Open mambasmile opened 5 years ago
nonzero_embeddings = tf.nn.embedding_lookup(self.weights['feature_embeddings'], self.train_features) self.summed_features_emb = tf.reduce_sum(nonzero_embeddings, 1) # None * K
self.summed_features_emb_square = tf.square(self.summed_features_emb) # None * K
The above code is in the NerualFM.py
when you computed the self.summed_features_emb, the axis you wrote is '1', I think it should be 0. Did I understand wrong?
self.summed_features_emb
Model.
_____ sumsquare part ____
get the summed up embeddings of features.
nonzero_embeddings = tf.nn.embedding_lookup(self.weights['feature_embeddings'], self.train_features) self.summed_features_emb = tf.reduce_sum(nonzero_embeddings, 1) # None * K
get the element-multiplication
self.summed_features_emb_square = tf.square(self.summed_features_emb) # None * K
The above code is in the NerualFM.py
when you computed the
self.summed_features_emb, the axis you wrote is '1', I think it should be 0. Did I understand wrong?