| | |
|---|
| | | ): |
|---|
| | | super(DenseDecoder, self).__init__() |
|---|
| | | self.resnet1_dense = torch.nn.Linear(encoder_output_size, num_nodes_resnet1) |
|---|
| | | self.resnet1_bn = torch.nn.BatchNorm1d(num_nodes_resnet1, eps=1e-3, momentum=batchnorm_momentum) |
|---|
| | | self.resnet1_bn = torch.nn.BatchNorm1d( |
|---|
| | | num_nodes_resnet1, eps=1e-3, momentum=batchnorm_momentum |
|---|
| | | ) |
|---|
| | | |
|---|
| | | self.resnet2_dense = torch.nn.Linear(num_nodes_resnet1, num_nodes_last_layer) |
|---|
| | | self.resnet2_bn = torch.nn.BatchNorm1d(num_nodes_last_layer, eps=1e-3, momentum=batchnorm_momentum) |
|---|
| | | self.resnet2_bn = torch.nn.BatchNorm1d( |
|---|
| | | num_nodes_last_layer, eps=1e-3, momentum=batchnorm_momentum |
|---|
| | | ) |
|---|
| | | |
|---|
| | | self.output_dense = torch.nn.Linear(num_nodes_last_layer, vocab_size, bias=False) |
|---|
| | | |
|---|
