add ARS to train/eval Minitaur

examples/pybullet/gym/pybullet_envs/ARS/config_ars.py

@@ -0,0 +1,83 @@
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import functools
+from pybullet_envs.minitaur.envs import minitaur_gym_env
+from pybullet_envs.minitaur.envs import minitaur_reactive_env
+from pybullet_envs.minitaur.envs.env_randomizers import minitaur_env_randomizer
+from pybullet_envs.minitaur.envs.env_randomizers import minitaur_env_randomizer_from_config as randomizer_config_lib
+
+MAX_LENGTH = 1000
+
+
+def merge_two_dicts(x, y):
+  """Given two dicts, merge them into a new dict as a shallow copy."""
+  z = dict(x)
+  z.update(y)
+  return z
+
+
+# The default configurations.
+DEFAULT_CONFIG = dict(
+    num_workers=8,
+    num_directions=8,
+    num_iterations=1000,
+    deltas_used=8,
+    step_size=0.02,
+    delta_std=0.03,
+    rollout_length=MAX_LENGTH,
+    shift=0,
+    seed=237,
+    policy_type="linear",
+    filter="MeanStdFilter",
+)
+
+# Configuration specific to minitaur_gym_env.MinitaurGymEnv class.
+MINITAUR_GYM_CONFIG_ADDITIONS = dict(
+    env=functools.partial(
+        minitaur_gym_env.MinitaurGymEnv,
+        urdf_version=minitaur_gym_env.DERPY_V0_URDF_VERSION,
+        accurate_motor_model_enabled=True,
+        motor_overheat_protection=True,
+        pd_control_enabled=True,
+        env_randomizer=None,#minitaur_env_randomizer.MinitaurEnvRandomizer(),
+        render=False,
+        num_steps_to_log=MAX_LENGTH))
+MINITAUR_GYM_CONFIG = merge_two_dicts(DEFAULT_CONFIG,
+                                      MINITAUR_GYM_CONFIG_ADDITIONS)
+
+# Configuration specific to MinitaurReactiveEnv class.
+MINITAUR_REACTIVE_CONFIG_ADDITIONS = dict(
+    env=functools.partial(
+        minitaur_reactive_env.MinitaurReactiveEnv,
+        urdf_version=minitaur_gym_env.RAINBOW_DASH_V0_URDF_VERSION,
+        energy_weight=0.005,
+        accurate_motor_model_enabled=True,
+        pd_latency=0.003,
+        control_latency=0.02,
+        motor_kd=0.015,
+        remove_default_joint_damping=True,
+        env_randomizer=None,
+        render=False,
+        num_steps_to_log=MAX_LENGTH))
+MINITAUR_REACTIVE_CONFIG = merge_two_dicts(DEFAULT_CONFIG,
+                                           MINITAUR_REACTIVE_CONFIG_ADDITIONS)
+
+# Configuration specific to MinitaurReactiveEnv class with randomizer.
+MINITAUR_REACTIVE_RANDOMIZER_CONFIG_ADDITIONS = dict(
+    env=functools.partial(
+        minitaur_reactive_env.MinitaurReactiveEnv,
+        urdf_version=minitaur_gym_env.RAINBOW_DASH_V0_URDF_VERSION,
+        energy_weight=0.005,
+        accurate_motor_model_enabled=True,
+        pd_latency=0.003,
+        control_latency=0.02,
+        motor_kd=0.015,
+        remove_default_joint_damping=True,
+        env_randomizer=randomizer_config_lib.MinitaurEnvRandomizerFromConfig(),
+        render=False,
+        num_steps_to_log=MAX_LENGTH))
+MINITAUR_REACTIVE_RANDOMIZER_CONFIG = merge_two_dicts(
+    DEFAULT_CONFIG, MINITAUR_REACTIVE_RANDOMIZER_CONFIG_ADDITIONS)