Function dot

nlp_class2/word2vec_tf.py:144–146

(A, B)

  # biases = tf.Variable(np.zeros(vocab_size, dtype=np.float32))

  def dot(A, B):
    C = A * B
    return tf.reduce_sum(input_tensor=C, axis=1)

  # correct middle word output
  emb_input = tf.nn.embedding_lookup(params=tfW, ids=tf_input) # 1 x D