SYLARandlishunyang12
1c2a81f6d8
Signed-off-by: lishunyang12 <lishunyang03@gmail.com> Signed-off-by: lishunyang12 <lishunyang12@163.com> Co-authored-by: lishunyang12 <lishunyang03@gmail.com>
65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
|
|
from contextlib import nullcontext
|
|
|
|
import pytest
|
|
import torch
|
|
|
|
from vllm_omni.diffusion.attention.backends.abstract import AttentionMetadata
|
|
from vllm_omni.diffusion.attention.backends.cudnn_attn import CuDNNAttentionImpl
|
|
|
|
pytestmark = [pytest.mark.diffusion, pytest.mark.cpu, pytest.mark.core_model]
|
|
|
|
|
|
def test_cudnn_slices_valid_kv_prefix_without_padding_mask(monkeypatch):
|
|
observed = {}
|
|
|
|
def fake_sdpa(query, key, value, **kwargs):
|
|
observed.update(query=query, key=key, value=value, kwargs=kwargs)
|
|
return query
|
|
|
|
monkeypatch.setattr(
|
|
"vllm_omni.diffusion.attention.backends.cudnn_attn.sdpa_kernel",
|
|
lambda _backends: nullcontext(),
|
|
)
|
|
monkeypatch.setattr(torch.nn.functional, "scaled_dot_product_attention", fake_sdpa)
|
|
impl = CuDNNAttentionImpl(
|
|
num_heads=2,
|
|
head_size=4,
|
|
softmax_scale=0.5,
|
|
)
|
|
query = torch.randn(1, 8, 2, 4)
|
|
key = torch.randn_like(query)
|
|
value = torch.randn_like(query)
|
|
|
|
output = impl.forward_cuda(
|
|
query,
|
|
key,
|
|
value,
|
|
AttentionMetadata(extra={"valid_kv_length": 5}),
|
|
)
|
|
|
|
assert output.shape == query.shape
|
|
assert observed["query"].shape == (1, 2, 8, 4)
|
|
assert observed["key"].shape == (1, 2, 5, 4)
|
|
assert observed["value"].shape == (1, 2, 5, 4)
|
|
assert observed["kwargs"]["attn_mask"] is None
|
|
|
|
|
|
def test_cudnn_rejects_invalid_valid_kv_length():
|
|
impl = CuDNNAttentionImpl(
|
|
num_heads=2,
|
|
head_size=4,
|
|
softmax_scale=0.5,
|
|
)
|
|
query = torch.randn(1, 8, 2, 4)
|
|
|
|
with pytest.raises(ValueError, match="valid_kv_length"):
|
|
impl.forward_cuda(
|
|
query,
|
|
query,
|
|
query,
|
|
AttentionMetadata(extra={"valid_kv_length": 9}),
|
|
)
|