mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
52 lines
2.0 KiB
52 lines
2.0 KiB
import torch
|
|
from torch.nn import functional as F
|
|
|
|
from colossalai.fx.tracer.meta_patch import patched_function
|
|
from colossalai.testing import clear_cache_before_run
|
|
|
|
|
|
@clear_cache_before_run()
|
|
def test_conv():
|
|
# test F.conv_1d
|
|
data_1d = torch.rand(3, 16, 10)
|
|
weight_1d = torch.rand(3, 16, 3)
|
|
out_1d = F.conv1d(data_1d, weight_1d)
|
|
patched_out_1d = patched_function.torch_nn_functional_conv1d(data_1d, weight_1d)
|
|
assert out_1d.shape == patched_out_1d.shape
|
|
|
|
# test F.conv_transpose1d
|
|
weight_1d = torch.transpose(weight_1d, 0, 1)
|
|
out_transpose_1d = F.conv_transpose1d(data_1d, weight_1d)
|
|
patched_out_transpose_1d = patched_function.torch_nn_functional_convtranspose1d(data_1d, weight_1d)
|
|
assert out_transpose_1d.shape == patched_out_transpose_1d.shape
|
|
|
|
# test F.conv2d
|
|
data_2d = torch.rand(3, 16, 10, 10)
|
|
weight_2d = torch.rand(3, 16, 3, 3)
|
|
out_2d = F.conv2d(data_2d, weight_2d)
|
|
patched_out_2d = patched_function.torch_nn_functional_conv2d(data_2d, weight_2d)
|
|
assert out_2d.shape == patched_out_2d.shape
|
|
|
|
# test F.conv_transpose2d
|
|
weight_2d = torch.transpose(weight_2d, 0, 1)
|
|
out_transpose_2d = F.conv_transpose2d(data_2d, weight_2d)
|
|
patched_out_transpose_2d = patched_function.torch_nn_functional_convtranspose2d(data_2d, weight_2d)
|
|
assert out_transpose_2d.shape == patched_out_transpose_2d.shape
|
|
|
|
# test F.conv3d
|
|
data_3d = torch.rand(3, 16, 10, 10, 10)
|
|
weight_3d = torch.rand(3, 16, 3, 3, 3)
|
|
out_3d = F.conv3d(data_3d, weight_3d)
|
|
patched_out_3d = patched_function.torch_nn_functional_conv3d(data_3d, weight_3d)
|
|
assert out_3d.shape == patched_out_3d.shape
|
|
|
|
# test F.conv_transpose3d
|
|
weight_3d = torch.transpose(weight_3d, 0, 1)
|
|
out_transpose_3d = F.conv_transpose3d(data_3d, weight_3d)
|
|
patched_out_transpose_3d = patched_function.torch_nn_functional_convtranspose3d(data_3d, weight_3d)
|
|
assert out_transpose_3d.shape == patched_out_transpose_3d.shape
|
|
|
|
|
|
if __name__ == "__main__":
|
|
test_conv()
|