def __call__(self, premise, hypo): inp = T.concatenate([premise, hypo], axis=1) # Which axis? return softmax( self.classify( self.activation( self.L3( self.activation( self.L2(self.activation(self.L1( self.Dropout(inp)))))))))
def __call__(self, premise, hypo): inp = T.concatenate([premise * hypo, abs(premise - hypo)], axis=1) # features return softmax(self.classify(self.Dropout(inp)))
def __call__(self, premise, hypo): inp = T.concatenate([premise, hypo], axis=1) # Which axis? return softmax(self.classify( self.activation(self.L3( self.activation(self.L2( self.activation(self.L1(self.Dropout(inp)))))))))
def __call__(self, premise, hypo): inp = T.concatenate( [premise * hypo, abs(premise - hypo)], axis=1) # features return softmax(self.classify(self.Dropout(inp)))