remove sonnet dependency

examples/pybullet/gym/agents/actor_net.py

@@ -1,21 +0,0 @@
-"""An actor network."""
-import tensorflow as tf
-import sonnet as snt
-
-class ActorNetwork(snt.AbstractModule):
-  """An actor network as a sonnet Module."""
-
-  def __init__(self, layer_sizes, action_size, name='target_actor'):
-    super(ActorNetwork, self).__init__(name=name)
-    self._layer_sizes = layer_sizes
-    self._action_size = action_size
-
-  def _build(self, inputs):
-    state = inputs
-    for output_size in self._layer_sizes:
-      state = snt.Linear(output_size)(state)
-      state = tf.nn.relu(state)
-
-    action = tf.tanh(
-        snt.Linear(self._action_size, name='action')(state))
-    return action

examples/pybullet/gym/agents/simpleAgent.py

@@ -1,46 +0,0 @@
-"""Loads a DDPG agent without too much external dependencies
-"""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import os
-import collections
-import numpy as np
-import tensorflow as tf
-
-import sonnet as snt
-from agents import actor_net
-
-class SimpleAgent():
-  def __init__(
-      self,
-      session,
-      ckpt_path,
-      actor_layer_size,
-      observation_size=(31,),
-      action_size=8,
-  ):
-    self._ckpt_path = ckpt_path
-    self._actor_layer_size = actor_layer_size
-    self._observation_size = observation_size
-    self._action_size = action_size
-    self._session = session
-    self._build()
-
-  def _build(self):
-    self._agent_net = actor_net.ActorNetwork(self._actor_layer_size, self._action_size)
-    self._obs = tf.placeholder(tf.float32, (31,))
-    with tf.name_scope('Act'):
-      batch_obs = snt.nest.pack_iterable_as(self._obs,
-                                            snt.nest.map(lambda x: tf.expand_dims(x, 0),
-                                                         snt.nest.flatten_iterable(self._obs)))
-      self._action = self._agent_net(batch_obs)
-      saver = tf.train.Saver()
-      saver.restore(
-          sess=self._session,
-          save_path=self._ckpt_path)
-
-  def __call__(self, observation):
-    out_action = self._session.run(self._action, feed_dict={self._obs: observation})
-    return out_action[0]

examples/pybullet/gym/agents/simplerAgent.py

@@ -0,0 +1,36 @@
+"""Loads a DDPG agent without too much external dependencies
+"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+import collections
+import numpy as np
+import tensorflow as tf
+import pdb
+
+class SimplerAgent():
+  def __init__(
+      self,
+      session,
+      ckpt_path,
+      observation_dim=31
+  ):
+    self._ckpt_path = ckpt_path
+    self._session = session
+    self._observation_dim = observation_dim
+    self._build()
+
+  def _build(self):
+    saver = tf.train.import_meta_graph(self._ckpt_path + '.meta')
+    saver.restore(
+        sess=self._session,
+        save_path=self._ckpt_path)
+    self._action = tf.get_collection('action_op')[0]
+    self._obs = tf.get_collection('observation_placeholder')[0]
+
+  def __call__(self, observation):
+    feed_dict={self._obs: observation}
+    out_action = self._session.run(self._action, feed_dict=feed_dict)
+    return out_action[0]

examples/pybullet/gym/data/agent/tf_graph_data/checkpoint

@@ -1,2 +1,2 @@
-model_checkpoint_path: "/cns/ij-d/home/jietan/persistent/minitaur/minitaur_vizier_3_153645653/Bullet/MinitaurSimEnv/28158/0003600000/agent/tf_graph_data/tf_graph_data.ckpt"
-all_model_checkpoint_paths: "/cns/ij-d/home/jietan/persistent/minitaur/minitaur_vizier_3_153645653/Bullet/MinitaurSimEnv/28158/0003600000/agent/tf_graph_data/tf_graph_data.ckpt"
+model_checkpoint_path: "tf_graph_data_converted.ckpt-0"
+all_model_checkpoint_paths: "tf_graph_data_converted.ckpt-0"

examples/pybullet/gym/minitaurGymEnvTest.py

@@ -10,7 +10,7 @@ import numpy as np
 import tensorflow as tf
 
 from envs.bullet.minitaurGymEnv import MinitaurGymEnv
-from agents import simpleAgent
+from agents import simplerAgent
 
 def testSinePolicy():
   """Tests sine policy
@@ -53,17 +53,14 @@ def testDDPGPolicy():
   environment = MinitaurGymEnv(render=True)
   sum_reward = 0
   steps = 1000
-  ckpt_path = 'data/agent/tf_graph_data/tf_graph_data.ckpt'
+  ckpt_path = 'data/agent/tf_graph_data/tf_graph_data_converted.ckpt-0'
   observation_shape = (31,)
   action_size = 8
   actor_layer_sizes = (100, 181)
   n_steps = 0
   tf.reset_default_graph()
   with tf.Session() as session:
-    agent = simpleAgent.SimpleAgent(session, ckpt_path,
-                                    actor_layer_sizes,
-                                    observation_size=observation_shape,
-                                    action_size=action_size)
+    agent = simplerAgent.SimplerAgent(session, ckpt_path)
     state = environment.reset()
     action = agent(state)
     for _ in range(steps):