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[Relay][Frontend][Pytorch] Fixed ConvTranspose2D parsing #5157

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merged 4 commits into from
Mar 28, 2020
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[Relay][Frontend][Pytorch] Fixed ConvTranspose2D parsing #5157

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a9bc486
Fixed conv transpose parsing.
jwfromm Mar 27, 2020
c880790
small format change.
jwfromm Mar 27, 2020
c9e383b
Chage test module names.
jwfromm Mar 27, 2020
43363ed
Simplified test syntax.
jwfromm Mar 27, 2020
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6 changes: 5 additions & 1 deletion python/tvm/relay/frontend/pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -251,7 +251,7 @@ def _impl(inputs, input_types):
def _convolution():
def _impl(inputs, input_types):
# Use transpose or normal
use_transpose = True if inputs[6] == "1" else False
use_transpose = True if inputs[6] == 1 else False

data = inputs[0]
weight = inputs[1]
Expand All @@ -268,6 +268,10 @@ def _impl(inputs, input_types):
else:
assert "data type {} could not be parsed in conv op" % (type(weight))

# Transposed convolutions have IOHW layout.
if use_transpose:
weight_shape[0], weight_shape[1] = weight_shape[1], weight_shape[0]

channels = weight_shape[0]
groups = int(inputs[8])

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9 changes: 9 additions & 0 deletions tests/python/frontend/pytorch/test_forward.py
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Expand Up @@ -448,6 +448,14 @@ def forward(self, *args):
input_data=torch.randn((1, 8, 16, 16)))


def test_forward_conv_transpose():
torch.set_grad_enabled(False)
input_shape = [1, 3, 10, 10]
input_data = torch.rand(input_shape).float()
verify_model(torch.nn.ConvTranspose2d(3, 6, 7, bias=True), input_data=input_data)
verify_model(torch.nn.ConvTranspose2d(3, 12, 3, bias=False), input_data=input_data)


def test_forward_threshold():
torch.set_grad_enabled(False)
input_shape = [1, 3]
Expand Down Expand Up @@ -1050,6 +1058,7 @@ def forward(self, xs):
test_forward_maxpool1d()
test_forward_hardtanh()
test_forward_conv()
test_forward_conv_transpose()
test_forward_threshold()
test_forward_contiguous()
test_forward_batchnorm()
Expand Down