Sync from v0.13
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60
vllm/model_executor/layers/fla/ops/op.py
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60
vllm/model_executor/layers/fla/ops/op.py
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# SPDX-FileCopyrightText: Songlin Yang, Yu Zhang
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#
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# This file contains code copied from the flash-linear-attention project.
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# The original source code was licensed under the MIT license and included
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# the following copyright notice:
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# Copyright (c) 2023-2025, Songlin Yang, Yu Zhang
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import os
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from vllm.triton_utils import tl, tldevice, triton
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from .utils import is_gather_supported
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if os.environ.get("FLA_USE_FAST_OPS", "0") == "1":
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exp = tldevice.fast_expf
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log = tldevice.fast_logf
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log2 = tldevice.fast_log2f
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else:
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exp = tl.exp
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log = tl.log
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log2 = tl.log2
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if not is_gather_supported:
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@triton.jit
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def gather(src, index, axis, _builder=None):
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"""
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Gather operation that works when tl.gather is not supported.
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This is a fallback implementation that returns None.
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Just to make triton compiler happy.
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"""
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return None
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else:
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gather = tl.gather
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if hasattr(triton.language, "_experimental_make_tensor_descriptor"):
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# For Triton 3.3.x
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make_tensor_descriptor = triton.language._experimental_make_tensor_descriptor
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elif hasattr(triton.language, "make_tensor_descriptor"):
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# For Triton 3.4.x and later
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make_tensor_descriptor = triton.language.make_tensor_descriptor
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else:
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"""
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Fallback implementation when TMA is not supported.
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Returns None to indicate TMA descriptors are unavailable.
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Just make triton compiler happy.
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"""
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@triton.jit
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def make_tensor_descriptor(
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base,
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shape,
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strides,
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block_shape,
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_builder=None,
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):
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return None
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