mirror of
https://github.com/wassname/ray.git
synced 2026-07-07 13:05:41 +08:00
alvkao58
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
import tensorflow as tf
|
|
import tensorflow.contrib.slim as slim
|
|
|
|
from ray.rllib.models.model import Model
|
|
|
|
|
|
class DDPGActor(Model):
|
|
"""Actor network for DDPG."""
|
|
|
|
def _init(self, inputs, num_outputs, options):
|
|
w_normal = tf.truncated_normal_initializer()
|
|
w_init = tf.random_uniform_initializer(minval=-0.003, maxval=0.003)
|
|
ac_bound = options["action_bound"]
|
|
|
|
net = slim.fully_connected(
|
|
inputs, 400, activation_fn=tf.nn.relu,
|
|
weights_initializer=w_normal)
|
|
net = slim.fully_connected(
|
|
net, 300, activation_fn=tf.nn.relu, weights_initializer=w_normal)
|
|
out = slim.fully_connected(
|
|
net, num_outputs, activation_fn=tf.nn.tanh,
|
|
weights_initializer=w_init)
|
|
scaled_out = tf.multiply(out, ac_bound)
|
|
return scaled_out, net
|
|
|
|
|
|
class DDPGCritic(Model):
|
|
"""Critic network for DDPG."""
|
|
|
|
def _init(self, inputs, num_outputs, options):
|
|
obs, action = inputs
|
|
w_normal = tf.truncated_normal_initializer()
|
|
w_init = tf.random_uniform_initializer(minval=-0.0003, maxval=0.0003)
|
|
net = slim.fully_connected(
|
|
obs, 400, activation_fn=tf.nn.relu, weights_initializer=w_normal)
|
|
t1 = slim.fully_connected(
|
|
net, 300, activation_fn=None, biases_initializer=None,
|
|
weights_initializer=w_normal)
|
|
t2 = slim.fully_connected(
|
|
action, 300, activation_fn=None, weights_initializer=w_normal)
|
|
net = tf.nn.relu(tf.add(t1, t2))
|
|
|
|
out = slim.fully_connected(
|
|
net, 1, activation_fn=None, weights_initializer=w_init)
|
|
return out, net
|