fixes in PyBullet deep_mimic to allow running in pip version

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/agent_builder.py

@@ -1,6 +1,6 @@
 import json
 import numpy as np
-from learning.ppo_agent import PPOAgent
+from pybullet_envs.deep_mimic.learning.ppo_agent import PPOAgent
 import pybullet_data
 
 AGENT_TYPE_KEY = "AgentType"

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/nets/fc_2layers_1024units.py

@@ -1,5 +1,5 @@
 import tensorflow as tf
-import learning.tf_util as TFUtil
+import pybullet_envs.deep_mimic.learning.tf_util as TFUtil
 
 NAME = "fc_2layers_1024units"
 

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/nets/net_builder.py

@@ -1,4 +1,4 @@
-import learning.nets.fc_2layers_1024units as fc_2layers_1024units
+import pybullet_envs.deep_mimic.learning.nets.fc_2layers_1024units as fc_2layers_1024units
 
 def build_net(net_name, input_tfs, reuse=False):
     net = None

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/pg_agent.py

@@ -2,12 +2,12 @@ import numpy as np
 import tensorflow as tf
 import copy
 
-from learning.tf_agent import TFAgent
-from learning.solvers.mpi_solver import MPISolver
-import learning.tf_util as TFUtil
-import learning.nets.net_builder as NetBuilder
-from learning.tf_normalizer import TFNormalizer
-import learning.rl_util as RLUtil
+from pybullet_envs.deep_mimic.learning.tf_agent import TFAgent
+from pybullet_envs.deep_mimic.learning.solvers.mpi_solver import MPISolver
+import pybullet_envs.deep_mimic.learning.tf_util as TFUtil
+import pybullet_envs.deep_mimic.learning.nets.net_builder as NetBuilder
+from pybullet_envs.deep_mimic.learning.tf_normalizer import TFNormalizer
+import pybullet_envs.deep_mimic.learning.rl_util as RLUtil
 from pybullet_utils.logger import Logger
 import pybullet_utils.mpi_util as MPIUtil
 import pybullet_utils.math_util as MathUtil
@@ -350,4 +350,4 @@ class PGAgent(TFAgent):
     def _build_replay_buffer(self, buffer_size):
         super()._build_replay_buffer(buffer_size)
         self.replay_buffer.add_filter_key(self.EXP_ACTION_FLAG)
-        return
+        return

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/ppo_agent.py

@@ -2,10 +2,10 @@ import numpy as np
 import copy as copy
 import tensorflow as tf
 
-from learning.pg_agent import PGAgent
-from learning.solvers.mpi_solver import MPISolver
-import learning.tf_util as TFUtil
-import learning.rl_util as RLUtil
+from pybullet_envs.deep_mimic.learning.pg_agent import PGAgent
+from pybullet_envs.deep_mimic.learning.solvers.mpi_solver import MPISolver
+import pybullet_envs.deep_mimic.learning.tf_util as TFUtil
+import pybullet_envs.deep_mimic.learning.rl_util as RLUtil
 from pybullet_utils.logger import Logger
 import pybullet_utils.mpi_util as MPIUtil
 import pybullet_utils.math_util as MathUtil
@@ -365,4 +365,4 @@ class PPOAgent(PGAgent):
             self._actor_stepsize_ph: stepsize,
         }
         self.sess.run(self._actor_stepsize_update_op, feed)
-        return
+        return

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/rl_agent.py

@@ -6,10 +6,10 @@ import time
 from abc import ABC, abstractmethod
 from enum import Enum
 
-from learning.path import *
-from learning.exp_params import ExpParams
-from learning.normalizer import Normalizer
-from learning.replay_buffer import ReplayBuffer
+from pybullet_envs.deep_mimic.learning.path import *
+from pybullet_envs.deep_mimic.learning.exp_params import ExpParams
+from pybullet_envs.deep_mimic.learning.normalizer import Normalizer
+from pybullet_envs.deep_mimic.learning.replay_buffer import ReplayBuffer
 from pybullet_utils.logger import Logger
 import pybullet_utils.mpi_util as MPIUtil
 import pybullet_utils.math_util as MathUtil

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/rl_world.py

@@ -1,7 +1,7 @@
 import numpy as np
-import learning.agent_builder as AgentBuilder
-import learning.tf_util as TFUtil
-from learning.rl_agent import RLAgent
+import pybullet_envs.deep_mimic.learning.agent_builder as AgentBuilder
+import pybullet_envs.deep_mimic.learning.tf_util as TFUtil
+from pybullet_envs.deep_mimic.learning.rl_agent import RLAgent
 from pybullet_utils.logger import Logger
 import pybullet_data
 

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/solvers/mpi_solver.py

@@ -1,12 +1,12 @@
 from mpi4py import MPI
 import tensorflow as tf
 import numpy as np
-import learning.tf_util as TFUtil
+import pybullet_envs.deep_mimic.learning.tf_util as TFUtil
 import pybullet_utils.math_util as MathUtil
 import pybullet_utils.mpi_util as MPIUtil
 from pybullet_utils.logger import Logger
 
-from learning.solvers.solver import Solver
+from pybullet_envs.deep_mimic.learning.solvers.solver import Solver
 
 class MPISolver(Solver):
     CHECK_SYNC_ITERS = 1000

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/tf_agent.py

@@ -2,9 +2,9 @@ import numpy as np
 import tensorflow as tf
 from abc import abstractmethod
 
-from learning.rl_agent import RLAgent
+from pybullet_envs.deep_mimic.learning.rl_agent import RLAgent
 from pybullet_utils.logger import Logger
-from learning.tf_normalizer import TFNormalizer
+from pybullet_envs.deep_mimic.learning.tf_normalizer import TFNormalizer
 
 class TFAgent(RLAgent):
     RESOURCE_SCOPE = 'resource'

examples/pybullet/gym/pybullet_envs/deep_mimic/learning/tf_normalizer.py

@@ -1,7 +1,7 @@
 import numpy as np
 import copy
 import tensorflow as tf
-from learning.normalizer import Normalizer
+from pybullet_envs.deep_mimic.learning.normalizer import Normalizer
 
 class TFNormalizer(Normalizer):
 

examples/pybullet/gym/pybullet_envs/deep_mimic/testrl.py

@@ -6,7 +6,7 @@ os.sys.path.insert(0,parentdir)
 print("parentdir=",parentdir)
 import json
 from pybullet_envs.deep_mimic.learning.rl_world import RLWorld
-from learning.ppo_agent import PPOAgent
+from pybullet_envs.deep_mimic.learning.ppo_agent import PPOAgent
 
 import pybullet_data
 from pybullet_utils.arg_parser import ArgParser