(self, x, x_mask)
return self._forward_unpadded(x, x_mask)
Can choose to either handle or ignore variable length sequences.
        Always handle padding in eval.
Can choose to either handle or ignore variable length sequences.
        Always handle padding in eval.
Can choose to either handle or ignore variable length sequences . Always handle padding in eval .
def forward(self, x, x_mask):
        """Can choose to either handle or ignore variable length sequences.
        Always handle padding in eval.
        """
        # No padding necessary.
        if x_mask.data.sum() == 0:
            return self._forward_unpadded(x, x_mask)
        # Pad if we care or if its during eval.
        #if self.padding or not self.training:
        #    return self._forward_padded(x, x_mask)
        # We don't care.
        return self._forward_unpadded(x, x_mask)
def forward ( self , x , x_mask ) : # No padding necessary. if x_mask . data . sum ( ) == 0 : return self . _forward_unpadded ( x , x_mask ) # Pad if we care or if its during eval. #if self.padding or not self.training: #    return self._forward_padded(x, x_mask) # We don't care. return self . _forward_unpadded ( x , x_mask )