fixes in PyBullet deep_mimic to allow running in pip version

This commit is contained in:
Erwin Coumans 2019-02-11 08:51:07 -08:00
parent 12e6478689
commit 1bd201eb43
13 changed files with 56 additions and 28 deletions

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@ -12,4 +12,16 @@ cd pybullet
if [ -e pybullet.dylib ]; then
ln -f -s pybullet.dylib pybullet.so
fi
if [ -e pybullet_envs ]; then
rm pybullet_envs
fi
if [ -e pybullet_data ]; then
rm pybullet_data
fi
if [ -e pybullet_utils ]; then
rm pybullet_utils
fi
ln -s ../../../examples/pybullet/gym/pybullet_envs .
ln -s ../../../examples/pybullet/gym/pybullet_data .
ln -s ../../../examples/pybullet/gym/pybullet_utils .
echo "Completed build of Bullet."

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@ -13,8 +13,24 @@ IF(BUILD_PYBULLET_NUMPY)
)
ENDIF()
ADD_DEFINITIONS(-DSTATIC_LINK_SPD_PLUGIN)
SET(pybullet_SRCS
pybullet.c
../../examples/SharedMemory/plugins/stablePDPlugin/SpAlg.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/SpAlg.h
../../examples/SharedMemory/plugins/stablePDPlugin/Shape.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/Shape.h
../../examples/SharedMemory/plugins/stablePDPlugin/RBDUtil.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/RBDUtil.h
../../examples/SharedMemory/plugins/stablePDPlugin/RBDModel.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/RBDModel.h
../../examples/SharedMemory/plugins/stablePDPlugin/MathUtil.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/MathUtil.h
../../examples/SharedMemory/plugins/stablePDPlugin/KinTree.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/KinTree.h
../../examples/SharedMemory/plugins/stablePDPlugin/BulletConversion.cpp
../../examples/SharedMemory/plugins/stablePDPlugin/BulletConversion.h
../../examples/SharedMemory/plugins/collisionFilterPlugin/collisionFilterPlugin.cpp
../../examples/SharedMemory/plugins/pdControlPlugin/pdControlPlugin.cpp
../../examples/SharedMemory/plugins/pdControlPlugin/pdControlPlugin.h

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@ -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"

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@ -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"

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@ -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

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@ -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

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@ -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

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@ -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

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@ -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

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@ -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

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@ -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'

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@ -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):

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@ -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