from __future__ import division
from __future__ import print_function
import platform
# Internal dependencies.
from absl.testing import absltest
from dm_control import render
from dm_control.mujoco import engine
from dm_control.mujoco.testing import assets
from dm_control.mujoco.testing import decorators
from six.moves import range
MODEL = assets.get_contents('cartpole.xml')
NUM_STEPS = 10
# Context creation with GLFW is not threadsafe.
if render.BACKEND == 'glfw':
# On Linux we are able to create a GLFW window in a single thread that is not
# the main thread.
# On Mac we are only allowed to create windows on the main thread, so we
# disable the `run_threaded` wrapper entirely.
NUM_THREADS = None if platform.system() == 'Darwin' else 1
else:
NUM_THREADS = 4
class ThreadSafetyTest(absltest.TestCase):
@decorators.run_threaded(num_threads=NUM_THREADS)
from dm_control.mujoco import engine
from dm_control.mujoco import wrapper
from dm_control.mujoco.testing import assets
from dm_control.mujoco.wrapper import mjbindings
from dm_control.mujoco.wrapper.mjbindings import enums
from dm_control.rl import control
import mock
import numpy as np
import six
from six.moves import cPickle
from six.moves import range
mjlib = mjbindings.mjlib
MODEL_PATH = assets.get_path('cartpole.xml')
MODEL_WITH_ASSETS = assets.get_contents('model_with_assets.xml')
ASSETS = {
'texture.png': assets.get_contents('deepmind.png'),
'mesh.stl': assets.get_contents('cube.stl'),
'included.xml': assets.get_contents('sphere.xml')
}
class MujocoEngineTest(parameterized.TestCase):
def setUp(self):
super(MujocoEngineTest, self).setUp()
self._physics = engine.Physics.from_xml_path(MODEL_PATH)
def _assert_attributes_equal(self, actual_obj, expected_obj, attr_to_compare):
for name in attr_to_compare:
from absl.testing import absltest
from absl.testing import parameterized
from dm_control import render
from dm_control.mujoco.testing import assets
from dm_control.mujoco.wrapper import core
from dm_control.mujoco.wrapper import mjbindings
from dm_control.mujoco.wrapper.mjbindings import enums
import mock
import numpy as np
from six.moves import cPickle
from six.moves import range
mjlib = mjbindings.mjlib
HUMANOID_XML_PATH = assets.get_path("humanoid.xml")
MODEL_WITH_ASSETS = assets.get_contents("model_with_assets.xml")
ASSETS = {
"texture.png": assets.get_contents("deepmind.png"),
"mesh.stl": assets.get_contents("cube.stl"),
"included.xml": assets.get_contents("sphere.xml")
}
SCALAR_TYPES = (int, float)
ARRAY_TYPES = (np.ndarray, )
OUT_DIR = absltest.get_default_test_tmpdir()
if not os.path.exists(OUT_DIR):
os.makedirs(OUT_DIR) # Ensure that the output directory exists.
class CoreTest(parameterized.TestCase):
from __future__ import print_function
import itertools
# Internal dependencies.
from absl.testing import absltest
from absl.testing import parameterized
from dm_control import mujoco
from dm_control.mujoco.testing import assets
from dm_control.mujoco.wrapper import mjbindings
from dm_control.utils import inverse_kinematics as ik
import numpy as np
mjlib = mjbindings.mjlib
_ARM_XML = assets.get_contents('arm.xml')
_MODEL_WITH_BALL_JOINTS_XML = assets.get_contents('model_with_ball_joints.xml')
_SITE_NAME = 'gripsite'
_JOINTS = ['joint_1', 'joint_2', 'joint_3', 'joint_4', 'joint_5', 'joint_6']
_TOL = 1e-14
_MAX_STEPS = 100
_MAX_RESETS = 10
_TARGETS = [
# target_pos # target_quat
(np.array([0., 0., 0.3]), np.array([0., 1., 0., 1.])),
(np.array([-0.5, 0., 0.5]), None),
(np.array([0., 0., 0.8]), np.array([0., 1., 0., 1.])),
(np.array([0., 0., 0.8]), None),
(np.array([0., -0.1, 0.5]), None),
import os
import itertools
from absl.testing import absltest
from absl.testing import parameterized
from dm_control import mujoco
from dm_control.mujoco.testing import assets
from dm_control.mujoco.wrapper import mjbindings
from dm_control.utils import inverse_kinematics as ik
import numpy as np
import pdb
import random
mjlib = mjbindings.mjlib
FlexivPeg_XML = assets.get_contents(os.path.abspath(os.path.dirname(os.path.dirname(__file__)))+'/assets/graphics/robot_chain.xml')
_SITE_NAME = 'ee_site'
_JOINTS = ['joint1', 'joint2', 'joint3', 'joint4', 'joint5', 'joint6', 'joint7']
_TOL = 1e-14
_MAX_STEPS = 100
_MAX_RESETS = 10
_TARGETS = [
# target_pos # target_quat
(np.array([0., 0., 0.3]), np.array([0., 1., 0., 1.])),
(np.array([-0.5, 0., 0.5]), None),
(np.array([0., 0., 0.8]), np.array([0., 1., 0., 1.])),
(np.array([0., 0., 0.8]), None),
(np.array([0., -0.1, 0.5]), None),
from __future__ import print_function
# Internal dependencies.
from absl.testing import absltest
from absl.testing import parameterized
from dm_control.mujoco import index
from dm_control.mujoco import wrapper
from dm_control.mujoco.testing import assets
from dm_control.mujoco.wrapper.mjbindings import sizes
import numpy as np
import six
MODEL = assets.get_contents('cartpole.xml')
MODEL_NO_NAMES = assets.get_contents('cartpole_no_names.xml')
FIELD_REPR = {
'act': ('FieldIndexer(act):\n'
'(empty)'),
'qM': ('FieldIndexer(qM):\n'
'0 [ 0 ]\n'
'1 [ 1 ]\n'
'2 [ 2 ]'),
'sensordata': ('FieldIndexer(sensordata):\n'
'0 accelerometer [ 0 ]\n'
'1 accelerometer [ 1 ]\n'
'2 accelerometer [ 2 ]\n'
'3 collision [ 3 ]'),
'xpos': ('FieldIndexer(xpos):\n'
from __future__ import print_function
# Internal dependencies.
from absl.testing import absltest
from absl.testing import parameterized
from dm_control.mujoco import index
from dm_control.mujoco import wrapper
from dm_control.mujoco.testing import assets
from dm_control.mujoco.wrapper.mjbindings import sizes
import numpy as np
import six
MODEL = assets.get_contents('cartpole.xml')
MODEL_NO_NAMES = assets.get_contents('cartpole_no_names.xml')
MODEL_3RD_ORDER_ACTUATORS = assets.get_contents(
'model_with_third_order_actuators.xml')
MODEL_INCORRECT_ACTUATOR_ORDER = assets.get_contents(
'model_incorrect_actuator_order.xml')
FIELD_REPR = {
'act': ('FieldIndexer(act):\n'
'(empty)'),
'qM': ('FieldIndexer(qM):\n'
'0 [ 0 ]\n'
'1 [ 1 ]\n'
'2 [ 2 ]'),
'sensordata': ('FieldIndexer(sensordata):\n'
'0 accelerometer [ 0 ]\n'
def _load_pixels(path): image_bytes = assets.get_contents(path) image = Image.open(io.BytesIO(image_bytes)) return np.array(image)
"""Returns an iterator over paths to the reference images."""
for frame_num in range(self._num_frames):
filename = self._FILENAME_TEMPLATE.format(frame_num=frame_num)
for camera_spec in self._camera_specs:
subdir_name = _get_subdir(
name=self._name,
seed=self._seed,
backend_string=BACKEND_STRING,
camera_spec=camera_spec)
directory = os.path.join(self._FRAMES_DIR, subdir_name)
yield directory, filename
cartpole = _FrameSequence(
name='cartpole',
xml_string=assets.get_contents('cartpole.xml'),
camera_specs=(
_CameraSpec(
width=320, height=240, camera_id=0, render_flag_overrides={}),
),
steps_per_frame=5)
humanoid = _FrameSequence(
name='humanoid',
xml_string=assets.get_contents('humanoid.xml'),
camera_specs=(
_CameraSpec(
width=240, height=320, camera_id=0, render_flag_overrides={}),
_CameraSpec(
width=240,
height=320,
path = os.path.join(full_directory_path, filename)
_save_pixels(pixels, path)
def _iter_paths(self):
subdir_name = self._SUBDIR_TEMPLATE.format(name=self._name,
camera_id=self._camera_id,
width=self._width,
height=self._height,
seed=self._seed)
directory = os.path.join(self._FRAMES_DIR, subdir_name)
for frame_num in xrange(self._num_frames):
filename = self._FILENAME_TEMPLATE.format(frame_num=frame_num)
yield directory, filename
cartpole = _FrameSequence('cartpole', assets.get_contents('cartpole.xml'),
width=320, height=240, camera_id=0,
steps_per_frame=5)
humanoid = _FrameSequence('humanoid', assets.get_contents('humanoid.xml'),
width=128, height=128, camera_id=-1)
SEQUENCES = {
'cartpole': cartpole,
'humanoid': humanoid,
}
def _save_pixels(pixels, path):
image = Image.fromarray(pixels)
