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Hi, thanks for sharing code ! I notice that in the forward function of class GCNMultiDecoder in model_util.py
def forward(self, inputs, output_type):
connection_matrix = self.label_matrix + self.weight * self.affinity
label_vectors = self.transform(
connection_matrix.mm(self.linear.weight) / connection_matrix.sum(
1, keepdim=True))
if output_type == "open":
return self.linear(inputs)
elif output_type == 'wiki':
return F.linear(
inputs, label_vectors[:constant.ANSWER_NUM_DICT['wiki'], :],
self.linear.bias)
elif output_type == 'kb':
return F.linear(inputs,
label_vectors[:constant.ANSWER_NUM_DICT['kb'], :],
self.linear.bias)
else:
raise ValueError('Decoder error: output type not one of the valid')
when output_type is "open", the model simply do a linear transform of the input hidden state which means the model doesn't utilize the label correlation information when the label space is "open", is there something wrong here?
The text was updated successfully, but these errors were encountered:
Hi, thanks for sharing code ! I notice that in the forward function of class GCNMultiDecoder in model_util.py
when output_type is "open", the model simply do a linear transform of the input hidden state which means the model doesn't utilize the label correlation information when the label space is "open", is there something wrong here?
The text was updated successfully, but these errors were encountered: