Function hop

nlp_class3/memory_network.py:350–364

(query, story)

# define one hop
# the "query" can be the question, or the answer from the previous hop
def hop(query, story):
  # query.shape = (embedding_dim,)
  # story.shape = (num sentences, embedding_dim)
  x = Reshape((1, embedding_dim))(query) # make it (1, embedding_dim)
  x = dot([story, x], 2)
  x = Reshape((story_maxsents,))(x) # flatten it for softmax
  x = Activation('softmax')(x)
  story_weights = Reshape((story_maxsents, 1))(x) # unflatten for dotting

  # makes a new embedding
  story_embedding2 = embed_and_sum(input_story_)
  x = dot([story_weights, story_embedding2], 1)
  x = Reshape((embedding_dim,))(x)
  x = dense_layer(x)
  return x, story_embedding2, story_weights


# do the hops