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292 lines
12 KiB
Python
292 lines
12 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from unittest.mock import patch
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import pytest
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import torch
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from vllm.attention.selector import _cached_get_attn_backend, get_attn_backend
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from vllm.platforms import current_platform
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from vllm.platforms.cpu import CpuPlatform
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from vllm.platforms.cuda import CudaPlatform
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from vllm.platforms.rocm import RocmPlatform
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@pytest.fixture(autouse=True)
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def clear_cache():
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"""Clear lru cache to ensure each test case runs without caching."""
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_cached_get_attn_backend.cache_clear()
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# Define MLA and non-MLA backends separately
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DEVICE_MLA_BACKENDS = {
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"cuda": [
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"TRITON_MLA",
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"FLASHMLA",
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"FLASHINFER_MLA",
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"FLASH_ATTN_MLA",
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"CUTLASS_MLA",
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],
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"hip": ["TRITON_MLA", "ROCM_AITER_MLA"],
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"cpu": [],
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}
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DEVICE_REGULAR_ATTN_BACKENDS = {
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"cuda": ["FLASHINFER", "FLASH_ATTN"],
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"hip": ["ROCM_ATTN"],
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"cpu": ["CPU_ATTN"],
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}
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DEVICE_MLA_BLOCK_SIZES = {
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"cuda": [16, 64], # CUDA supports both standard and extended block sizes
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"hip": [16, 1], # HIP requires special handling for block_size=1
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# "cpu": [16] # CPU uses fixed block size from test cases
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"cpu": [], # FIXME(woosuk): Temporarily disable CPU tests
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}
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def generate_params():
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is_rocm = current_platform.is_rocm()
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params = []
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device_list = ["cuda", "cpu"] if not is_rocm else ["hip", "cpu"]
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for use_mla in [True, False]:
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for device in device_list:
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backends = (
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DEVICE_MLA_BACKENDS[device]
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if use_mla
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else DEVICE_REGULAR_ATTN_BACKENDS[device]
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)
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for name in backends:
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block_sizes = DEVICE_MLA_BLOCK_SIZES[device] if use_mla else [16]
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for block_size in block_sizes:
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params.append(
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pytest.param(
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device,
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name,
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use_mla,
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block_size,
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id=f"{device}_{name}_mla_{str(use_mla)[0]}_blks{block_size}",
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)
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)
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return params
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@pytest.mark.parametrize("device, name, use_mla, block_size", generate_params())
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def test_env(
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device: str,
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name: str,
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use_mla: bool,
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block_size: int,
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monkeypatch: pytest.MonkeyPatch,
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):
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"""Test attention backend selection with valid device-backend pairs."""
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with monkeypatch.context() as m:
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m.setenv("VLLM_ATTENTION_BACKEND", name)
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m.setenv("VLLM_MLA_DISABLE", "1" if use_mla else "0")
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if device == "cpu":
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with patch("vllm.platforms.current_platform", CpuPlatform()):
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backend = get_attn_backend(16, torch.float16, None, block_size)
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assert backend.get_name() == "CPU_ATTN"
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elif device == "hip":
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with patch("vllm.platforms.current_platform", RocmPlatform()):
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if use_mla:
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# ROCm MLA backend logic:
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# - TRITON_MLA: supported when block_size != 1
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# - ROCM_AITER_MLA: supported when block_size == 1
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# If backend is forced but doesn't match block_size,
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# should raise ValueError
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if name == "TRITON_MLA" and block_size == 1:
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# TRITON_MLA doesn't support block_size == 1
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with pytest.raises(ValueError) as exc_info:
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get_attn_backend(
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16, torch.float16, None, block_size, use_mla=use_mla
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)
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assert f"The selected backend, {name}" in str(exc_info.value)
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else:
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# Valid backend-block_size combination
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backend = get_attn_backend(
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16, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = name
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assert backend.get_name() == expected
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else:
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backend = get_attn_backend(
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16, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "ROCM_ATTN"
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assert backend.get_name() == expected
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elif device == "cuda":
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with patch("vllm.platforms.current_platform", CudaPlatform()):
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capability = torch.cuda.get_device_capability()
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if use_mla:
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# CUDA MLA backend logic:
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# - CUTLASS_MLA: only supported with block_size == 128
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# and Blackwell GPUs (SM 10.x), V1 only
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# - FLASHINFER_MLA: only supported on Blackwell GPUs
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# (SM 10.x), V1 only
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# - FLASHMLA: only supported with block_size == 64
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# - FLASH_ATTN_MLA: V1 only
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# - TRITON_MLA: fallback for other cases
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if name == "CUTLASS_MLA":
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if block_size != 128:
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# CUTLASS_MLA only supports block_size == 128
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pytest.skip("CUTLASS_MLA only supports block_size 128")
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if capability[0] != 10:
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pytest.skip("CUTLASS MLA is not supported on this platform")
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backend = get_attn_backend(
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576, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "CUTLASS_MLA"
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assert backend.get_name() == expected
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elif name == "FLASHINFER_MLA":
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if capability[0] != 10:
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pytest.skip(
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"FlashInfer MLA is not supported on this platform"
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)
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if block_size not in [32, 64]:
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# FlashInfer MLA only supports block_size 32 or 64
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pytest.skip(
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"FlashInfer MLA only supports block_size 32 or 64"
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)
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backend = get_attn_backend(
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576, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "FLASHINFER_MLA"
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assert backend.get_name() == expected
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elif name == "FLASHMLA":
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if block_size != 64:
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# FlashMLA only supports block_size == 64
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pytest.skip("FlashMLA only supports block_size 64")
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from vllm.v1.attention.backends.mla.flashmla import (
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is_flashmla_dense_supported,
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)
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is_supported, _ = is_flashmla_dense_supported()
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if not is_supported:
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pytest.skip("FlashMLA not supported on this platform")
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backend = get_attn_backend(
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576,
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torch.float16,
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None,
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block_size,
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use_mla=use_mla,
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)
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expected = name
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assert backend.get_name() == expected
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elif name == "FLASH_ATTN_MLA":
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from vllm.attention.utils.fa_utils import (
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flash_attn_supports_mla,
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)
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if not flash_attn_supports_mla():
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pytest.skip(
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"FlashAttention MLA not supported on this platform"
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)
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backend = get_attn_backend(
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576, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "FLASH_ATTN_MLA"
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assert backend.get_name() == expected
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else:
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# TRITON_MLA or other fallback
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backend = get_attn_backend(
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576, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "TRITON_MLA"
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assert backend.get_name() == expected
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elif name == "FLASHINFER":
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backend = get_attn_backend(
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64, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "FLASHINFER"
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assert backend.get_name() == expected
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elif name == "FLASH_ATTN":
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backend = get_attn_backend(
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32, torch.float16, None, block_size, use_mla=use_mla
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)
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expected = "FLASH_ATTN"
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assert backend.get_name() == expected
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@pytest.mark.parametrize("device", ["cpu", "cuda"])
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def test_fp32_fallback(device: str):
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"""Test attention backend selection with fp32."""
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if device == "cpu":
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with patch("vllm.platforms.current_platform", CpuPlatform()):
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backend = get_attn_backend(16, torch.float32, None, 16)
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assert backend.get_name() == "CPU_ATTN"
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elif device == "cuda":
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with patch("vllm.platforms.current_platform", CudaPlatform()):
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backend = get_attn_backend(16, torch.float32, None, 16)
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assert backend.get_name() == "FLEX_ATTENTION"
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def test_flash_attn(monkeypatch: pytest.MonkeyPatch):
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"""Test FlashAttn validation."""
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pytest.skip(
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"Skipping as current backend selector does not "
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"handle fallbacks when a backend is set via env var."
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)
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with monkeypatch.context() as m:
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m.setenv("VLLM_ATTENTION_BACKEND", "FLASH_ATTN")
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# Unsupported CUDA arch
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monkeypatch.setattr(torch.cuda, "get_device_capability", lambda _=None: (7, 5))
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backend = get_attn_backend(16, torch.float16, None, 16)
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assert backend.get_name() != "FLASH_ATTN"
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# Reset the monkeypatch for subsequent tests
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monkeypatch.undo()
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# Unsupported data type
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backend = get_attn_backend(16, torch.float8_e4m3fn, None, 16)
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assert backend.get_name() != "FLASH_ATTN"
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# Unsupported kv cache data type
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backend = get_attn_backend(16, torch.float16, "fp8", 16)
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assert backend.get_name() != "FLASH_ATTN"
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# Unsupported block size
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backend = get_attn_backend(16, torch.float16, None, 8)
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assert backend.get_name() != "FLASH_ATTN"
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# flash-attn is not installed
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import sys
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original_module = sys.modules.get("vllm_flash_attn")
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monkeypatch.setitem(sys.modules, "vllm_flash_attn", None)
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backend = get_attn_backend(16, torch.float16, None, 16)
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assert backend.get_name() != "FLASH_ATTN"
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# Restore the original module if it existed
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if original_module is not None:
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monkeypatch.setitem(sys.modules, "vllm_flash_attn", original_module)
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else:
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monkeypatch.delitem(sys.modules, "vllm_flash_attn", raising=False)
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# Unsupported head size
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backend = get_attn_backend(17, torch.float16, None, 16)
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assert backend.get_name() != "FLASH_ATTN"
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def test_invalid_env(monkeypatch: pytest.MonkeyPatch):
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"""Test that invalid attention backend names raise ValueError."""
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with (
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monkeypatch.context() as m,
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patch("vllm.platforms.current_platform", CudaPlatform()),
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):
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m.setenv("VLLM_ATTENTION_BACKEND", "INVALID")
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# Should raise ValueError for invalid backend
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with pytest.raises(ValueError) as exc_info:
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get_attn_backend(32, torch.float16, None, 16)
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assert "Invalid value 'INVALID'" in str(exc_info.value)
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