def call(self, hidden_states):
    seq_length = shape_list(tensor=hidden_states)[1]
    hidden_states = tf.reshape(tensor=hidden_states, shape=[(- 1), self.embedding_size])
    hidden_states = tf.matmul(a=hidden_states, b=self.input_embeddings.weight, transpose_b=True)
    hidden_states = tf.reshape(tensor=hidden_states, shape=[(- 1), seq_length, self.vocab_size])
    hidden_states = tf.nn.bias_add(value=hidden_states, bias=self.bias)
    return hidden_states
def call(self, hidden_states):
    seq_length = shape_list(tensor=hidden_states)[1]
    hidden_states = tf.reshape(tensor=hidden_states, shape=[(- 1), self.embedding_size])
    hidden_states = tf.matmul(a=hidden_states, b=self.input_embeddings.weight, transpose_b=True)
    hidden_states = tf.reshape(tensor=hidden_states, shape=[(- 1), seq_length, self.vocab_size])
    hidden_states = tf.nn.bias_add(value=hidden_states, bias=self.bias)
    return hidden_states