[Performance] Use forward_native for Conv3dLayer and add UT (#8375)
What this PR does / why we need it? switch Ascend conv3d forward_oot to use forward_native and add ut Does this PR introduce any user-facing change? No How was this patch tested? by CI --------- Signed-off-by: zouyizhou <zouyizhou@huawei.com>
This commit is contained in:
35
tests/ut/_310p/ops/test_conv_310.py
Normal file
35
tests/ut/_310p/ops/test_conv_310.py
Normal file
@@ -0,0 +1,35 @@
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
import torch
|
||||
from vllm.config import set_current_vllm_config
|
||||
from vllm.model_executor.layers.conv import Conv3dLayer
|
||||
|
||||
from vllm_ascend._310p.ops.conv import AscendConv3dLayer310
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def default_vllm_config():
|
||||
mock_config = MagicMock()
|
||||
mock_config.compilation_config.custom_ops = ["all"]
|
||||
with set_current_vllm_config(mock_config):
|
||||
yield mock_config
|
||||
|
||||
|
||||
def test_conv3d_310_forward_oot_uses_forward_native():
|
||||
layer = AscendConv3dLayer310(
|
||||
in_channels=2,
|
||||
out_channels=4,
|
||||
kernel_size=(2, 2, 2),
|
||||
stride=(2, 2, 2),
|
||||
bias=True,
|
||||
params_dtype=torch.float32,
|
||||
)
|
||||
x = torch.randn(1, 2, 4, 4, 4, dtype=torch.float32)
|
||||
expected = torch.randn(1, 4, 2, 2, 2, dtype=torch.float32)
|
||||
|
||||
with patch.object(Conv3dLayer, "forward_native", autospec=True, return_value=expected) as mock_forward_native:
|
||||
out = layer.forward_oot(x)
|
||||
|
||||
mock_forward_native.assert_called_once_with(layer, x)
|
||||
assert out is expected
|
||||
Reference in New Issue
Block a user