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Missing required positional arguments calling _output_padding in _ConvTransposeNd from torch. #2965

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Missing required positional arguments calling _output_padding in _ConvTransposeNd from torch. #2965

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50e6197
Update quant_conv.py
geoffrey-g-delhomme May 12, 2023
ccd4448
Merge pull request #1 from geoffrey-g-delhomme/geoffrey-g-delhomme-pa…
geoffrey-g-delhomme May 12, 2023
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6 changes: 3 additions & 3 deletions tools/pytorch-quantization/pytorch_quantization/nn/modules/quant_conv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -299,7 +299,7 @@ def forward(self, input, output_size=None):
if self.padding_mode != 'zeros':
raise ValueError('Only `zeros` padding mode is supported for QuantConvTranspose1d')

output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size)
output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size, 1, self.dilation)

quant_input, quant_weight = self._quant(input)
output = F.conv_transpose1d(quant_input, quant_weight, self.bias, self.stride, self.padding, output_padding,
Expand Down Expand Up @@ -339,7 +339,7 @@ def forward(self, input, output_size=None):
if self.padding_mode != 'zeros':
raise ValueError('Only `zeros` padding mode is supported for QuantConvTranspose2d')

output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size)
output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size, 2, self.dilation)

quant_input, quant_weight = self._quant(input)
output = F.conv_transpose2d(quant_input, quant_weight, self.bias, self.stride, self.padding, output_padding,
Expand Down Expand Up @@ -380,7 +380,7 @@ def forward(self, input, output_size=None):
if self.padding_mode != 'zeros':
raise ValueError('Only `zeros` padding mode is supported for QuantConvTranspose3d')

output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size)
output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size, 3, self.dilation)

quant_input, quant_weight = self._quant(input)
output = F.conv_transpose3d(quant_input, quant_weight, self.bias, self.stride, self.padding, output_padding,
Expand Down