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First, thanks for this very good code!
The original paper proposes a decoder with three fully connected layers:
FC+ReLU -> FC+ReLU -> FC+Sigmoid.
But your decoder code seens to do FC -> FC -> FC -> ReLU -> Sigmoid:
self.fc1 = nn.Linear(num_classes * output_unit_size, fc1_output_size) # input dim 10 * 16. self.fc2 = nn.Linear(fc1_output_size, fc2_output_size) self.fc3 = nn.Linear(fc2_output_size, self.fc3_output_size) # Activation functions self.relu = nn.ReLU(inplace=True) self.sigmoid = nn.Sigmoid()
Would not be correct this way?
self.fc1 = nn.Linear(num_classes * output_unit_size, fc1_output_size) # input dim 10 * 16. self.relu = nn.ReLU(inplace=True) self.fc2 = nn.Linear(fc1_output_size, fc2_output_size) self.relu = nn.ReLU(inplace=True) self.fc3 = nn.Linear(fc2_output_size, self.fc3_output_size) self.sigmoid = nn.Sigmoid()
The text was updated successfully, but these errors were encountered:
Sorry, dumb comment.
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First, thanks for this very good code!
The original paper proposes a decoder with three fully connected layers:
FC+ReLU -> FC+ReLU -> FC+Sigmoid.
But your decoder code seens to do FC -> FC -> FC -> ReLU -> Sigmoid:
Would not be correct this way?
The text was updated successfully, but these errors were encountered: