model_utils.py 文件源码

def multilayer_perceptron(final_output, weights, biases):
  """MLP over output with attention over enc outputs
  Args:
     final_output: [batch_size x 2*size]
  Returns:
     logit:  [batch_size x target_label_size]
  """

  # Layer 1
  layer_1 = tf.add(tf.matmul(final_output, weights["h1"]), biases["b1"])
  layer_1 = tf.nn.relu(layer_1)

  # Layer 2
  layer_2 = tf.add(tf.matmul(layer_1, weights["h2"]), biases["b2"])
  layer_2 = tf.nn.relu(layer_2)

  # output layer
  layer_out = tf.add(tf.matmul(layer_2, weights["out"]), biases["out"])

  return layer_out