nn.py 文件源码

def __init__(self,
                 name,
                 hidden_layers,
                 input_dims,
                 output_dims):

        # tf
        self.sess = tf.get_default_session()

        with tf.variable_scope(name):
            self.obs = tf.placeholder(shape=[None, input_dims], dtype=tf.float32)
            flat_input_state = slim.flatten(self.obs, scope='flat')

            if hidden_layers == "":
                self.logits = slim.fully_connected(
                    inputs=flat_input_state,
                    num_outputs=output_dims,
                    activation_fn=None,
                    weights_initializer=tf.zeros_initializer)
            else:
                final_hidden = self.hidden_layers_starting_at(flat_input_state, hidden_layers)
                self.logits = slim.fully_connected(
                        inputs=final_hidden,
                        num_outputs=output_dims,
                        activation_fn=None)