if pre_trained == []:
self.W = tf.Variable(tf.random_uniform([vocab_size, embedding_size], -math.sqrt(1.0/embedding_size), math.sqrt(1.0/embedding_size), seed=1234), name="W")
else:
self.W = tf.get_variable(name="W2", initializer=pre_trained) #trainable=is_trainable)
embeddings = tf.get_variable("embeddings", shape=[dim1, dim2], initializer=tf.constant_initializer(np.array(embeddings_matrix))
W = tf.get_variable(name="W", shape=embedding.shape, initializer=tf.constant_initializer(embedding), trainable=False)
