqkv = torch.empty(qkv_shape, dtype=q.dtype, device=q.device)
-            dq, dk, dv = dqkv.split([num_heads_q, num_heads_k, num_heads_k], dim=-2)
-        _flash_attn_backward(
-            dout,
-            q,
-            k,
-            v,
-            out,
-            softmax_lse,
-            None, None, # cu_seqlens_q, cu_seqlens_k,
-            None, None, # sequed_q, sequed_k,
-            None, None, # max_seqlen_q, max_seqlen_k,
-            dq,
-            dk,
-            dv,
-            ctx.softmax_scale,
-            ctx.causal,
-            ctx.window_size[0],
-            ctx.window_size[1],
-            ctx.softcap,
-            ctx.deterministic,
-            ctx.sm_margin,
-        )
-        dqkv = dqkv[..., : dout.shape[-1]]  # We could have padded the head dimension
-        return dqkv, None, None, None, None, None, None, None, None, None, None, None, None
-class FlashAttnFunc(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        q,
-        k,
-        v,
-        softmax_scale,
-        causal,
-        qv=None,
-        q_descale=None, k_descale=None, v_descale=None,
-        window_size=(-1, -1),
-        attention_chunk=0,
-        softcap=0.0,
-        num_splits=1,
-        pack_gqa=None,
-        deterministic=False,
-        sm_margin=0,
-        return_softmax=False,
-    ):
-        if softmax_scale is None:
-            softmax_scale = (q.shape[-1] + (qv.shape[-1] if qv is not None else 0)) ** (-0.5)
-        # out, q, k, v, out_padded, softmax_lse = _flash_attn_forward(
-        out, softmax_lse, *rest = _flash_attn_forward(
-            q,
-            k,
-            v,
-            None, None,  # k_new, v_new
-            qv,  # qv
-            None,  # out
-            None, None, None,   # cu_seqlens_q/k/k_new
-            None, None,   # seqused_q/k
-            None, None,   # max_seqlen_q/k
-            None, None, None,   # page_table, kv_batch_idx, leftpad_k,
-            None, None, None,  # rotary_cos/sin, seqlens_rotary
-            q_descale, k_descale, v_descale,
-            softmax_scale,
-            causal=causal,
-            window_size_left=window_size[0],
-            window_size_right=window_size[1],
-            attention_chunk=attention_chunk,
-            softcap=softcap,
-            num_splits=num_splits,
-            pack_gqa=pack_gqa,
-            sm_margin=sm_margin,
-        )
-        # ctx.save_for_backward(q, k, v, out_padded, softmax_lse)
-        ctx.save_for_backward(q, k, v, out, softmax_lse)
-        ctx.softmax_scale = softmax_scale
-        ctx.causal = causal
-        ctx.window_size = window_size
-        ctx.attention_chunk = attention_chunk
-        ctx.softcap = softcap
-        ctx.deterministic = deterministic
-        ctx.sm_margin = sm_margin
-        return (out, softmax_lse) if return_softmax else out
-    @staticmethod
-    def backward(ctx, dout, *args):
-        q, k, v, out, softmax_lse = ctx.saved_tensors
-        assert ctx.attention_chunk == 0, "FA3 backward does not support attention_chunk"
-        dq, dk, dv = torch.empty_like(q), torch.empty_like(k), torch.empty_like(v)
-        _flash_attn_backward(
-            dout,
-            q,
-            k,
-            v,
-            out,
-            softmax_lse,
-            None, None, # cu_seqlens_q, cu_seqlens_k,
-            None, None, # sequed_q, sequed_k,
-            None, None, # max_seqlen_q, max_seqlen_k,
-            dq,
-            dk,
-            dv,
-            ctx.softmax_scale,
-            ctx.causal,
-            ctx.window_size[0],
-            ctx.window_size[1],
-            ctx.softcap,
-            ctx.deterministic,
-            ctx.sm_margin,
-        )
-        dq = dq[..., : q.shape[-1]]  # We could have padded the head dimension
-        dk = dk[..., : k.shape[-1]]
-        dv = dv[..., : v.shape[-1]]
-        return dq, dk, dv, None, None, None, None, None, None, None, None, None, None, None, None, None, None
-class FlashAttnVarlenFunc(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        q,
-        k,
-        v,
-        cu_seqlens_q,
-        cu_seqlens_k,
-        seqused_q,
-        seqused_k,
-        max_seqlen_q,
-        max_seqlen_k,
-        softmax_scale,
-        causal,
-        qv=None,
-        q_descale=None, k_descale=None, v_descale=None,
-        window_size=(-1, -1),
-        attention_chunk=0,
-        softcap=0.0,
-        num_splits=1,
-        pack_gqa=None,
-        deterministic=False,
-        sm_margin=0,
-        return_softmax=False,
-    ):
-        if softmax_scale is None:
-            softmax_scale = (q.shape[-1] + (qv.shape[-1] if qv is not None else 0)) ** (-0.5)
-        # out, q, k, v, out_padded, softmax_lse = _flash_attn_varlen_forward(
-        out, softmax_lse, *rest = _flash_attn_forward(
-            q,
-            k,
-            v,
-            None, None,  # k_new, v_new
-            qv,  # qv
-            None,  # out
-            cu_seqlens_q,
-            cu_seqlens_k,
-            None,   # cu_seqlens_k_new
-            seqused_q,
-            seqused_k,
-            max_seqlen_q,
-            max_seqlen_k,
-            None, None, None,   # page_table, kv_batch_idx, leftpad_k,
-            None, None, None,  # rotary_cos/sin, seqlens_rotary
-            q_descale, k_descale, v_descale,
-            softmax_scale,
-            causal=causal,
-            window_size_left=window_size[0],
-            window_size_right=window_size[1],
-            attention_chunk=attention_chunk,
-            softcap=softcap,
-            num_splits=num_splits,
-            pack_gqa=pack_gqa,
-            sm_margin=sm_margin,
-        )
-        # ctx.save_for_backward(q, k, v, out_padded, softmax_lse, cu_seqlens_q, cu_seqlens_k, seqused_q, seqused_k)
-        ctx.save_for_backward(q, k, v, out, softmax_lse, cu_seqlens_q, cu_seqlens_k, seqused_q, seqused_k)
-        ctx.max_seqlen_q = max_seqlen_q
-        ctx.max_seqlen_k = max_seqlen_k
-        ctx.softmax_scale = softmax_scale
-        ctx.causal = causal
-        ctx.window_size = window_size
-        ctx.attention_chunk = attention_chunk
-        ctx.softcap = softcap
-        ctx.deterministic = deterministic
-        ctx.sm_margin = sm_margin
-        return (out, softmax_lse) if return_softmax else out
-    @staticmethod
-    def backward(ctx, dout, *args):
-        q, k, v, out, softmax_lse, cu_seqlens_q, cu_seqlens_k, seqused_q, seqused_k = ctx.saved_tensors
-        assert ctx.attention_chunk == 0, "FA3 backward does not support attention_chunk"
-        dq, dk, dv = torch.empty_like(q), torch.empty_like(k), torch.empty_like(v)
-        _flash_attn_backward(
-            dout,
-            q,
-            k,
-            v,
-            out,
-            softmax_lse,
-            cu_seqlens_q,
-            cu_seqlens_k,
-            seqused_q,
-            seqused_k,
-            ctx.max_seqlen_q,
-            ctx.max_seqlen_k,
-            dq,
-            dk,
-            dv,
-            ctx.softmax_scale,
-            ctx.causal,
-            ctx.window_size[0],
-            ctx.window_size[1],
-            ctx.softcap,
-            ctx.deterministic,
-            ctx.sm_margin,
-        )
-        dq = dq[..., : q.shape[-1]]  # We could have padded the head dimension
-        dk = dk[..., : k.shape[-1]]
-        dv = dv[..., : v.shape[-1]]
-        return dq, dk, dv, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None
-def flash_attn_qkvpacked_func(
-    qkv,
-    softmax_scale=None,
-    causal=False,
-    q_descale=None, k_descale=None, v_descale=None,
-    window_size=(-1, -1),
-    attention_chunk=0,
-    softcap=0.0,
-    deterministic=False,
-    num_heads_q=None,
-    sm_margin=0,
-    return_attn_probs=False,
-):
-    """dropout_p should be set to 0.0 during evaluation
-    If Q, K, V are already stacked into 1 tensor, this function will be faster than
-    calling flash_attn_func on Q, K, V since the backward pass avoids explicit concatenation
-    of the gradients of Q, K, V.
-    For multi-query and grouped-query attention (MQA/GQA), please see
-    flash_attn_kvpacked_func and flash_attn_func.
-    If window_size != (-1, -1), implements sliding window local attention. Query at position i
-    will only attend to keys between [i - window_size[0], i + window_size[1]] inclusive.
-    Arguments:
-        qkv: (batch_size, seqlen, 3, nheads, headdim)
-        dropout_p: float. Dropout probability.
-        softmax_scale: float. The scaling of QK^T before applying softmax.
-            Default to 1 / sqrt(headdim).
-        causal: bool. Whether to apply causal attention mask (e.g., for auto-regressive modeling).
-        window_size: (left, right). If not (-1, -1), implements sliding window local attention.
-        softcap: float. Anything > 0 activates softcapping attention.
-        alibi_slopes: (nheads,) or (batch_size, nheads), fp32. A bias of (-alibi_slope * |i - j|) is added to
-            the attention score of query i and key j.
-        deterministic: bool. Whether to use the deterministic implementation of the backward pass,
-            which is slightly slower and uses more memory. The forward pass is always deterministic.
-        return_attn_probs: bool. Whether to return the attention probabilities. This option is for
-           testing only. The returned probabilities are not guaranteed to be correct
-           (they might not have the right scaling).
-    Return:
-        out: (batch_size, seqlen, nheads, headdim).
-        softmax_lse [optional, if return_attn_probs=True]: (batch_size, nheads, seqlen). The
-            logsumexp of each row of the matrix QK^T * scaling (e.g., log of the softmax
-            normalization factor).
-        S_dmask [optional, if return_attn_probs=True]: (batch_size, nheads, seqlen, seqlen).
-            The output of softmax (possibly with different scaling). It also encodes the dropout
-            pattern (negative means that location was dropped, nonnegative means it was kept).
-    """
-    return FlashAttnQKVPackedFunc.apply(
-        qkv,
-        softmax_scale,
-        causal,
-        q_descale, k_descale, v_descale,
-        window_size,
-        attention_chunk,
-        softcap,
-        deterministic,
-        num_heads_q,
-        sm_margin,
-        return_attn_probs,
-    )
-def flash_attn_func(
-    q,
-    k,
-    v,
-    softmax_scale=None,
-    causal=False,
-    qv=None,
-    q_descale=None, k_descale=None, v_descale=None,
-    window_size=(-1, -1),
-    attention_chunk=0,
-    softcap=0.0,
-    num_splits=1,
-    pack_gqa=None,
-    deterministic=False,
-    sm_margin=0,
-    return_attn_probs=False,
-):
-    """dropout_p should be set to 0.0 during evaluation
-    Supports multi-query and grouped-query attention (MQA/GQA) by passing in KV with fewer heads
-    than Q. Note that the number of heads in Q must be divisible by the number of heads in KV.
-    For example, if Q has 6 heads and K, V have 2 heads, head 0, 1, 2 of Q will attention to head
-    0 of K, V, and head 3, 4, 5 of Q will attention to head 1 of K, V.
-    If causal=True, the causal mask is aligned to the bottom right corner of the attention matrix.
-    For example, if seqlen_q = 2 and seqlen_k = 5, the causal mask (1 = keep, 0 = masked out) is:
-        1 1 1 1 0
-        1 1 1 1 1
-    If seqlen_q = 5 and seqlen_k = 2, the causal mask is:
-        0 0
-        0 0
-        0 0
-        1 0
-        1 1
-    If the row of the mask is all zero, the output will be zero.
-    If window_size != (-1, -1), implements sliding window local attention. Query at position i
-    will only attend to keys between
-    [i + seqlen_k - seqlen_q - window_size[0], i + seqlen_k - seqlen_q + window_size[1]] inclusive.
-    Arguments:
-        q: (batch_size, seqlen, nheads, headdim)
-        k: (batch_size, seqlen, nheads_k, headdim)
-        v: (batch_size, seqlen, nheads_k, headdim)
-        dropout_p: float. Dropout probability.
-        softmax_scale: float. The scaling of QK^T before applying softmax.
-            Default to 1 / sqrt(headdim).
-        causal: bool. Whether to apply causal attention mask (e.g., for auto-regressive modeling).
-        window_size: (left, right). If not (-1, -1), implements sliding window local attention.
-        alibi_slopes: (nheads,) or (batch_size, nheads), fp32. A bias of
-            (-alibi_slope * |i + seqlen_k - seqlen_q - j|)
-            is added to the attention score of query i and key j.
-        deterministic: bool. Whether to use the deterministic implementation of the backward pass,
-            which is slightly slower and uses more memory. The forward pass is always deterministic.
-        return_attn_probs: bool. Whether to return the attention probabilities. This option is for
-           testing only. The returned probabilities are not guaranteed to be correct
-           (they might not have the right scaling).
-    Return:
-        out: (batch_size, seqlen, nheads, headdim).
-        softmax_lse [optional, if return_attn_probs=True]: (batch_size, nheads, seqlen). The
-            logsumexp of each row of the matrix QK^T * scaling (e.g., log of the softmax
-            normalization factor).
-    """
-    return FlashAttnFunc.apply(
-        q,
-        k,
-        v,
-        softmax_scale,
-        causal,
-        qv,
-        q_descale, k_descale, v_descale,
-        window_size,
-        attention_chunk,
-        softcap,
-        num_splits,
-        pack_gqa,
-        deterministic,
-        sm_margin,
-        return_attn_probs,
-    )
-def flash_attn_varlen_func(
-    q,
-    k,
-    v,
-    cu_seqlens_q,
-    cu_seqlens_k,
-    max_seqlen_q,
-    max_seqlen_k,
-    seqused_q=None,
-    seqused_k=None,
-    softmax_scale=None,
-    causal=False,
-    qv=None,
-    q_descale=None, k_descale=None, v_descale=None,
-    window_size=(-1, -1),
-    attention_chunk=0,
-    softcap=0.0,
-    num_splits=1,
-    pack_gqa=None,
-    deterministic=False,
-    sm_margin=0,
-    return_attn_probs=False,
-):
-    return FlashAttnVarlenFunc.apply(
-        q,
-        k,
-        v,
-        cu_seqlens_q,
-        cu_seqlens_k,
-        seqused_q,
-        seqused_k,
-        max_seqlen_q,
-        max_seqlen_k,
-        softmax_scale,
-        causal,
-        qv,
-        q_descale, k_descale, v_descale,
-        window_size,
-        attention_chunk,
-        softcap,
-        num_splits,
-        pack_gqa,
-        deterministic,
-        sm_margin,
-        return_attn_probs,
-    )
-def flash_attn_combine(out_partial, lse_partial, out=None, out_dtype=None):
-    return flash_attn_3_cuda.fwd_combine(out_partial, lse_partial, out, out_dtype)
-def flash_attn_with_kvcache(
-    q,
-    k_cache,
-    v_cache,
-    k=None,
-    v=None,
-    qv=None,
-    rotary_cos=None,
-    rotary_sin=None,
-    cache_seqlens: Optional[Union[(int, torch.Tensor)]] = None,
-    cache_batch_idx: Optional[torch.Tensor] = None,
-    cache_leftpad: Optional[torch.Tensor] = None,
-    page_table: Optional[torch.Tensor] = None,
-    cu_seqlens_q: Optional[torch.Tensor] = None,
-    cu_seqlens_k_new: Optional[torch.Tensor] = None,
-    max_seqlen_q: Optional[int] = None,
-    rotary_seqlens: Optional[torch.Tensor] = None,
-    q_descale: Optional[torch.Tensor] = None,
-    k_descale: Optional[torch.Tensor] = None,
-    v_descale: Optional[torch.Tensor] = None,
-    softmax_scale=None,
-    causal=False,
-    window_size=(-1, -1),  # -1 means infinite context window
-    attention_chunk=0,
-    softcap=0.0, # 0.0 means deactivated
-    rotary_interleaved=True,
-    scheduler_metadata=None,
-    num_splits=0,    # Can be tuned for speed
-    pack_gqa=None,   # Can be tuned for speed
-    sm_margin=0,     # Can be tuned if some SMs are used for communication
-    return_softmax_lse=False,
-):
-    """
-    If k and v are not None, k_cache and v_cache will be updated *inplace* with the new values from
-    k and v. This is useful for incremental decoding: you can pass in the cached keys/values from
-    the previous step, and update them with the new keys/values from the current step, and do
-    attention with the updated cache, all in 1 kernel.
-    If you pass in k / v, you must make sure that the cache is large enough to hold the new values.
-    For example, the KV cache could be pre-allocated with the max sequence length, and you can use
-    cache_seqlens to keep track of the current sequence lengths of each sequence in the batch.
-    Also apply rotary embedding if rotary_cos and rotary_sin are passed in. The key @k will be
-    rotated by rotary_cos and rotary_sin at indices cache_seqlens, cache_seqlens + 1, etc.
-    If causal or local (i.e., window_size != (-1, -1)), the query @q will be rotated by rotary_cos
-    and rotary_sin at indices cache_seqlens, cache_seqlens + 1, etc.
-    If not causal and not local, the query @q will be rotated by rotary_cos and rotary_sin at
-    indices cache_seqlens only (i.e. we consider all tokens in @q to be at position cache_seqlens).
-    See tests/test_flash_attn.py::test_flash_attn_kvcache for examples of how to use this function.
-    Supports multi-query and grouped-query attention (MQA/GQA) by passing in KV with fewer heads
-    than Q. Note that the number of heads in Q must be divisible by the number of heads in KV.
-    For example, if Q has 6 heads and K, V have 2 heads, head 0, 1, 2 of Q will attention to head
-    0 of K, V, and head 3, 4, 5 of Q will attention to head 1 of K, V.
-    If causal=True, the causal mask is aligned to the bottom right corner of the attention matrix.
-    For example, if seqlen_q = 2 and seqlen_k = 5, the causal mask (1 = keep, 0 = masked out) is:
-        1 1 1 1 0
-        1 1 1 1 1
-    If seqlen_q = 5 and seqlen_k = 2, the causal mask is:
-        0 0
-        0 0
-        0 0
-        1 0
-        1 1
-    If the row of the mask is all zero, the output will be zero.
-    If window_size != (-1, -1), implements sliding window local attention. Query at position i
-    will only attend to keys between
-    [i + seqlen_k - seqlen_q - window_size[0], i + seqlen_k - seqlen_q + window_size[1]] inclusive.
-    Note: Does not support backward pass.
-    Arguments:
-        q: (batch_size, seqlen, nheads, headdim)
-        k_cache: (batch_size_cache, seqlen_cache, nheads_k, headdim) if there's no page_table,
-            or (num_blocks, page_block_size, nheads_k, headdim) if there's a page_table (i.e. paged KV cache)
-            page_block_size can be arbitrary (e.g, 1, 2, 3, 64, etc.).
-        v_cache: (batch_size_cache, seqlen_cache, nheads_k, headdim_v) if there's no page_table,
-            or (num_blocks, page_block_size, nheads_k, headdim_v) if there's a page_table (i.e. paged KV cache)
-        k [optional]: (batch_size, seqlen_new, nheads_k, headdim). If not None, we concatenate
-            k with k_cache, starting at the indices specified by cache_seqlens.
-        v [optional]: (batch_size, seqlen_new, nheads_k, headdim_v). Similar to k.
-        qv [optional]: (batch_size, seqlen, nheads, headdim_v)
-        rotary_cos [optional]: (seqlen_ro, rotary_dim / 2). If not None, we apply rotary embedding
-            to k and q. Only applicable if k and v are passed in. rotary_dim must be divisible by 16.
-        rotary_sin [optional]: (seqlen_ro, rotary_dim / 2). Similar to rotary_cos.
-        cache_seqlens: int, or (batch_size,), dtype torch.int32. The sequence lengths of the
-            KV cache.
-        cache_batch_idx: (batch_size,), dtype torch.int32. The indices used to index into the KV cache.
-            If None, we assume that the batch indices are [0, 1, 2, ..., batch_size - 1].
-            If the indices are not distinct, and k and v are provided, the values updated in the cache
-                 might come from any of the duplicate indices.
-        cache_leftpad: (batch_size,), dtype torch.int32. The index that the KV cache starts. If None, assume 0.
-        page_table [optional]: (batch_size, max_num_blocks_per_seq), dtype torch.int32.
-        softmax_scale: float. The scaling of QK^T before applying softmax.
-            Default to 1 / sqrt(headdim).
-        causal: bool. Whether to apply causal attention mask (e.g., for auto-regressive modeling).
-        window_size: (left, right). If not (-1, -1), implements sliding window local attention.
-        softcap: float. Anything > 0 activates softcapping attention.
-        rotary_interleaved: bool. Only applicable if rotary_cos and rotary_sin are passed in.
-            If True, rotary embedding will combine dimensions 0 & 1, 2 & 3, etc. If False,
-            rotary embedding will combine dimensions 0 & rotary_dim / 2, 1 & rotary_dim / 2 + 1
-            (i.e. GPT-NeoX style).
-        num_splits: int. If > 1, split the key/value into this many chunks along the sequence.
-           If num_splits == 1, we don't split the key/value. If num_splits == 0, we use a heuristic
-           to automatically determine the number of splits.
-           Don't change this unless you know what you are doing.
-        return_softmax_lse: bool. Whether to return the logsumexp of the attention scores.
-    Return:
-        out: (batch_size, seqlen, nheads, headdim).
-        softmax_lse [optional, if return_softmax_lse=True]: (batch_size, nheads, seqlen). The
-            logsumexp of each row of the matrix QK^T * scaling (e.g., log of the softmax
-            normalization factor).
-    """
-    assert k_cache.stride(-1) == 1, "k_cache must have contiguous last dimension"
-    assert v_cache.stride(-1) == 1, "v_cache must have contiguous last dimension"
-    if softmax_scale is None:
-        softmax_scale = (q.shape[-1] + (qv.shape[-1] if qv is not None else 0)) ** (-0.5)
-    if cache_seqlens is not None and isinstance(cache_seqlens, int):
-        cache_seqlens = torch.full(
-            (q.shape[0],), cache_seqlens, dtype=torch.int32, device=k_cache.device
-        )
-        cache_seqlens = maybe_contiguous(cache_seqlens)
-    out, softmax_lse, *rest = _flash_attn_forward(
-        q,
-        k_cache,
-        v_cache,
-        k,
-        v,
-        qv,
-        None,  # out
-        cu_seqlens_q,
-        None,  # cu_seqlens_k
-        cu_seqlens_k_new,
-        None,  # seqused_q
-        cache_seqlens,
-        max_seqlen_q,
-        None,  # max_seqlen_k
-        page_table,
-        cache_batch_idx,
-        cache_leftpad,
-        rotary_cos,
-        rotary_sin,
-        rotary_seqlens,
-        q_descale, k_descale, v_descale,
-        softmax_scale,
-        causal=causal,
-        window_size_left=window_size[0],
-        window_size_right=window_size[1],
-        attention_chunk=attention_chunk,
-        softcap=softcap,
-        rotary_interleaved=rotary_interleaved,
-        scheduler_metadata=scheduler_metadata,
-        num_splits=num_splits,
-        pack_gqa=pack_gqa,
-        sm_margin=sm_margin,
-    )
-    # return (out, softmax_lse) if return_softmax_lse else out
-    return (out, softmax_lse, *rest) if return_softmax_lse else out
-def get_scheduler_metadata(
-    batch_size, max_seqlen_q, max_seqlen_k, num_heads_q, num_heads_kv, headdim,
-    cache_seqlens: torch.Tensor,
-    qkv_dtype=torch.bfloat16,
-    headdim_v=None,
-    cu_seqlens_q: Optional[torch.Tensor] = None,
-    cu_seqlens_k_new: Optional[torch.Tensor] = None,
-    cache_leftpad: Optional[torch.Tensor] = None,
-    page_size: Optional[int] = None,
-    max_seqlen_k_new=0,
-    causal=False,
-    window_size=(-1, -1),  # -1 means infinite context window
-    attention_chunk=0,
-    has_softcap=False,
-    num_splits=0,    # Can be tuned for speed
-    pack_gqa=None,   # Can be tuned for speed
-    sm_margin=0,     # Can be tuned if some SMs are used for communication
-):
-    cache_seqlens = maybe_contiguous(cache_seqlens)
-    if headdim_v is None:
-        headdim_v = headdim
-    scheduler_metadata = flash_attn_3_cuda.get_scheduler_metadata(
-        batch_size, max_seqlen_q, max_seqlen_k, num_heads_q, num_heads_kv, headdim, headdim_v,
-        qkv_dtype,
-        cache_seqlens,
-        cu_seqlens_q,
-        None,  # cu_seqlens_k
-        cu_seqlens_k_new,
-        None,  # seqused_q
-        cache_leftpad,
-        page_size,
-        max_seqlen_k_new,
-        causal,
-        window_size[0], window_size[1],
-        attention_chunk,
-        has_softcap,
-        num_splits,
-        pack_gqa,
-        sm_margin,
-    )
-    return scheduler_metadata

build/torch-stable-abi29-cu126-aarch64-linux/metadata.json DELETED Viewed

@@ -1,36 +0,0 @@
-{
-  "name": "flash-attn3",
-  "id": "_flash_attn3_cuda_addf474",
-  "version": 1,
-  "license": "BSD-3-Clause",
-  "python-depends": [],
-  "kernel-depends": [],
-  "backend": {
-    "type": "cuda",
-    "archs": [
-      "8.0",
-      "9.0a"
-    ]
-  },
-  "digest": {
-    "algorithm": "sha256",
-    "files": {
-      "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
-      "_flash_attn3_cuda_addf474.abi3.so": "R0iCttxlNUiJqaxkibP/ueRJt02xYQ8DLmuU2dV4iHQ=",
-      "_ops.py": "4sqwjhtKEY9fRKr7Vk2ZAG4trj5QLXAyJX7jMFQAk/c=",
-      "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
-      "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
-    }
-  },
-  "provenance": {
-    "kernel-builder": {
-      "version": "0.17.0-dev0",
-      "commit": "081dcd473f8eca27226eef1f9c47c45b86c756b5",
-      "dirty": false
-    },
-    "kernel": {
-      "commit": "addf4741fafb55b4c101b15985dfaeea7c7c2f3a",
-      "dirty": false
-    }
-  }
-}

build/torch-stable-abi29-cu126-aarch64-linux/metadata.json.sigstore DELETED Viewed

@@ -1 +0,0 @@

- {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json","verificationMaterial":{"certificate":{"rawBytes":"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"},"tlogEntries":[{"logIndex":"2615769314","logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="},"kindVersion":{"kind":"hashedrekord","version":"0.0.1"},"integratedTime":"1787825357","inclusionPromise":{"signedEntryTimestamp":"MEQCICewmT+sdmoUVbv8bEqaCkhoGJCaB9toR70A/qiEkLZaAiA4KRnj7Eb6+5BJI6wp5WXetn8qPKAzVrBsmpOx8duORQ=="},"inclusionProof":{"logIndex":"2493865052","rootHash":"Zr8NCEQrPuF8ZrKLN7K8gUvogLwd8lnyex7J366X+e0=","treeSize":"2493865063","hashes":["UsAxuHihwTM0F6jiitt44ZYWarK9+yS5g9xKuH8IW0M=","QZbRgLLSjaqmTsgTIGoGwiiaFx839XZzguuClHackG8=","e5b/AYKdh88XryIHCPwf84ng2J4aSlqqbYnpOjvJ4rw=","vBU+qvfiGbkcjGki2Tz09MjLXTtcuLWsR1ILJYbcyec=","Bz192670BP/DtrZA73Dx27TFAuIRn+gkVy7Rw2iQwYQ=","f/Hwqa6xE0m3E1jSIiKqXv2Vv9dDj1TPHN+2bcH/n2Q=","DyUe5poSVZKoV2zH+IssS94I/3KUWGNpyigpct4JDIc=","TVmA212Aoc3NvMI6wi3DWzcJdrmISdCXXMvGhdgUDPs=","QJDcRiGVOZB3ZqnStLyI6p5cHJuHYlpj9l30D6dJ4Yw=","VHkNTYfdfGLDpVFWfWKSjfjcRuvQlmuUAdBmyFPK/Jo=","Vtj0cV1JVg42BarN6IFuc9sxxwj5qjpEvAS3hvIgmqQ=","usYuW9ftMWWjBIVuil0n2P3fbsrU4FRBFZln2tQbHGQ=","65nLcE82CMT/uSWMopvTC90nO7as1YEdu7mW501kZBw=","Ht3LUeLpnjrcUg7YO0SSbg+oDasSRyW4K6209DcTr0I=","7TfDCaMWgEwSJEZd/e33b24919rF4IDJLmbqNNRNhZs=","0HfdxDt/zGugZLIuHasrdLEW9s8OaTykSSqBEDFQXdw=","SndbMKVtcTenAkwi2JBfGzD+mhexp1qJbRIY+A1JRIU=","xH/DCseLHr9eKoYT8qsORZK7zVdEGYWHuVtsVrD95wY="],"checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n2493865063\nZr8NCEQrPuF8ZrKLN7K8gUvogLwd8lnyex7J366X+e0=\n\n— rekor.sigstore.dev wNI9ajBGAiEAzBLS4PZv3u5BRf7j1Iui6Ro294Dk9+RFN1711I+WLz4CIQD/UpJXxhjZX4FJgXIs5BddGiQRJuh2+hPykMz7HryGkw==\n"}},"canonicalizedBody":"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"}],"timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"MIICyjADAgEAMIICwQYJKoZIhvcNAQcCoIICsjCCAq4CAQMxDTALBglghkgBZQMEAgEwgbcGCyqGSIb3DQEJEAEEoIGnBIGkMIGhAgEBBgkrBgEEAYO/MAIwMTANBglghkgBZQMEAgEFAAQg4c7SsE4fNL2ujrkdk41m/zgVNjA8D4tSo2cHOFUKQMQCFGThRRBmHjOwVGW4E3N3HR64gzTOGA8yMDI2MDgyNzEwMDkxNlowAwIBAaAypDAwLjEVMBMGA1UEChMMc2lnc3RvcmUuZGV2MRUwEwYDVQQDEwxzaWdzdG9yZS10c2GgADGCAdwwggHYAgEBMFEwOTEVMBMGA1UEChMMc2lnc3RvcmUuZGV2MSAwHgYDVQQDExdzaWdzdG9yZS10c2Etc2VsZnNpZ25lZAIUOhNULwyQYe68wUMvy4qOiyojiwwwCwYJYIZIAWUDBAIBoIH8MBoGCSqGSIb3DQEJAzENBgsqhkiG9w0BCRABBDAcBgkqhkiG9w0BCQUxDxcNMjYwODI3MTAwOTE2WjAvBgkqhkiG9w0BCQQxIgQg+qG4yk22r/p/MCANlXF3wmfeATi58VUJSZNGK5aVsMIwgY4GCyqGSIb3DQEJEAIvMX8wfTB7MHkEIIX5J7wHq2LKw7RDVsEO/IGyxog/2nq55thw2dE6zQW3MFUwPaQ7MDkxFTATBgNVBAoTDHNpZ3N0b3JlLmRldjEgMB4GA1UEAxMXc2lnc3RvcmUtdHNhLXNlbGZzaWduZWQCFDoTVC8MkGHuvMFDL8uKjosqI4sMMAoGCCqGSM49BAMCBGgwZgIxAN2+77Cc9kdsp2A60lgtyWDVc4ahpiGBZPoYFCL+vUZz8ZT8TJDnvRe6QjQHYwfGOwIxAJrHj97rBcjI0/q/uhpHywSZQ3II0wqjf6Uc3WXR5jBxKeiCmIMi4ROdTO0ktn2xWw=="}]}},"messageSignature":{"messageDigest":{"algorithm":"SHA2_256","digest":"9Zdh44tpNHPR/u5mHnXdjsyIfl05SJCiaQhVkt6yixM="},"signature":"MEYCIQCfgHu0GQvERN4Y2ltNA1OM8v5Rso7GqXenXjqGgUexcgIhAPUIYi5ltU84c1kT7y79IT7z3fD2WRX80g1MQPTDEJJ9"}}

build/torch-stable-abi29-cu126-x86_64-linux/{_flash_attn3_cuda_0f52d9d.abi3.so → _flash_attn3_cuda_47281f5.abi3.so} RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:504cfe6ebed9546becabdc40727c4f27197b9f368448ebc9ad9be4aa2f468c87
-size 798357424

 version https://git-lfs.github.com/spec/v1
+oid sha256:02cb8bb1ed36846eac484229dff9eb920e3dcd18bca462e467d4b1d93898052d
+size 798352168

build/torch-stable-abi29-cu126-x86_64-linux/_ops.py CHANGED Viewed

@@ -1,9 +1,9 @@
 import torch
-from . import _flash_attn3_cuda_0f52d9d
-ops = torch.ops._flash_attn3_cuda_0f52d9d
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_flash_attn3_cuda_0f52d9d::{op_name}"

 import torch
+from . import _flash_attn3_cuda_47281f5
+ops = torch.ops._flash_attn3_cuda_47281f5
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
+    return f"_flash_attn3_cuda_47281f5::{op_name}"

build/torch-stable-abi29-cu126-x86_64-linux/flash_attn3/__init__.py ADDED Viewed

	@@ -0,0 +1,26 @@

+import ctypes
+import importlib.util
+import sys
+from pathlib import Path
+from types import ModuleType
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch-stable-abi29-cu126-x86_64-linux/metadata.json CHANGED Viewed

@@ -1,10 +1,9 @@
 {
   "name": "flash-attn3",
-  "id": "_flash_attn3_cuda_0f52d9d",
   "version": 1,
   "license": "BSD-3-Clause",
   "python-depends": [],
-  "kernel-depends": [],
   "backend": {
     "type": "cuda",
     "archs": [
@@ -16,21 +15,11 @@
     "algorithm": "sha256",
     "files": {
       "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
-      "_flash_attn3_cuda_0f52d9d.abi3.so": "UEz+br7ZVGvsq9xAcnxPJxl7nzaESOvJrZvkqi9GjIc=",
-      "_ops.py": "skEK8ihOH71VCjft8pGBiJcdk5CRvJWcb81mL7YyQQQ=",
       "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
       "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
     }
-  },
-  "provenance": {
-    "kernel-builder": {
-      "version": "0.17.0-dev0",
-      "commit": "081dcd473f8eca27226eef1f9c47c45b86c756b5",
-      "dirty": false
-    },
-    "kernel": {
-      "commit": "0f52d9d81c14d81c1d5bbde875c3d85b0fa37cc7",
-      "dirty": false
-    }
   }
 }

 {
   "name": "flash-attn3",
+  "id": "_flash_attn3_cuda_47281f5",
   "version": 1,
   "license": "BSD-3-Clause",
   "python-depends": [],
   "backend": {
     "type": "cuda",
     "archs": [
     "algorithm": "sha256",
     "files": {
       "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
+      "_flash_attn3_cuda_47281f5.abi3.so": "AsuLse02hG6sSEIp3/nrkg49zRi8pGLkZ9Sx2TiYBS0=",
+      "_ops.py": "qhazHfRzv7OkC0vnHustj4UksH6An4mU8dLo91m2ziQ=",
+      "flash_attn3/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
       "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
       "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
     }
   }
 }

build/torch-stable-abi29-cu126-x86_64-linux/metadata.json.sigstore CHANGED Viewed

@@ -1 +1 @@

- {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json", "verificationMaterial":{"certificate":{"rawBytes":"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"}, "tlogEntries":[{"logIndex":"2618837100", "logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="}, "kindVersion":{"kind":"hashedrekord", "version":"0.0.1"}, "integratedTime":"1787861585", "inclusionPromise":{"signedEntryTimestamp":"MEQCIHcyqGcGPm8CLXULv6no3dgcAlsB/fXXxwwFu1Y/z1n1AiBeooBkUfcGRpQnv/uL/Af9VF7JW3VbQteiuPFX2Ri9cA=="}, "inclusionProof":{"logIndex":"2496932838", "rootHash":"3VAb5eRBE78EzD30pMObabCcEVO7asjJKWf85MHIv4Q=", "treeSize":"2496932841", "hashes":["RlfzhXRlaVb1dWK6dyI+FoEJtlPvgxzg/iSXidy8AlI=", "Cvu7hg5YfuKVHcGyF6kHa7Ng4tdWEuBFEb3AJYHz0Og=", "Yqln5D4GTKRbwmIUXFtyl5nTrk4Km03fzJGUQMSLXyw=", "0YHhMRyM49+hBAVwguYCB9cKJfRzye2xCzB+zr7kIio=", "uB+z7Dck/2UKAnnprryhNGZQqiP8xObhgGG5budOmPE=", "ZZ7A0WF9TrltVaS1UL4yUsFfHXtS0cPB4Xg3ZPYT2tI=", "XHtByHTOI8DrY/YiGKUiyoMaLwC4vUQnDpJz0DsOfrc=", "KU/5qTnchtfh+lVBmpgbwGtW8za9KWOF/uDiYFDghnM=", "w3HaAreLxIokmrX0CllDsJ79U/1ZwiMcb0pebOjkT54=", "JQiuQMw8M2FbRIlsChY2u6mqTNQNFORoEICw/YpOWXs=", "7miArd4rv5JDTAL0CrXluOO1cZ6JqCt31WwycaYdKs8=", "LyTvxBbtFt2C77xSe3YHWz88fi+OwkikHvRTXNyMCV8=", "oXpZdinIWOxn8d4g/7Q6OdCals+/SNep+Ou+M4o98Q8=", "QutiLOAfQukwHVQ717gM+94FF/5Giel82kbXkTx/F8w=", "7TfDCaMWgEwSJEZd/e33b24919rF4IDJLmbqNNRNhZs=", "0HfdxDt/zGugZLIuHasrdLEW9s8OaTykSSqBEDFQXdw=", "SndbMKVtcTenAkwi2JBfGzD+mhexp1qJbRIY+A1JRIU=", "xH/DCseLHr9eKoYT8qsORZK7zVdEGYWHuVtsVrD95wY="], "checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n2496932841\n3VAb5eRBE78EzD30pMObabCcEVO7asjJKWf85MHIv4Q=\n\n— rekor.sigstore.dev wNI9ajBFAiAWN+Y23+vxiKvWB3cZp1HLjZs4K3U50KiNLReg2VBSYQIhAP9k5XWzOu29gLh/Uugiw+AXYUsJ8ifcmE8/nOZendJB\n"}}, "canonicalizedBody":"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"}], "timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"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"}]}}, "messageSignature":{"messageDigest":{"algorithm":"SHA2_256", "digest":"8qE5v3PG4Ib+E3at1wKfx/n9G86pdtrQFYuQpsKwKW0="}, "signature":"MEQCIFWzO5QhENotU5APDQH313CCmjjg6CzO5QPAVxOGnUE/AiAO/78XXXHlCfiTt/ajHqzhAKodexD8T0GD18VQv8Me2Q=="}}

+ {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json","verificationMaterial":{"certificate":{"rawBytes":"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"},"tlogEntries":[{"logIndex":"1973428633","logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="},"kindVersion":{"kind":"hashedrekord","version":"0.0.1"},"integratedTime":"1782518629","inclusionPromise":{"signedEntryTimestamp":"MEYCIQDCyEFVrf/PiKPN9ElmwrvSh9BX45zduf/uucUFzegx9gIhAJW7bylKgGXzFf9DOyPhOCmypspnvAIlKMfemHqQ0qaj"},"inclusionProof":{"logIndex":"1851524371","rootHash":"Qjdo30p8XWEHTPjc6VwTvdlLJc8QTYvDlWeHvtB2Vms=","treeSize":"1851524389","hashes":["3kP/uLcm6RZtuLyXpFlpjirIMACtLH0heyaRZozYX/U=","GEeVBwNLpXUqPCjU0CbY89WuFTToOHlOfvciDzmLGEw=","UPV5/kHDMx7rFEwdcOhnu9EkTlhsh4LKz2HyHdIbdG4=","ehGmdY3KgdVnjxhgPdydTLZC0xO+9iOLTeio7zwSsIE=","A7G/eMP62s0HFyL8d5LWi/ElUKeF4P9r/LDdGXVY2Ew=","XiQlWiROSRSHfkI+J/M3955iJUd9RcqSgVZJ2mlkYV0=","Wdllnp8SId/YtRn3pOdAK4C/ZxhU7UGY5BwhSftyuX0=","oJjTWHTqS/TUyXxNmX3wlyDZsnTxxJeLd1N81BbJN9Q=","KWE0KrOJD/Dq7DkhL1da9kPDp72uQzyG7H1rUNKjhSE=","F/E+IBLEkJoA0SxKVYMfSDV1fewa94v46ZNBuuH5NNg=","XlI4aVuorCLlTnjn2TYC/z1MnWgASm+mgSvhh6NUwn0=","YIvmYTmatT5c8GJFUcC+FIN+astoVJW85SRS23hm6K0=","5SicDVFW/8/mpbov3/7HmgjUm4Z/ok9MDfkpyklk/zc=","zBViQsza/o62MhKl7o4JWnBX2kwGEPVYEl7i+HPv9MA=","NDIRlqxO0IaGr94q86MIU7VCAN3yEEgOHS4loya5lu4=","daxmZaajRpZV+JxHiOYZhJBiSKN5ucqjh2WnGbHhirw=","DOCeoSMovIvLExkhIvisow9AuNXgeWs4ECkyR6EcqYU="],"checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n1851524389\nQjdo30p8XWEHTPjc6VwTvdlLJc8QTYvDlWeHvtB2Vms=\n\n— rekor.sigstore.dev wNI9ajBFAiEA4wzBghVW6Meg11MIyrtsTOrvwPDLrwDKPJhoHMO8ILMCIFoABRJLbBEhKH5N8qpdOPjSg6tTLN7EQG0FVu/C658U\n"}},"canonicalizedBody":"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"}],"timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"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"}]}},"messageSignature":{"messageDigest":{"algorithm":"SHA2_256","digest":"6RT4Ewehe+M2Wh697frP0YhOEg6qnZb8RwakpBYOpGo="},"signature":"MEUCIQCnSvf2Sz1AwoqMxT4H339QD/0cWN5R01RQIHDPYdvIJAIgESmc+dbqsYrCPIF3G/wju7e7MYpoo5qTF1jGTwBcdW4="}}

build/torch-stable-abi29-cu128-x86_64-linux/{_flash_attn3_cuda_8a730d9.abi3.so → _flash_attn3_cuda_47281f5.abi3.so} RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e7c51038223450b4841a978f88a0d2bd41f4dabc2218d395ecdaa1ee3c736a68
 size 802030296

 version https://git-lfs.github.com/spec/v1
+oid sha256:cc5e6babfafb4f539327c695c8112c66a0c273069df7c35b2a072672d102c658
 size 802030296

build/torch-stable-abi29-cu128-x86_64-linux/_ops.py CHANGED Viewed

@@ -1,9 +1,9 @@
 import torch
-from . import _flash_attn3_cuda_8a730d9
-ops = torch.ops._flash_attn3_cuda_8a730d9
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_flash_attn3_cuda_8a730d9::{op_name}"

 import torch
+from . import _flash_attn3_cuda_47281f5
+ops = torch.ops._flash_attn3_cuda_47281f5
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
+    return f"_flash_attn3_cuda_47281f5::{op_name}"

build/torch-stable-abi29-cu128-x86_64-linux/metadata.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "name": "flash-attn3",
-  "id": "_flash_attn3_cuda_8a730d9",
   "version": 1,
   "license": "BSD-3-Clause",
   "python-depends": [],
@@ -15,22 +15,11 @@
     "algorithm": "sha256",
     "files": {
       "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
-      "_flash_attn3_cuda_8a730d9.abi3.so": "58UQOCI0ULSEGpePiKDSvUH02rwiGNOV7Nqh7jxzamg=",
-      "_ops.py": "IB37k3QlN7IQi8rLoaWXzh4VROcbFVi4jSfLdb9Ew+w=",
       "flash_attn3/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
       "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
       "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
     }
-  },
-  "provenance": {
-    "kernel-builder": {
-      "version": "0.17.0-dev0",
-      "sha": "81580bb92577f2f7228661ca2a221fc052375709",
-      "dirty": false
-    },
-    "kernel": {
-      "sha": "8a730d96c37560ccf1d3e09f7bbccdc886818f33",
-      "dirty": false
-    }
   }
 }

 {
   "name": "flash-attn3",
+  "id": "_flash_attn3_cuda_47281f5",
   "version": 1,
   "license": "BSD-3-Clause",
   "python-depends": [],
     "algorithm": "sha256",
     "files": {
       "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
+      "_flash_attn3_cuda_47281f5.abi3.so": "zF5rq/r7T1OTJ8aVyBEsZqDCcwad98NbKgcmctECxlg=",
+      "_ops.py": "qhazHfRzv7OkC0vnHustj4UksH6An4mU8dLo91m2ziQ=",
       "flash_attn3/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
       "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
       "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
     }
   }
 }

build/torch-stable-abi29-cu128-x86_64-linux/metadata.json.sigstore CHANGED Viewed

@@ -1 +1 @@

- {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json","verificationMaterial":{"certificate":{"rawBytes":"MIIHTDCCBtGgAwIBAgIUBbPaF4GfHWiJF2BP+z2xfOqWX+wwCgYIKoZIzj0EAwMwNzEVMBMGA1UEChMMc2lnc3RvcmUuZGV2MR4wHAYDVQQDExVzaWdzdG9yZS1pbnRlcm1lZGlhdGUwHhcNMjYwNzA4MTY0NTUxWhcNMjYwNzA4MTY1NTUxWjAAMFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAEk6u0Xe1L6S9FFfKSj4SjjKgM+N9JXbMfTVDLt5pezHfqp7zi2N2DNugWfs9iBkQeYNQ8a+Pzk05SD+OsxwFFXqOCBfAwggXsMA4GA1UdDwEB/wQEAwIHgDATBgNVHSUEDDAKBggrBgEFBQcDAzAdBgNVHQ4EFgQUWOXruGfRmmOC+ochUvqvGmqwlccwHwYDVR0jBBgwFoAU39Ppz1YkEZb5qNjpKFWixi4YZD8wawYDVR0RAQH/BGEwX4ZdaHR0cHM6Ly9naXRodWIuY29tL2h1Z2dpbmdmYWNlL2tlcm5lbHMtY29tbXVuaXR5Ly5naXRodWIvd29ya2Zsb3dzL2J1aWxkLnlhbWxAcmVmcy9oZWFkcy9tYWluMDkGCisGAQQBg78wAQEEK2h0dHBzOi8vdG9rZW4uYWN0aW9ucy5naXRodWJ1c2VyY29udGVudC5jb20wHwYKKwYBBAGDvzABAgQRd29ya2Zsb3dfZGlzcGF0Y2gwNgYKKwYBBAGDvzABAwQoOGE3MzBkOTZjMzc1NjBjY2YxZDNlMDlmN2JiY2NkYzg4NjgxOGYzMzATBgorBgEEAYO/MAEEBAVCdWlsZDArBgorBgEEAYO/MAEFBB1odWdnaW5nZmFjZS9rZXJuZWxzLWNvbW11bml0eTAdBgorBgEEAYO/MAEGBA9yZWZzL2hlYWRzL21haW4wOwYKKwYBBAGDvzABCAQtDCtodHRwczovL3Rva2VuLmFjdGlvbnMuZ2l0aHVidXNlcmNvbnRlbnQuY29tMG0GCisGAQQBg78wAQkEXwxdaHR0cHM6Ly9naXRodWIuY29tL2h1Z2dpbmdmYWNlL2tlcm5lbHMtY29tbXVuaXR5Ly5naXRodWIvd29ya2Zsb3dzL2J1aWxkLnlhbWxAcmVmcy9oZWFkcy9tYWluMDgGCisGAQQBg78wAQoEKgwoOGE3MzBkOTZjMzc1NjBjY2YxZDNlMDlmN2JiY2NkYzg4NjgxOGYzMzAbBgorBgEEAYO/MAELBA0MC3NlbGYtaG9zdGVkMEAGCisGAQQBg78wAQwEMgwwaHR0cHM6Ly9naXRodWIuY29tL2h1Z2dpbmdmYWNlL2tlcm5lbHMtY29tbXVuaXR5MDgGCisGAQQBg78wAQ0EKgwoOGE3MzBkOTZjMzc1NjBjY2YxZDNlMDlmN2JiY2NkYzg4NjgxOGYzMzAfBgorBgEEAYO/MAEOBBEMD3JlZnMvaGVhZHMvbWFpbjAaBgorBgEEAYO/MAEPBAwMCjEwNzE0NzU1MjkwLgYKKwYBBAGDvzABEAQgDB5odHRwczovL2dpdGh1Yi5jb20vaHVnZ2luZ2ZhY2UwGAYKKwYBBAGDvzABEQQKDAgyNTcyMDc0MzBtBgorBgEEAYO/MAESBF8MXWh0dHBzOi8vZ2l0aHViLmNvbS9odWdnaW5nZmFjZS9rZXJuZWxzLWNvbW11bml0eS8uZ2l0aHViL3dvcmtmbG93cy9idWlsZC55YW1sQHJlZnMvaGVhZHMvbWFpbjA4BgorBgEEAYO/MAETBCoMKDhhNzMwZDk2YzM3NTYwY2NmMWQzZTA5ZjdiYmNjZGM4ODY4MThmMzMwIQYKKwYBBAGDvzABFAQTDBF3b3JrZmxvd19kaXNwYXRjaDBkBgorBgEEAYO/MAEVBFYMVGh0dHBzOi8vZ2l0aHViLmNvbS9odWdnaW5nZmFjZS9rZXJuZWxzLWNvbW11bml0eS9hY3Rpb25zL3J1bnMvMjg5MzExOTk3MDMvYXR0ZW1wdHMvMTAWBgorBgEEAYO/MAEWBAgMBnB1YmxpYzBGBgorBgEEAYO/MAEYBDgMNnJlcG86aHVnZ2luZ2ZhY2Uva2VybmVscy1jb21tdW5pdHk6cmVmOnJlZnMvaGVhZHMvbWFpbjCBigYKKwYBBAHWeQIEAgR8BHoAeAB2AN09MGrGxxEyYxkeHJlnNwKiSl643jyt/4eKcoAvKe6OAAABn0KfHc4AAAQDAEcwRQIgRSaXej+tkk42/vNQIBFmsUoPXmOVmbzTK62Z5WaRaW4CIQCULbQMlVKcnGJUvWibZ3MxoPgFyDHwKjs1EkKzeJb/kjAKBggqhkjOPQQDAwNpADBmAjEAgklushRgcgTaPMcLoqowUbMyR7IXzfvStS6Skb/zJ6Ohjm+QusKc6DbljWz+z1hQAjEA8NIun66yXhOhbH8fJYTF2u2WdiEoOC8yNF0RDeDWfARfQ1QOciQGFb/JgTJbFJzU"},"tlogEntries":[{"logIndex":"2118035315","logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="},"kindVersion":{"kind":"hashedrekord","version":"0.0.1"},"integratedTime":"1783529152","inclusionPromise":{"signedEntryTimestamp":"MEQCIB3e2B2G67heW9SQyQRn/+x6btXbEqF1fZzetYvyJKOGAiBrJpyKKqVO6rXxhK+Ploj6olp0TV7icpGvGB2lK8dsRQ=="},"inclusionProof":{"logIndex":"1996131053","rootHash":"83vKyngorA7aIqoKaf2MZaJVFg6lSUW0woJD/f3wjKA=","treeSize":"1996131063","hashes":["ETNiPA+FCYAg8m/E53BLdDL/BAB8kM00lA+0TebUQX8=","fVgrfNLxMjAoGtFN6e0NtB01SbwCGY9xD/aeQk0ueb0=","g+LqnIMQr/tidXza8lU8VuLHAzON173YpZNYsIvdL3o=","vtx3tgO6guw0LPj50VW0gmh9TgUqK0Mw8n/o6cFHHcM=","pt1BRaKYgN4jk6cKPNunchUXv3OVL8ZiK98gl6STwcE=","+vjSCHPmFaGdkTyrItILGTzTgaZe+SSwI76buoVmdNk=","AuJ5yZaX+ax7RYvlF2vIN8NXOhG9s88y0+UyfRJaNWU=","JGTXipcBf6+rNH7aPgajrQAqSGaN4vKPKRw+PvB8NEs=","560g9I2weWseHzpI3f9zEK9EopDHVGbzWDjki/071bw=","kxfqdkfoPYkMfiH0NX6ff9usYaftJo0K/1UNn+5yQlM=","3zUpFG7ktUxnvEcdtooG5SRvctKvdckUSOz9B1RjplM=","9q0OT+BptjINoR8zAzEP3oPUCirDQTT26JI3eJtmyZI=","rGFoGtRVfl41SgsFsU2IgUCjfRmn18jvpugaT99fFtg=","v3Rnvwdy/iZuSJqQSjxAKTt0GBmX+4XksDaltKHxXs0=","lwFfNQVdnM+UXReXH9xyhoIKaRe1KrqgBwsxZGklig0=","frI9BMUdqa/KPLUCZ9yfDzZ2Z6tglf7SvThMJqEFBKU=","Bcvbbu+tDL+zr1H2q26c2ATmVu7v/f7JIFweUu7qDK8=","WajL3ZhY6ZX9meV3VTH9TkrbM31OF4o6+7foL0Uf6PI=","cyKMKBvHkQtwb2xR5svh+YppANOVdn7X8t4DuKMxICA=","+/VZ56MsIPxMiyLAodzKXo5TEWdQp36z89qLhpzloAo=","daxmZaajRpZV+JxHiOYZhJBiSKN5ucqjh2WnGbHhirw=","DOCeoSMovIvLExkhIvisow9AuNXgeWs4ECkyR6EcqYU="],"checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n1996131063\n83vKyngorA7aIqoKaf2MZaJVFg6lSUW0woJD/f3wjKA=\n\n— rekor.sigstore.dev wNI9ajBFAiEAwuF173o7KsUM9T3wCjZZ0hw/fJ/TjrO02kKq63v02gcCIAwP6+DuMHt+RBcTVdLKB3sf+/sspPy0l8uj5AJPCuo5\n"}},"canonicalizedBody":"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"}],"timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"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"}]}},"messageSignature":{"messageDigest":{"algorithm":"SHA2_256","digest":"RGFYfLwrgx4VZdqQfkPVXXjC9rU/5B4yTlWdNfOB8zQ="},"signature":"MEQCIETJ0qdtuk7Et4Dzpwnu85zsoSFWZOUJuBqq4tQoRoKHAiAXsEtwr83j0/+a5PgYDkXppZ7mq2uKm8WiZw9hH8CPUQ=="}}

+ {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json","verificationMaterial":{"certificate":{"rawBytes":"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"},"tlogEntries":[{"logIndex":"1973428740","logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="},"kindVersion":{"kind":"hashedrekord","version":"0.0.1"},"integratedTime":"1782518630","inclusionPromise":{"signedEntryTimestamp":"MEYCIQCD7YbwkOFqOspji1aixt67T4JazCZg+BLHsm6WXZCGtQIhALNkT/Yz1g360eGvmh4U8gfKALxMy4svFNjshoZOZ9uU"},"inclusionProof":{"logIndex":"1851524478","rootHash":"6AEi5zwZD2B2DdLWDmq4RBI3SXn4+Ywmj14tLQ/kx3w=","treeSize":"1851524489","hashes":["ZVu2zOFqRnXS7dhF58+FV3YIi6T2DVBOFR5qC6pZH5Q=","SspTZBFCG/Uj7fIjQ+RCrl5HVbjkMZ+UxD5oGV5XvWM=","Edr+jIncEKsnuLmOdyIwMYzFNdS+04zyEc4NhkuwSqE=","+UEIFV8XY9jMpn5XfpoI/9VZJCXFv6ZTWDIZ0/Wjn0E=","Sta4rrWeLrBtoEumP4FMVtBr+n96AXw8W0CJfx1jhfg=","la0N1VAKKgK4FsbrjXpN28xEvPebmXEwlVYOSQf1Ofc=","qriMQl9FQH/IRSzYdiKRlmKw+LMtyFmnhn4IC/Rf3Gw=","B2e6SoLnEcazEBK3nQSgQTxsRL3eJLBp/qMOzgWGdFo=","Wdllnp8SId/YtRn3pOdAK4C/ZxhU7UGY5BwhSftyuX0=","oJjTWHTqS/TUyXxNmX3wlyDZsnTxxJeLd1N81BbJN9Q=","KWE0KrOJD/Dq7DkhL1da9kPDp72uQzyG7H1rUNKjhSE=","F/E+IBLEkJoA0SxKVYMfSDV1fewa94v46ZNBuuH5NNg=","XlI4aVuorCLlTnjn2TYC/z1MnWgASm+mgSvhh6NUwn0=","YIvmYTmatT5c8GJFUcC+FIN+astoVJW85SRS23hm6K0=","5SicDVFW/8/mpbov3/7HmgjUm4Z/ok9MDfkpyklk/zc=","zBViQsza/o62MhKl7o4JWnBX2kwGEPVYEl7i+HPv9MA=","NDIRlqxO0IaGr94q86MIU7VCAN3yEEgOHS4loya5lu4=","daxmZaajRpZV+JxHiOYZhJBiSKN5ucqjh2WnGbHhirw=","DOCeoSMovIvLExkhIvisow9AuNXgeWs4ECkyR6EcqYU="],"checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n1851524489\n6AEi5zwZD2B2DdLWDmq4RBI3SXn4+Ywmj14tLQ/kx3w=\n\n— rekor.sigstore.dev wNI9ajBFAiA9VhK/jiJog/4qoXoxf4CreYZRC1hNJsscnF/JxJYjywIhAOcU5D3RinBjZOgtuSzIbrsDjdTHFJtEU+dlZQXVyUiu\n"}},"canonicalizedBody":"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"}],"timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"MIICyjADAgEAMIICwQYJKoZIhvcNAQcCoIICsjCCAq4CAQMxDTALBglghkgBZQMEAgEwgbgGCyqGSIb3DQEJEAEEoIGoBIGlMIGiAgEBBgkrBgEEAYO/MAIwMTANBglghkgBZQMEAgEFAAQgNw/zRK3sEjj0msEXE8MOGFzyO+EAxgvzSjoiL02gnjUCFQC6gzini/bFEtVBfOrUGxr4sxlKXBgPMjAyNjA2MjcwMDAzNTBaMAMCAQGgMqQwMC4xFTATBgNVBAoTDHNpZ3N0b3JlLmRldjEVMBMGA1UEAxMMc2lnc3RvcmUtdHNhoAAxggHbMIIB1wIBATBRMDkxFTATBgNVBAoTDHNpZ3N0b3JlLmRldjEgMB4GA1UEAxMXc2lnc3RvcmUtdHNhLXNlbGZzaWduZWQCFDoTVC8MkGHuvMFDL8uKjosqI4sMMAsGCWCGSAFlAwQCAaCB/DAaBgkqhkiG9w0BCQMxDQYLKoZIhvcNAQkQAQQwHAYJKoZIhvcNAQkFMQ8XDTI2MDYyNzAwMDM1MFowLwYJKoZIhvcNAQkEMSIEIIXDl8Bhx5KTGIV7Qhrk24byBx9/HQhVBQY7hwytn+V2MIGOBgsqhkiG9w0BCRACLzF/MH0wezB5BCCF+Se8B6tiysO0Q1bBDvyBssaIP9p6uebYcNnROs0FtzBVMD2kOzA5MRUwEwYDVQQKEwxzaWdzdG9yZS5kZXYxIDAeBgNVBAMTF3NpZ3N0b3JlLXRzYS1zZWxmc2lnbmVkAhQ6E1QvDJBh7rzBQy/Lio6LKiOLDDAKBggqhkjOPQQDAgRnMGUCMDibPp4p1N7GBnUbApVOTByrzwQk1R6/d2Rn6yZKVexwR2+3152Wa0fZpvk7HIQxCAIxAObFN65lBcJBI7/4+O0uWunWzSe4VL5Ve1fh1BzE/mtrwI0PE1Py8gfMRtYYsL8l4w=="}]}},"messageSignature":{"messageDigest":{"algorithm":"SHA2_256","digest":"zAL9HHfixdBvgwl31jdxxX/wGQ4w6sQn/cTzkrmr3Cc="},"signature":"MEUCIH9ETbGoqkcMsnc1Dwl6JWEjkU9QbkOD9QiYaN5u7HwHAiEAg6cnlPnpWHYoV1gDSwLsTSEezLsY3QUBsvOZycBbpTU="}}

build/torch-stable-abi29-cu130-x86_64-linux/_flash_attn3_cuda_0f52d9d.abi3.so DELETED Viewed

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3e7e7178a8d0c67e197101b4a0d52983a4891d0e4b970316582f4d37ddfb1bac
-size 821408256

build/{torch-stable-abi29-cu126-aarch64-linux/_flash_attn3_cuda_addf474.abi3.so → torch-stable-abi29-cu130-x86_64-linux/_flash_attn3_cuda_47281f5.abi3.so} RENAMED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:474882b6dc65354889a9ac6489b3ffb9e449b74db1610f032e6b94d9d5788874
-size 780674496

 version https://git-lfs.github.com/spec/v1
+oid sha256:fe8097092fd3f9710b766b418d616d93824f9682c9cd8a8ab7d5ab98743405d4
+size 821403000

build/torch-stable-abi29-cu130-x86_64-linux/_ops.py CHANGED Viewed

@@ -1,9 +1,9 @@
 import torch
-from . import _flash_attn3_cuda_0f52d9d
-ops = torch.ops._flash_attn3_cuda_0f52d9d
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
-    return f"_flash_attn3_cuda_0f52d9d::{op_name}"

 import torch
+from . import _flash_attn3_cuda_47281f5
+ops = torch.ops._flash_attn3_cuda_47281f5
 def add_op_namespace_prefix(op_name: str):
     """
     Prefix op by namespace.
     """
+    return f"_flash_attn3_cuda_47281f5::{op_name}"

build/torch-stable-abi29-cu130-x86_64-linux/flash_attn3/__init__.py ADDED Viewed

	@@ -0,0 +1,26 @@

+import ctypes
+import importlib.util
+import sys
+from pathlib import Path
+from types import ModuleType
+def _import_from_path(file_path: Path) -> ModuleType:
+    # We cannot use the module name as-is, after adding it to `sys.modules`,
+    # it would also be used for other imports. So, we make a module name that
+    # depends on the path for it to be unique using the hex-encoded hash of
+    # the path.
+    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
+    module_name = path_hash
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None:
+        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    if module is None:
+        raise ImportError(f"Cannot load module {module_name} from spec")
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)  # type: ignore
+    return module
+globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch-stable-abi29-cu130-x86_64-linux/metadata.json CHANGED Viewed

@@ -1,10 +1,9 @@
 {
   "name": "flash-attn3",
-  "id": "_flash_attn3_cuda_0f52d9d",
   "version": 1,
   "license": "BSD-3-Clause",
   "python-depends": [],
-  "kernel-depends": [],
   "backend": {
     "type": "cuda",
     "archs": [
@@ -16,21 +15,11 @@
     "algorithm": "sha256",
     "files": {
       "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
-      "_flash_attn3_cuda_0f52d9d.abi3.so": "Pn5xeKjQxn4ZcQG0oNUpg6SJHQ5LlwMWWC9NN937G6w=",
-      "_ops.py": "skEK8ihOH71VCjft8pGBiJcdk5CRvJWcb81mL7YyQQQ=",
       "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
       "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
     }
-  },
-  "provenance": {
-    "kernel-builder": {
-      "version": "0.17.0-dev0",
-      "commit": "081dcd473f8eca27226eef1f9c47c45b86c756b5",
-      "dirty": false
-    },
-    "kernel": {
-      "commit": "0f52d9d81c14d81c1d5bbde875c3d85b0fa37cc7",
-      "dirty": false
-    }
   }
 }

 {
   "name": "flash-attn3",
+  "id": "_flash_attn3_cuda_47281f5",
   "version": 1,
   "license": "BSD-3-Clause",
   "python-depends": [],
   "backend": {
     "type": "cuda",
     "archs": [
     "algorithm": "sha256",
     "files": {
       "__init__.py": "KXVmQJM+KhWc2UqWJesupCaP+mqAvTx7yGueFATglHE=",
+      "_flash_attn3_cuda_47281f5.abi3.so": "/oCXCS/T+XELdmtBjWFtk4JPloLJzYqKt9WrmHQ0BdQ=",
+      "_ops.py": "qhazHfRzv7OkC0vnHustj4UksH6An4mU8dLo91m2ziQ=",
+      "flash_attn3/__init__.py": "DFYPlrhXwYjEqCl/8n0SmWGZV8NFml5DPhMjKfv98GY=",
       "flash_attn_config.py": "uxo+eyMcDit//8YDaS4Rtk5BTMKzTSK9tOKTjdWVe/w=",
       "flash_attn_interface.py": "y0bD2JYGMFgX6iDre3zJN2sBPuq/12N6Mo55Z+HQCNQ="
     }
   }
 }

build/torch-stable-abi29-cu130-x86_64-linux/metadata.json.sigstore CHANGED Viewed

@@ -1 +1 @@

- {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json", "verificationMaterial":{"certificate":{"rawBytes":"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"}, "tlogEntries":[{"logIndex":"2618837112", "logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="}, "kindVersion":{"kind":"hashedrekord", "version":"0.0.1"}, "integratedTime":"1787861585", "inclusionPromise":{"signedEntryTimestamp":"MEQCIDbxp0zS858yU8meowxp/LSkbxI2dmvw/rm3dJT1rI+KAiBDd4hpfifIx+LOEU37XqqBwuqJ/HA2WPlE+gZD9VL9SQ=="}, "inclusionProof":{"logIndex":"2496932850", "rootHash":"2T3dy5dbShO24qI1pPbx+iFq2dmcvNZLjEsyplVyXSc=", "treeSize":"2496932851", "hashes":["2S3YyHDfwX7jc/Nr+CStdmNtxhX8IP/6HUTLxaukqGw=", "6wGz4lftE9E5iryFHtsV2WzeWG2SD7O9zd43s1Kxbuw=", "uB+z7Dck/2UKAnnprryhNGZQqiP8xObhgGG5budOmPE=", "ZZ7A0WF9TrltVaS1UL4yUsFfHXtS0cPB4Xg3ZPYT2tI=", "XHtByHTOI8DrY/YiGKUiyoMaLwC4vUQnDpJz0DsOfrc=", "KU/5qTnchtfh+lVBmpgbwGtW8za9KWOF/uDiYFDghnM=", "w3HaAreLxIokmrX0CllDsJ79U/1ZwiMcb0pebOjkT54=", "JQiuQMw8M2FbRIlsChY2u6mqTNQNFORoEICw/YpOWXs=", "7miArd4rv5JDTAL0CrXluOO1cZ6JqCt31WwycaYdKs8=", "LyTvxBbtFt2C77xSe3YHWz88fi+OwkikHvRTXNyMCV8=", "oXpZdinIWOxn8d4g/7Q6OdCals+/SNep+Ou+M4o98Q8=", "QutiLOAfQukwHVQ717gM+94FF/5Giel82kbXkTx/F8w=", "7TfDCaMWgEwSJEZd/e33b24919rF4IDJLmbqNNRNhZs=", "0HfdxDt/zGugZLIuHasrdLEW9s8OaTykSSqBEDFQXdw=", "SndbMKVtcTenAkwi2JBfGzD+mhexp1qJbRIY+A1JRIU=", "xH/DCseLHr9eKoYT8qsORZK7zVdEGYWHuVtsVrD95wY="], "checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n2496932851\n2T3dy5dbShO24qI1pPbx+iFq2dmcvNZLjEsyplVyXSc=\n\n— rekor.sigstore.dev wNI9ajBEAiAq71f4G9BQ0U+Q32t05GBC/rGLVnbbiWIF0oWaAk3PQQIgAy1eq31lYE4I32A5Jx1o3/sZrfgIyNCYiBNbs15xH5Y=\n"}}, "canonicalizedBody":"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"}], "timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"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"}]}}, "messageSignature":{"messageDigest":{"algorithm":"SHA2_256", "digest":"JsyzgjZZbkpTv/HsyS29bGHn3B1c/mwIGNge5tnrfsw="}, "signature":"MEUCIEZl8O5jTVA1qj/Bprs9XWNbN2qqa12zVsbDgkoo1yOkAiEA3IcMfDpJhTZwpasGhuBSgk7l/ZbJi5yrGpD2abGKtCg="}}

+ {"mediaType":"application/vnd.dev.sigstore.bundle.v0.3+json","verificationMaterial":{"certificate":{"rawBytes":"MIIHTTCCBtKgAwIBAgIUCUufKkAooDHOrNzxkxxhiXjPNQ8wCgYIKoZIzj0EAwMwNzEVMBMGA1UEChMMc2lnc3RvcmUuZGV2MR4wHAYDVQQDExVzaWdzdG9yZS1pbnRlcm1lZGlhdGUwHhcNMjYwNjI3MDAwMzUwWhcNMjYwNjI3MDAxMzUwWjAAMFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAECR4C6ARLh5Urs9M2Rqx+nZt0N/PQnVZo69uHSHhGG1NKdal0L43zlJ6jUftrPaJdX9qe7FxxGeCj1+ZmV+bdBaOCBfEwggXtMA4GA1UdDwEB/wQEAwIHgDATBgNVHSUEDDAKBggrBgEFBQcDAzAdBgNVHQ4EFgQULT8vzhk2AgMY6D0aN31a7yNpi1owHwYDVR0jBBgwFoAU39Ppz1YkEZb5qNjpKFWixi4YZD8wawYDVR0RAQH/BGEwX4ZdaHR0cHM6Ly9naXRodWIuY29tL2h1Z2dpbmdmYWNlL2tlcm5lbHMtY29tbXVuaXR5Ly5naXRodWIvd29ya2Zsb3dzL2J1aWxkLnlhbWxAcmVmcy9oZWFkcy9tYWluMDkGCisGAQQBg78wAQEEK2h0dHBzOi8vdG9rZW4uYWN0aW9ucy5naXRodWJ1c2VyY29udGVudC5jb20wHwYKKwYBBAGDvzABAgQRd29ya2Zsb3dfZGlzcGF0Y2gwNgYKKwYBBAGDvzABAwQoNDcyODFmNTU5NjMyMWFlNjc1NDliZWIyZDJhYjE3NGRjYTUxMjg2NzATBgorBgEEAYO/MAEEBAVCdWlsZDArBgorBgEEAYO/MAEFBB1odWdnaW5nZmFjZS9rZXJuZWxzLWNvbW11bml0eTAdBgorBgEEAYO/MAEGBA9yZWZzL2hlYWRzL21haW4wOwYKKwYBBAGDvzABCAQtDCtodHRwczovL3Rva2VuLmFjdGlvbnMuZ2l0aHVidXNlcmNvbnRlbnQuY29tMG0GCisGAQQBg78wAQkEXwxdaHR0cHM6Ly9naXRodWIuY29tL2h1Z2dpbmdmYWNlL2tlcm5lbHMtY29tbXVuaXR5Ly5naXRodWIvd29ya2Zsb3dzL2J1aWxkLnlhbWxAcmVmcy9oZWFkcy9tYWluMDgGCisGAQQBg78wAQoEKgwoNDcyODFmNTU5NjMyMWFlNjc1NDliZWIyZDJhYjE3NGRjYTUxMjg2NzAbBgorBgEEAYO/MAELBA0MC3NlbGYtaG9zdGVkMEAGCisGAQQBg78wAQwEMgwwaHR0cHM6Ly9naXRodWIuY29tL2h1Z2dpbmdmYWNlL2tlcm5lbHMtY29tbXVuaXR5MDgGCisGAQQBg78wAQ0EKgwoNDcyODFmNTU5NjMyMWFlNjc1NDliZWIyZDJhYjE3NGRjYTUxMjg2NzAfBgorBgEEAYO/MAEOBBEMD3JlZnMvaGVhZHMvbWFpbjAaBgorBgEEAYO/MAEPBAwMCjEwNzE0NzU1MjkwLgYKKwYBBAGDvzABEAQgDB5odHRwczovL2dpdGh1Yi5jb20vaHVnZ2luZ2ZhY2UwGAYKKwYBBAGDvzABEQQKDAgyNTcyMDc0MzBtBgorBgEEAYO/MAESBF8MXWh0dHBzOi8vZ2l0aHViLmNvbS9odWdnaW5nZmFjZS9rZXJuZWxzLWNvbW11bml0eS8uZ2l0aHViL3dvcmtmbG93cy9idWlsZC55YW1sQHJlZnMvaGVhZHMvbWFpbjA4BgorBgEEAYO/MAETBCoMKDQ3MjgxZjU1OTYzMjFhZTY3NTQ5YmViMmQyYWIxNzRkY2E1MTI4NjcwIQYKKwYBBAGDvzABFAQTDBF3b3JrZmxvd19kaXNwYXRjaDBkBgorBgEEAYO/MAEVBFYMVGh0dHBzOi8vZ2l0aHViLmNvbS9odWdnaW5nZmFjZS9rZXJuZWxzLWNvbW11bml0eS9hY3Rpb25zL3J1bnMvMjgyNTE3MDAwNTMvYXR0ZW1wdHMvMTAWBgorBgEEAYO/MAEWBAgMBnB1YmxpYzBGBgorBgEEAYO/MAEYBDgMNnJlcG86aHVnZ2luZ2ZhY2Uva2VybmVscy1jb21tdW5pdHk6cmVmOnJlZnMvaGVhZHMvbWFpbjCBiwYKKwYBBAHWeQIEAgR9BHsAeQB3AN09MGrGxxEyYxkeHJlnNwKiSl643jyt/4eKcoAvKe6OAAABnwZjyh4AAAQDAEgwRgIhAKwCn95AbC62omD4U/LJgjBIDh5asopnDYfQN1L+oiJZAiEAq4jwHuo2GmCAJGf++kVGX4xwBh9EIuc2s/Zjo1APTGwwCgYIKoZIzj0EAwMDaQAwZgIxAIABeU4fM/sMN7N1Sc4SfD4L2DtFNcmiEgIZYsG1ib/ndFrQ1eMcVECoISTrdR3/igIxAM7nR5w35mNKkrX53kzkL815626coPvLAAkCaq1LRfe2BbBcbAPPUjT5RAjNK5tb6w=="},"tlogEntries":[{"logIndex":"1973428852","logId":{"keyId":"wNI9atQGlz+VWfO6LRygH4QUfY/8W4RFwiT5i5WRgB0="},"kindVersion":{"kind":"hashedrekord","version":"0.0.1"},"integratedTime":"1782518631","inclusionPromise":{"signedEntryTimestamp":"MEUCIAS3s8htVd+GX3fP6Q7RuA2O12ZG+QpzszqvkkfHn9/TAiEA6lVpnaLE3s7g+1RhhGSXgjdeiSCWqhWmGIVqWPTWmRU="},"inclusionProof":{"logIndex":"1851524590","rootHash":"KRlv4WOEhLGAxq3A0N8oS9IuTtyJm12HYniu4fKYfVI=","treeSize":"1851524613","hashes":["sL0IJgfUqJQu2yO/Fpy6EvV+XmkKJMw/4yb3wv5Yl7o=","LLTP/KG/hPqUPc8mxkPpJSHokS5C1o5T/ssOWM52aD8=","fzVmNZP+V12JAmY/o1JEY4g2YMNGReiF/s8NG+mE2gI=","aJ/5ZezFSaqxg2fX3GtgDu9ju+lpi3IM0ll07NXPVPY=","6/Ff8Rzz2rlFBGgCg4Cr7g4WmjCJkX0CJXeUqa4Mqrw=","Ip17Q8kGzrvGkfCNTaLKtzPnoeO6ep3QizuEWn09KTY=","vYyv1S6sndj979YuON1/iIs0bR6ULdfXr8/qCCSMLEo=","D7KryKA++QXmfrwCETdnsxZiy6gwMgGzvbDJZYmHQbA=","Wdllnp8SId/YtRn3pOdAK4C/ZxhU7UGY5BwhSftyuX0=","X7GxOYZ+uCUysb9vCYUNmNq8IOFSCrY2GZl9x9qRO+I=","oJjTWHTqS/TUyXxNmX3wlyDZsnTxxJeLd1N81BbJN9Q=","KWE0KrOJD/Dq7DkhL1da9kPDp72uQzyG7H1rUNKjhSE=","F/E+IBLEkJoA0SxKVYMfSDV1fewa94v46ZNBuuH5NNg=","XlI4aVuorCLlTnjn2TYC/z1MnWgASm+mgSvhh6NUwn0=","YIvmYTmatT5c8GJFUcC+FIN+astoVJW85SRS23hm6K0=","5SicDVFW/8/mpbov3/7HmgjUm4Z/ok9MDfkpyklk/zc=","zBViQsza/o62MhKl7o4JWnBX2kwGEPVYEl7i+HPv9MA=","NDIRlqxO0IaGr94q86MIU7VCAN3yEEgOHS4loya5lu4=","daxmZaajRpZV+JxHiOYZhJBiSKN5ucqjh2WnGbHhirw=","DOCeoSMovIvLExkhIvisow9AuNXgeWs4ECkyR6EcqYU="],"checkpoint":{"envelope":"rekor.sigstore.dev - 1193050959916656506\n1851524613\nKRlv4WOEhLGAxq3A0N8oS9IuTtyJm12HYniu4fKYfVI=\n\n— rekor.sigstore.dev wNI9ajBEAiAO2K5Fnyp7YVBEfgS4nYWB28POx3IN8M9kWknIvZF4MgIgVVHsoB7k7wld7tvpuM+eIIL234lgnGevFnzCMmUhsFE=\n"}},"canonicalizedBody":"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"}],"timestampVerificationData":{"rfc3161Timestamps":[{"signedTimestamp":"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"}]}},"messageSignature":{"messageDigest":{"algorithm":"SHA2_256","digest":"PIIFHQzuVeT0hPtS6Mc71H6LbFSJLe9h/Gpy2v3OxdE="},"signature":"MEUCIHFdNgtQ3uio9AfhmyDzCA9oDsiyYZWv1gjz3STN+bcMAiEArCxnj6XOyw6v1JPw4V2/Nz/rshDMU6WRzG9IbW/jCQE="}}