From 0d15ab68bbadee7218782d870d4ca7284d82248c Mon Sep 17 00:00:00 2001 From: Vittorio Caggiano Date: Mon, 4 Dec 2023 03:57:59 -0500 Subject: [PATCH 01/62] gymnasium compatibility --- myosuite/envs/env_base.py | 52 +++-- myosuite/envs/env_variants.py | 75 ++++++- myosuite/envs/myo/base_v0.py | 15 +- myosuite/envs/myo/myobase/__init__.py | 48 +++- myosuite/envs/myo/myobase/key_turn_v0.py | 2 +- myosuite/envs/myo/myobase/obj_hold_v0.py | 2 +- myosuite/envs/myo/myobase/pen_v0.py | 2 +- myosuite/envs/myo/myobase/pose_v0.py | 2 +- myosuite/envs/myo/myobase/reach_v0.py | 2 +- myosuite/envs/myo/myobase/reorient_sar_v0.py | 2 +- myosuite/envs/myo/myobase/walk_v0.py | 3 +- myosuite/envs/myo/myochallenge/__init__.py | 5 +- myosuite/envs/myo/myochallenge/baoding_v1.py | 2 +- myosuite/envs/myo/myochallenge/chasetag_v0.py | 92 ++------ myosuite/envs/myo/myochallenge/relocate_v0.py | 4 +- myosuite/envs/myo/myochallenge/reorient_v0.py | 2 +- myosuite/envs/myo/myodm/__init__.py | 3 +- myosuite/envs/myo/myodm/myodm_v0.py | 4 +- myosuite/logger/examine_logs.py | 26 +-- myosuite/logger/examine_reference.py | 2 +- myosuite/logger/grouped_datasets.py | 8 +- myosuite/logger/roboset_logger.py | 4 +- myosuite/physics/mj_sim_scene.py | 2 +- myosuite/physics/mjpy_sim_scene.py | 2 +- myosuite/physics/sim_scene.py | 2 +- myosuite/physics/sim_scene_test.py | 2 +- myosuite/robot/robot.py | 4 +- myosuite/utils/curriculum_utils.py | 38 ++++ myosuite/utils/examine_env.py | 4 +- myosuite/utils/implement_for.py | 211 ++++++++++++++++++ myosuite/utils/import_utils.py | 66 ++++++ myosuite/utils/paths_utils.py | 2 +- 32 files changed, 525 insertions(+), 165 deletions(-) create mode 100644 myosuite/utils/curriculum_utils.py create mode 100644 myosuite/utils/implement_for.py diff --git a/myosuite/envs/env_base.py b/myosuite/envs/env_base.py index f5464ebc..733423c7 100644 --- a/myosuite/envs/env_base.py +++ b/myosuite/envs/env_base.py @@ -1,11 +1,13 @@ """ ================================================= Copyright (C) 2018 Vikash Kumar Author :: Vikash Kumar (vikashplus@gmail.com) -Source :: https://github.com/vikashplus/robohive +Source :: https://github.com/vikashplus/myosuite License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -import gym +# TODO: find how to make this compatible with gymnasium. Maybe a global variable that indicates what to use as backend? +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils.import_utils import import_gym; gym = import_gym() import numpy as np import os import time as timer @@ -13,6 +15,7 @@ from myosuite.envs.obs_vec_dict import ObsVecDict from myosuite.utils import tensor_utils from myosuite.robot.robot import Robot +from myosuite.utils.implement_for import implement_for from myosuite.utils.prompt_utils import prompt, Prompt import skvideo.io from sys import platform @@ -31,8 +34,8 @@ class MujocoEnv(gym.Env, gym.utils.EzPickle, ObsVecDict): """ DEFAULT_CREDIT = """\ - RoboHive: A unified framework for robot learning | https://sites.google.com/view/robohive - Code: https://github.com/vikashplus/robohive/stargazers (add a star to support the project) + MyoSuite: a collection of environments/tasks to be solved by musculoskeletal models | https://sites.google.com/view/myosuite + Code: https://github.com/MyoHub/myosuite/stargazers (add a star to support the project) """ def __init__(self, model_path, obsd_model_path=None, seed=None, env_credits=DEFAULT_CREDIT): @@ -130,7 +133,7 @@ def _setup(self, self._setup_rgb_encoders(self.visual_keys, device=None) # reset to get the env ready - observation, _reward, done, _info = self.step(np.zeros(self.sim.model.nu)) + observation, _reward, done, *_, _info = self.step(np.zeros(self.sim.model.nu)) # Question: Should we replace above with following? Its specially helpful for hardware as it forces a env reset before continuing, without which the hardware will make a big jump from its position to the position asked by step. # observation = self.reset() assert not done, "Check initialization. Simulation starts in a done state." @@ -263,8 +266,23 @@ def step(self, a, **kwargs): render_cbk=self.mj_render if self.mujoco_render_frames else None) return self.forward(**kwargs) + @implement_for("gym", None, "0.24") + def forward(self, **kwargs): + return self._forward(**kwargs) + + @implement_for("gym", "0.24", None) + def forward(self, **kwargs): + obs, reward, done, info = self._forward(**kwargs) + terminal = done + return obs, reward, terminal, False, info + @implement_for("gymnasium") def forward(self, **kwargs): + obs, reward, done, info = self._forward(**kwargs) + terminal = done + return obs, reward, terminal, False, info + + def _forward(self, **kwargs): """ Forward propagate env to recover env details Returns current obs(t), rwd(t), done(t), info(t) @@ -476,7 +494,7 @@ def get_input_seed(self): return self.input_seed - def reset(self, reset_qpos=None, reset_qvel=None, **kwargs): + def _reset(self, reset_qpos=None, reset_qvel=None, **kwargs): """ Reset the environment Default implemention provided. Override if env needs custom reset @@ -485,11 +503,19 @@ def reset(self, reset_qpos=None, reset_qvel=None, **kwargs): qvel = self.init_qvel.copy() if reset_qvel is None else reset_qvel self.robot.reset(qpos, qvel, **kwargs) return self.get_obs() + @implement_for("gym", None, "0.26") + def reset(self, reset_qpos=None, reset_qvel=None, **kwargs): + return self._reset(reset_qpos=reset_qpos, reset_qvel=reset_qvel, **kwargs) + @implement_for("gym", "0.26", None) + def reset(self, reset_qpos=None, reset_qvel=None, **kwargs): + return self._reset(reset_qpos=reset_qpos, reset_qvel=reset_qvel, **kwargs), {} + @implement_for("gymnasium") + def reset(self, reset_qpos=None, reset_qvel=None, **kwargs): + return self._reset(reset_qpos=reset_qpos, reset_qvel=reset_qvel, **kwargs), {} - - @property - def _step(self, a): - return self.step(a) + # @property + # def _step(self, a): + # return self.step(a) @property @@ -702,7 +728,7 @@ def examine_policy(self, ep_rwd = 0.0 while t < horizon and done is False: a = policy.get_action(o)[0] if mode == 'exploration' else policy.get_action(o)[1]['evaluation'] - next_o, rwd, done, env_info = self.step(a) + next_o, rwd, done, *_, env_info = self.step(a) ep_rwd += rwd # render offscreen visuals if render =='offscreen': @@ -794,7 +820,7 @@ def examine_policy_new(self, ep_rwd = 0.0 # Rollout -------------------------------- - obs, rwd, done, env_info = self.forward(update_exteroception=True) # t=0 + obs, rwd, done, *_, env_info = self.forward(update_exteroception=True) # t=0 while t < horizon and done is False: # print(t, t*self.dt, self.time, t*self.dt-self.time) @@ -825,7 +851,7 @@ def examine_policy_new(self, # step env using actions from t=>t+1 ---------------------- - obs, rwd, done, env_info = self.step(act, update_exteroception=True) + obs, rwd, done, *_, env_info = self.step(act, update_exteroception=True) t = t+1 ep_rwd += rwd diff --git a/myosuite/envs/env_variants.py b/myosuite/envs/env_variants.py index 07bb3374..b2b4450d 100644 --- a/myosuite/envs/env_variants.py +++ b/myosuite/envs/env_variants.py @@ -5,12 +5,65 @@ License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -import gym -from gym.envs.registration import register +from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register import collections from copy import deepcopy from flatten_dict import flatten, unflatten +from myosuite.utils.implement_for import implement_for + +#TODO: check versions +@implement_for("gym", None, "0.24") +def gym_registry_specs(): + return gym.envs.registry.env_specs + +@implement_for("gym", "0.24", None) +def gym_registry_specs(): + return gym.envs.registry + +@implement_for("gymnasium") +def gym_registry_specs(): + return gym.envs.registry + +# TODO: move to within the function? +@implement_for("gym", None, "0.24") +def _update_env_spec_kwarg(env_variant_specs, variants, override_keys): + env_variant_specs._kwargs, variants_update_keyval_str = update_dict(env_variant_specs._kwargs, variants, override_keys=override_keys) + return variants_update_keyval_str + +@implement_for("gym", "0.24", None) +def _update_env_spec_kwarg(env_variant_specs, variants, override_keys): + env_variant_specs.kwargs, variants_update_keyval_str = update_dict(env_variant_specs.kwargs, variants, override_keys=override_keys) + return variants_update_keyval_str + +@implement_for("gymnasium") +def _update_env_spec_kwarg(env_variant_specs, variants, override_keys): + env_variant_specs.kwargs, variants_update_keyval_str = update_dict(env_variant_specs.kwargs, variants, override_keys=override_keys) + return variants_update_keyval_str + +@implement_for("gym", None, "0.24") +def _entry_point(env_variant_specs): + return env_variant_specs._entry_point + +@implement_for("gym", "0.24", None) +def _entry_point(env_variant_specs): + return env_variant_specs.entry_point + +@implement_for("gymnasium") +def _entry_point(env_variant_specs): + return env_variant_specs.entry_point + +@implement_for("gym", None, "0.24") +def _kwargs(env_variant_specs): + return env_variant_specs._kwargs + +@implement_for("gym", "0.24", None) +def _kwargs(env_variant_specs): + return env_variant_specs.kwargs + +@implement_for("gymnasium") +def _kwargs(env_variant_specs): + return env_variant_specs.kwargs # Update base_dict using update_dict def update_dict(base_dict:dict, update_dict:dict, override_keys:list=None): @@ -47,10 +100,10 @@ def register_env_variant(env_id:str, variants:dict, variant_id=None, silent=Fals """ # check if the base env is registered - assert env_id in gym.envs.registry.env_specs.keys(), "ERROR: {} not found in env registry".format(env_id) + assert env_id in gym_registry_specs().keys(), "ERROR: {} not found in env registry".format(env_id) # recover the specs of the existing env - env_variant_specs = deepcopy(gym.envs.registry.env_specs[env_id]) + env_variant_specs = deepcopy(gym_registry_specs()[env_id]) env_variant_id = env_variant_specs.id[:-3] # update horizon if requested @@ -60,16 +113,16 @@ def register_env_variant(env_id:str, variants:dict, variant_id=None, silent=Fals del variants['max_episode_steps'] # merge specs._kwargs with variants - env_variant_specs._kwargs, variants_update_keyval_str = update_dict(env_variant_specs._kwargs, variants, override_keys=override_keys) + variants_update_keyval_str = _update_env_spec_kwarg(env_variant_specs, variants, override_keys) env_variant_id += variants_update_keyval_str # finalize name and register env env_variant_specs.id = env_variant_id+env_variant_specs.id[-3:] if variant_id is None else variant_id register( id=env_variant_specs.id, - entry_point=env_variant_specs._entry_point, + entry_point=_entry_point(env_variant_specs), max_episode_steps=env_variant_specs.max_episode_steps, - kwargs=env_variant_specs._kwargs + kwargs=_kwargs(env_variant_specs) ) if not silent: print("Registered a new env-variant:", env_variant_specs.id) @@ -78,7 +131,7 @@ def register_env_variant(env_id:str, variants:dict, variant_id=None, silent=Fals # Example usage if __name__ == '__main__': - import robohive + import myosuite import pprint # Register a variant @@ -96,11 +149,11 @@ def register_env_variant(env_id:str, variants:dict, variant_id=None, silent=Fals # Test variant print("Base-env kwargs: ") - pprint.pprint(gym.envs.registry.env_specs[base_env_name]._kwargs) + pprint.pprint(gym_registry_specs()[base_env_name]._kwargs) print("Env-variant kwargs: ") - pprint.pprint(gym.envs.registry.env_specs[variant_env_name]._kwargs) + pprint.pprint(gym_registry_specs()[variant_env_name]._kwargs) print("Env-variant (with override) kwargs: ") - pprint.pprint(gym.envs.registry.env_specs[variant_overide_env_name]._kwargs) + pprint.pprint(gym_registry_specs()[variant_overide_env_name]._kwargs) # Test one of the newly minted env env = gym.make(variant_env_name) diff --git a/myosuite/envs/myo/base_v0.py b/myosuite/envs/myo/base_v0.py index a43da888..21e27c2f 100644 --- a/myosuite/envs/myo/base_v0.py +++ b/myosuite/envs/myo/base_v0.py @@ -116,17 +116,4 @@ def step(self, a, **kwargs): realTimeSim=self.mujoco_render_frames, render_cbk=self.mj_render if self.mujoco_render_frames else None) - # observation - obs = self.get_obs(**kwargs) - - # rewards - self.expand_dims(self.obs_dict) # required for vectorized rewards calculations - self.rwd_dict = self.get_reward_dict(self.obs_dict) - self.squeeze_dims(self.rwd_dict) - self.squeeze_dims(self.obs_dict) - - # finalize step - env_info = self.get_env_infos() - - # returns obs(t+1), rwd(t+1), done(t+1), info(t+1) - return obs, env_info['rwd_'+self.rwd_mode], bool(env_info['done']), env_info + return self.forward(**kwargs) \ No newline at end of file diff --git a/myosuite/envs/myo/myobase/__init__.py b/myosuite/envs/myo/myobase/__init__.py index 13d70ef9..00c2d0b0 100644 --- a/myosuite/envs/myo/myobase/__init__.py +++ b/myosuite/envs/myo/myobase/__init__.py @@ -3,7 +3,8 @@ Authors :: Vikash Kumar (vikashplus@gmail.com), Vittorio Caggiano (caggiano@gmail.com) ================================================= """ -from gym.envs.registration import register +from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register + from myosuite.envs.env_variants import register_env_variant import os @@ -291,14 +292,14 @@ def register_env_with_variants(id, entry_point, max_episode_steps, kwargs): leg_model='/../../../simhive/myo_sim/leg/myolegs_v0.54(mj210).mjb' elif sim_backend == SimBackend.MUJOCO: leg_model='/../../../simhive/myo_sim/leg/myolegs_v0.56(mj237).mjb' - + register_env_with_variants(id='myoLegStandRandom-v0', entry_point='myosuite.envs.myo.myobase.walk_v0:ReachEnvV0', max_episode_steps=150, kwargs={ 'model_path': curr_dir+leg_model, - 'joint_random_range': (0.2, -0.2), #range of joint randomization (jnt = init_qpos + random(range) + 'joint_random_range': (-.2, 0.2), #range of joint randomization (jnt = init_qpos + random(range) 'target_reach_range': { 'pelvis': ((-.05, -.05, 0), (0.05, 0.05, 0)), }, @@ -307,6 +308,7 @@ def register_env_with_variants(id, entry_point, max_episode_steps, kwargs): } ) + # Gait Torso Walking ============================== register_env_with_variants(id='myoLegWalk-v0', entry_point='myosuite.envs.myo.myobase.walk_v0:WalkEnvV0', @@ -377,7 +379,7 @@ def register_env_with_variants(id, entry_point, max_episode_steps, kwargs): 'target_y_vel':1.2, # desired y velocity in m/s 'target_rot': None, # if None then the initial root pos will be taken, otherwise provide quat 'terrain':'stairs', - 'variant':'fixed', + 'variant':'fixed' } ) @@ -417,7 +419,6 @@ def register_env_with_variants(id, entry_point, max_episode_steps, kwargs): } ) - # Hand-Joint key turn ============================== register_env_with_variants(id='myoHandKeyTurnFixed-v0', entry_point='myosuite.envs.myo.myobase.key_turn_v0:KeyTurnEnvV0', @@ -520,3 +521,40 @@ def register_env_with_variants(id, entry_point, max_episode_steps, kwargs): 'frame_skip': 5, } ) + + +# Baoding ============================== +register_env_with_variants(id='myoHandBaodingFixed-v1', + entry_point='myosuite.envs.myo.myobase.baoding_v1:BaodingEnvV1', + max_episode_steps=200, + kwargs={ + 'model_path': curr_dir+'/../assets/hand/myohand_baoding.xml', + 'normalize_act': True, + } + ) +register_env_with_variants(id='myoHandBaodingRandom-v1', + entry_point='myosuite.envs.myo.myobase.baoding_v1:BaodingEnvV1', + max_episode_steps=200, + kwargs={ + 'model_path': curr_dir+'/../assets/hand/myohand_baoding.xml', + 'normalize_act': True, + } + ) +register_env_with_variants(id='myoHandBaodingFixed4th-v1', + entry_point='myosuite.envs.myo.myobase.baoding_v1:BaodingEnvV1', + max_episode_steps=200, + kwargs={ + 'model_path': curr_dir+'/../assets/hand/myohand_baoding.xml', + 'normalize_act': True, + 'n_shifts_per_period':4, + } + ) +register_env_with_variants(id='myoHandBaodingFixed8th-v1', + entry_point='myosuite.envs.myo.myobase.baoding_v1:BaodingEnvV1', + max_episode_steps=200, + kwargs={ + 'model_path': curr_dir+'/../assets/hand/myohand_baoding.xml', + 'normalize_act': True, + 'n_shifts_per_period':8, + } + ) diff --git a/myosuite/envs/myo/myobase/key_turn_v0.py b/myosuite/envs/myo/myobase/key_turn_v0.py index 6a8cdbc1..c22bd9f5 100644 --- a/myosuite/envs/myo/myobase/key_turn_v0.py +++ b/myosuite/envs/myo/myobase/key_turn_v0.py @@ -5,7 +5,7 @@ import collections import numpy as np -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/obj_hold_v0.py b/myosuite/envs/myo/myobase/obj_hold_v0.py index e61ffb3b..1a2b938c 100644 --- a/myosuite/envs/myo/myobase/obj_hold_v0.py +++ b/myosuite/envs/myo/myobase/obj_hold_v0.py @@ -5,7 +5,7 @@ import collections import numpy as np -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/pen_v0.py b/myosuite/envs/myo/myobase/pen_v0.py index b6ae7cd5..e3f727ef 100644 --- a/myosuite/envs/myo/myobase/pen_v0.py +++ b/myosuite/envs/myo/myobase/pen_v0.py @@ -5,7 +5,7 @@ import collections import numpy as np -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import euler2quat diff --git a/myosuite/envs/myo/myobase/pose_v0.py b/myosuite/envs/myo/myobase/pose_v0.py index 3fef7fa8..091aa540 100644 --- a/myosuite/envs/myo/myobase/pose_v0.py +++ b/myosuite/envs/myo/myobase/pose_v0.py @@ -4,7 +4,7 @@ ================================================= """ import collections -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/reach_v0.py b/myosuite/envs/myo/myobase/reach_v0.py index 7514b62e..c7b3b87f 100644 --- a/myosuite/envs/myo/myobase/reach_v0.py +++ b/myosuite/envs/myo/myobase/reach_v0.py @@ -4,7 +4,7 @@ ================================================= """ import collections -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/reorient_sar_v0.py b/myosuite/envs/myo/myobase/reorient_sar_v0.py index 88de938a..efb337e1 100644 --- a/myosuite/envs/myo/myobase/reorient_sar_v0.py +++ b/myosuite/envs/myo/myobase/reorient_sar_v0.py @@ -5,7 +5,7 @@ import collections import numpy as np -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import euler2quat, mulQuat, negQuat, mat2quat diff --git a/myosuite/envs/myo/myobase/walk_v0.py b/myosuite/envs/myo/myobase/walk_v0.py index 730c393f..a95f0d03 100644 --- a/myosuite/envs/myo/myobase/walk_v0.py +++ b/myosuite/envs/myo/myobase/walk_v0.py @@ -4,7 +4,7 @@ ================================================= """ import collections -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import quat2mat @@ -139,7 +139,6 @@ def reset(self): obs = super().reset() return obs - class WalkEnvV0(BaseV0): DEFAULT_OBS_KEYS = [ diff --git a/myosuite/envs/myo/myochallenge/__init__.py b/myosuite/envs/myo/myochallenge/__init__.py index 3bb528da..a8bd11bd 100644 --- a/myosuite/envs/myo/myochallenge/__init__.py +++ b/myosuite/envs/myo/myochallenge/__init__.py @@ -1,4 +1,5 @@ -from gym.envs.registration import register +from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register + import os curr_dir = os.path.dirname(os.path.abspath(__file__)) @@ -16,7 +17,7 @@ 'frame_skip': 5, 'pos_th': 0.1, # cover entire base of the receptacle 'rot_th': np.inf, # ignore rotation errors - 'target_xyz_range': {'high':[0.2, -.35, 0.9], 'low':[0.0, -.1, 0.9]}, + 'target_xyz_range': {'high':[0.2, -.1, 0.9], 'low':[0.0, -.35, 0.9]}, 'target_rxryrz_range': {'high':[0.0, 0.0, 0.0], 'low':[0.0, 0.0, 0.0]} } ) diff --git a/myosuite/envs/myo/myochallenge/baoding_v1.py b/myosuite/envs/myo/myochallenge/baoding_v1.py index 7b3d0bb7..a9cee19b 100644 --- a/myosuite/envs/myo/myochallenge/baoding_v1.py +++ b/myosuite/envs/myo/myochallenge/baoding_v1.py @@ -5,7 +5,7 @@ import collections import enum -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myochallenge/chasetag_v0.py b/myosuite/envs/myo/myochallenge/chasetag_v0.py index 7441c2e9..0dbc460e 100644 --- a/myosuite/envs/myo/myochallenge/chasetag_v0.py +++ b/myosuite/envs/myo/myochallenge/chasetag_v0.py @@ -4,12 +4,11 @@ ================================================= """ import collections -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import numpy as np import pink import os from enum import Enum -from typing import Optional from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.envs.myo.myobase.walk_v0 import WalkEnvV0 @@ -200,17 +199,6 @@ def __init__(self, self.relief_range = relief_range self._populate_patches() - def flatten_agent_patch(self, qpos): - """ - Turn terrain in the patch around the agent to flat. - """ - # convert position to map position - pos = self.cart2map(qpos[:2]) - # get patch that belongs to the position - i = pos[0] // self.patch_size - j = pos[1] // self.patch_size - self._fill_patch(i, j, terrain_type=TerrainTypes.FLAT) - def _compute_patch_data(self, terrain_type): if terrain_type.name == 'FLAT': return np.zeros((self.patch_size, self.patch_size)) @@ -235,10 +223,11 @@ def _populate_patches(self): self._fill_patch(i, j, terrain_type) # put special terrain only once in 20% of episodes if self.rng.uniform() < 0.2: - i, j = self.rng.randint(0, self.patches_per_side, size=2) + i = self.rng.choice(range(self.patches_per_side)) + j = self.rng.choice(range(self.patches_per_side)) self._fill_patch(i, j, SpecialTerrains.RELIEF) - def _fill_patch(self, i, j, terrain_type=TerrainTypes.FLAT): + def _fill_patch(self, i, j, terrain_type='FLAT'): """ Fill patch at position , with terrain """ @@ -246,37 +235,20 @@ def _fill_patch(self, i, j, terrain_type=TerrainTypes.FLAT): j * self.patch_size: j * self.patch_size + self.patch_size] = self._compute_patch_data(terrain_type) def get_heightmap_obs(self): - """ - Get heightmap observation. - """ if self.heightmap_window is None: self.heightmap_window = np.zeros((10, 10)) self._measure_height() return self.heightmap_window[:].flatten().copy() - def cart2map(self, - points_1: list, - points_2: Optional[list] = None): + def cart2map(self, pos): """ Transform cartesian position [m * m] to rounded map position [nrow * ncol] - If only points_1 is given: Expects cartesian positions in [x, y] format. - If also points_2 is given: Expects points_1 = [x1, x2, ...] points_2 = [y1, y2, ...] """ delta_map = self.real_length / self.nrow offset = self.hfield.data.shape[0] / 2 - # x, y needs to be switched to match hfield. - if points_2 is None: - return np.array(points_1[::-1] / delta_map + offset, dtype=np.int16) - else: - ret1 = np.array(points_1[:] / delta_map + offset, dtype=np.int16) - ret2 = np.array(points_2[:] / delta_map + offset, dtype=np.int16) - return ret2, ret1 + return pos[:] / delta_map + offset def sample(self, rng=None): - """ - Sample an entire heightfield for the episode. - Update geom in viewer if rendering. - """ if not rng is None: self.rng = rng self._populate_patches() @@ -285,9 +257,6 @@ def sample(self, rng=None): # Patch types --------------- def _compute_rough_terrain(self): - """ - Compute data for a random noise rough terrain. - """ rough = self.rng.uniform(low=-1.0, high=1.0, size=(self.patch_size, self.patch_size)) normalized_data = (rough - np.min(rough)) / (np.max(rough) - np.min(rough)) scalar, offset = .08, .02 @@ -295,18 +264,12 @@ def _compute_rough_terrain(self): return normalized_data * scalar - offset def _compute_relief_terrain(self): - """ - Compute data for a special logo terrain. - """ curr_dir = os.path.dirname(__file__) relief = np.load(os.path.join(curr_dir, '../assets/myo_relief.npy')) normalized_data = (relief - np.min(relief)) / (np.max(relief) - np.min(relief)) return np.flipud(normalized_data) * self.rng.uniform(self.relief_range[0], self.relief_range[1]) def _compute_hilly_terrain(self): - """ - Compute data for a terrain with smooth hills. - """ frequency = 10 scalar = self.rng.uniform(low=self.hills_range[0], high=self.hills_range[1]) data = np.sin(np.linspace(0, frequency * np.pi, self.patch_size * self.patch_size) + np.pi / 2) - 1 @@ -317,7 +280,7 @@ def _compute_hilly_terrain(self): return normalized_data def _init_height_points(self): - """ Compute grid points at which height measurements are sampled (in base frame) + """ Compute points at which height measurments are sampled (in base frame) Saves the points in ndarray of shape (self.num_height_points, 3) """ measured_points_x = [-0.4, -0.3, -0.2, -0.1, 0., 0.1, 0.2, 0.3, 0.4, 0.5] @@ -333,14 +296,10 @@ def _init_height_points(self): self.height_points = points def _measure_height(self): - """ - Update heights at grid points around - model. - """ rot_direction = quat2euler(self.sim.data.qpos[3:7])[2] rot_mat = euler2mat([0, 0, rot_direction]) # rotate points around z-direction to match model - points = np.einsum("ij,kj->ik", self.height_points, rot_mat) + points = self.height_points @ rot_mat # increase point spacing points = (points * self.view_distance) # translate points to model frame @@ -349,17 +308,20 @@ def _measure_height(self): px = self.points[:, 0] py = self.points[:, 1] # get map_index coordinates of points - px, py = self.cart2map(px, py) + px = np.asarray(self.cart2map(px), dtype=np.int16) + py = np.asarray(self.cart2map(py), dtype=np.int16) # avoid out-of-bounds by clipping indices to map boundaries # -2 because we go one further and shape is 1 longer than map index px = np.clip(px, 0, self.hfield.data.shape[0] - 2) py = np.clip(py, 0, self.hfield.data.shape[1] - 2) - heights = self.hfield.data[px, py] + # switch x and y here because of array indexing + heights = self.hfield.data[py, px] + if not hasattr(self, 'length'): self.length = 0 self.length += 1 # align with egocentric view of model - self.heightmap_window[:] = np.flipud(np.rot90(heights.reshape(10, 10), axes=(1,0))) + self.heightmap_window[:] = np.rot90((heights).reshape(10, 10)) @property def size(self): @@ -414,6 +376,7 @@ def __init__(self, model_path, obsd_model_path=None, seed=None, **kwargs): # first construct the inheritance chain, which is just __init__ calls all the way down, with env_base # creating the sim / sim_obsd instances. Next we run through "setup" which relies on sim / sim_obsd # created in __init__ to complete the setup. + # base().__init__(model_path=model_path, obsd_model_path=obsd_model_path, seed=seed) BaseV0.__init__(self, model_path=model_path, obsd_model_path=obsd_model_path, seed=seed, env_credits=self.MYO_CREDIT) self._setup(**kwargs) @@ -566,22 +529,12 @@ def reset(self): self._sample_task() # randomized initial state qpos, qvel = self._get_reset_state() - self._maybe_flatten_agent_patch(qpos) self.robot.sync_sims(self.sim, self.sim_obsd) obs = super(WalkEnvV0, self).reset(reset_qpos=qpos, reset_qvel=qvel) self.opponent.reset_opponent(player_task=self.current_task.name, rng=self.np_random) self.sim.forward() return obs - def _maybe_flatten_agent_patch(self, qpos): - """ - Ensure that initial state patch is flat. - """ - if self.heightfield is not None: - self.heightfield.flatten_agent_patch(qpos) - if hasattr(self.sim, 'renderer') and not self.sim.renderer._window is None: - self.sim.renderer._window.update_hfield(0) - def _sample_task(self): if self.task_choice == 'random': self.current_task = self.np_random.choice(Task) @@ -607,8 +560,6 @@ def _randomize_position_orientation(self, qpos, qvel): euler_angle = quat2euler(qpos[3:7]) euler_angle[-1] = orientation qpos[3:7] = euler2quat(euler_angle) - # rotate original velocity with unit direction vector - qvel[:2] = np.array([np.cos(orientation), np.sin(orientation)]) * np.linalg.norm(qvel[:2]) return qpos, qvel def _get_reset_state(self): @@ -620,17 +571,6 @@ def _get_reset_state(self): else: return self.sim.model.key_qpos[0], self.sim.model.key_qvel[0] - def _maybe_adjust_height(self, qpos, qvel): - """ - Currently not used. - """ - if self.heightfield is not None: - map_i, map_j = self.heightfield.cart2map(qpos[:2]) - hfield_val = self.heightfield.hfield.data[map_i, map_j] - if hfield_val > 0.05: - qpos[2] += hfield_val - return qpos, qvel - def viewer_setup(self, *args, **kwargs): """ Setup the default camera @@ -790,7 +730,7 @@ def _get_actuator_names(self): Return a list of actuator names according to the index ID of the actuators ''' return [self.sim.model.actuator(act_id).name for act_id in range(1, self.sim.model.na)] - + def _get_fallen_condition(self): """ diff --git a/myosuite/envs/myo/myochallenge/relocate_v0.py b/myosuite/envs/myo/myochallenge/relocate_v0.py index 15fdd0b4..c38eece5 100644 --- a/myosuite/envs/myo/myochallenge/relocate_v0.py +++ b/myosuite/envs/myo/myochallenge/relocate_v0.py @@ -5,7 +5,7 @@ import collections import numpy as np -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import mat2euler, euler2quat @@ -153,7 +153,7 @@ def reset(self, reset_qpos=None, reset_qvel=None): for gid in range(self.sim.model.body_geomnum[bid]): gid+=self.sim.model.body_geomadr[bid] # get geom ids # update type, size, and collision bounds - self.sim.model.geom_type[gid]=self.np_random.randint(low=2, high=7) # random shape + self.sim.model.geom_type[gid]=self.np_random.choice([2,3,4,5,6]) # random shape self.sim.model.geom_size[gid]=self.np_random.uniform(low=self.obj_geom_range['low'], high=self.obj_geom_range['high']) # random size self.sim.model.geom_aabb[gid][3:]= self.obj_geom_range['high'] # bounding box, (center, size) self.sim.model.geom_rbound[gid] = 2.0*max(self.obj_geom_range['high']) # radius of bounding sphere diff --git a/myosuite/envs/myo/myochallenge/reorient_v0.py b/myosuite/envs/myo/myochallenge/reorient_v0.py index 91388538..bdb3114e 100644 --- a/myosuite/envs/myo/myochallenge/reorient_v0.py +++ b/myosuite/envs/myo/myochallenge/reorient_v0.py @@ -5,7 +5,7 @@ import collections import numpy as np -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import mat2euler, euler2quat diff --git a/myosuite/envs/myo/myodm/__init__.py b/myosuite/envs/myo/myodm/__init__.py index b77280e7..925b7c45 100644 --- a/myosuite/envs/myo/myodm/__init__.py +++ b/myosuite/envs/myo/myodm/__init__.py @@ -1,4 +1,5 @@ -from gym.envs.registration import register +from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register + import collections import os import numpy as np diff --git a/myosuite/envs/myo/myodm/myodm_v0.py b/myosuite/envs/myo/myodm/myodm_v0.py index 7e4787e6..1fd48cef 100644 --- a/myosuite/envs/myo/myodm/myodm_v0.py +++ b/myosuite/envs/myo/myodm/myodm_v0.py @@ -1,11 +1,11 @@ """ ================================================= Copyright (C) 2018 Vikash Kumar Author :: Vikash Kumar (vikashplus@gmail.com), Sudeep Dasari (sdasari@andrew.cmu.edu), Vittorio Caggiano (caggiano@gmail.com) -Source :: https://github.com/vikashplus/robohive +Source :: https://github.com/MyoHub/myosuite License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.envs import env_base from myosuite.logger.reference_motion import ReferenceMotion from myosuite.utils.quat_math import quat2euler, euler2quat, quatDiff2Vel, mat2quat diff --git a/myosuite/logger/examine_logs.py b/myosuite/logger/examine_logs.py index cef1cdca..04dcd8a2 100644 --- a/myosuite/logger/examine_logs.py +++ b/myosuite/logger/examine_logs.py @@ -8,7 +8,7 @@ > Render options\n - either onscreen, or offscreen, or just rollout without rendering.\n > Save options:\n - - save resulting rollouts as RoboHive/Roboset format, and as 2D plots\n + - save resulting rollouts as myosuite/Roboset format, and as 2D plots\n USAGE:\n $ python examine_rollout.py --env_name door-v0 \n $ python examine_rollout.py --env_name door-v0 --rollout_path my_rollouts.h5 --repeat 10 \n @@ -17,7 +17,7 @@ from myosuite.utils.paths_utils import plot as plotnsave_paths from myosuite.utils import tensor_utils -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import click import numpy as np import time @@ -27,7 +27,7 @@ @click.command(help=DESC) @click.option('-e', '--env_name', type=str, help='environment to load', required=True) @click.option('-p', '--rollout_path', type=str, help='absolute path of the rollout', default=None) -@click.option('-f', '--rollout_format', type=click.Choice(['RoboHive', 'RoboSet']), help='Data format', default='RoboHive') +@click.option('-f', '--rollout_format', type=click.Choice(['myosuite', 'RoboSet']), help='Data format', default='myosuite') @click.option('-m', '--mode', type=click.Choice(['record', 'render', 'playback', 'recover']), help='How to examine rollout', default='playback') @click.option('-h', '--horizon', type=int, help='Rollout horizon, when mode is record', default=-1) @click.option('-s', '--seed', type=int, help='seed for generating environment instances', default=123) @@ -48,11 +48,11 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu # seed and load environments np.random.seed(seed) env = gym.make(env_name) if env_args==None else gym.make(env_name, **(eval(env_args))) - env = env.env + env = env.unwrapped env.seed(seed) # Start a "trace" for recording rollouts - if rollout_format=='RoboHive': + if rollout_format=='myosuite': from myosuite.logger.grouped_datasets import Trace elif rollout_format=='RoboSet': from myosuite.logger.roboset_logger import RoboSet_Trace as Trace @@ -98,7 +98,7 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu trace.create_group(path_name) # init: reset to starting state - if path_data and rollout_format=='RoboHive': + if path_data and rollout_format=='myosuite': # reset to init state if "state" in path_data['env_infos'].keys(): path_state = tensor_utils.split_tensor_dict_list(path_data['env_infos']['state']) @@ -122,7 +122,7 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu trace_horizon = horizon if mode=='record' else path_data['time'].shape[0]-1 # Rollout path -------------------------------- - obs, rwd, done, env_info = env.forward(update_exteroception=include_exteroception) + obs, rwd, done, *_, env_info = env.forward(update_exteroception=include_exteroception) ep_rwd = rwd for i_step in range(trace_horizon+1): @@ -137,7 +137,7 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu # populate actions merely for logging if rollout_format=='RoboSet': act = np.concatenate([path_data['ctrl_arm'][i_step], path_data['ctrl_ee'][i_step]]) - elif rollout_format=='RoboHive' and "state" in path_data['env_infos'].keys(): + elif rollout_format=='myosuite' and "state" in path_data['env_infos'].keys(): act = path_data['actions'][i_step] else: raise NotImplementedError("Settings not found") @@ -146,7 +146,7 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu elif mode=='playback': if rollout_format=='RoboSet': act = np.concatenate([path_data['ctrl_arm'][i_step], path_data['ctrl_ee'][i_step]]) - elif rollout_format=='RoboHive': + elif rollout_format=='myosuite': act = path_data['actions'][i_step] # Recover actions from states @@ -154,7 +154,7 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu # assumes position controls if rollout_format=='RoboSet': act = np.concatenate([path_data['qp_arm'][i_step], path_data['qp_ee'][i_step]]) - elif rollout_format=='RoboHive': + elif rollout_format=='myosuite': act = path_data['env_infos']['obs_dict']['qp'][i_step] if noise_scale: act = act + env.np_random.uniform(high=noise_scale, low=-noise_scale, size=len(act)).astype(act.dtype) @@ -201,14 +201,14 @@ def examine_logs(env_name, rollout_path, rollout_format, mode, horizon, seed, nu env.sim.data.qvel[:nq_arm]= path_data['qv_arm'][i_step+1] env.sim.data.qvel[nq_arm:nq_arm+nq_ee]= path_data['qv_ee'][i_step+1] env.sim.data.time = path_data['time'][i_step+1] - elif rollout_format=='RoboHive' and "state" in path_data['env_infos'].keys(): + elif rollout_format=='myosuite' and "state" in path_data['env_infos'].keys(): env.set_env_state(path_state[i_step+1]) else: raise NotImplementedError("Settings not found") - obs, rwd, done, env_info = env.forward(update_exteroception=include_exteroception) + obs, rwd, done, *_, env_info = env.forward(update_exteroception=include_exteroception) ep_rwd += rwd elif i_step < trace_horizon: # incase last step actions (nans) can cause issues in step - obs, rwd, done, env_info = env.step(act, update_exteroception=include_exteroception) + obs, rwd, done, *_, env_info = env.step(act, update_exteroception=include_exteroception) ep_rwd += rwd # save offscreen buffers as video and clear the dataset diff --git a/myosuite/logger/examine_reference.py b/myosuite/logger/examine_reference.py index 7fb2c6f5..ba982d96 100644 --- a/myosuite/logger/examine_reference.py +++ b/myosuite/logger/examine_reference.py @@ -1,5 +1,5 @@ import myosuite -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() import time import click from tqdm import tqdm diff --git a/myosuite/logger/grouped_datasets.py b/myosuite/logger/grouped_datasets.py index 32791b72..642cac45 100644 --- a/myosuite/logger/grouped_datasets.py +++ b/myosuite/logger/grouped_datasets.py @@ -25,7 +25,7 @@ class TraceType(enum.Enum): """Trace types.""" UNSET = -1 - ROBOHIVE = 0 + myosuite = 0 ROBOSET = 1 def get_type(input_type): @@ -33,8 +33,8 @@ def get_type(input_type): A more robust way of getting trace type. Supports strings """ if type(input_type) == str: - if input_type.lower() == "robohive": - return TraceType.ROBOHIVE + if input_type.lower() == "myosuite": + return TraceType.myosuite elif input_type.lower() == "roboset": return TraceType.ROBOSET else: @@ -48,7 +48,7 @@ def __init__(self, name): self.root = {name: {}} self.trace = self.root[name] self.index = 0 - self.type = TraceType.ROBOHIVE + self.type = TraceType.myosuite # Create a group in your logs def create_group(self, name): diff --git a/myosuite/logger/roboset_logger.py b/myosuite/logger/roboset_logger.py index 09729b7a..418498ab 100644 --- a/myosuite/logger/roboset_logger.py +++ b/myosuite/logger/roboset_logger.py @@ -9,10 +9,10 @@ def __init__(self, name, **kwargs): self.trace_type=TraceType.ROBOSET - # parse path from robohive format into robopen dataset format + # parse path from myosuite format into robopen dataset format def path2dataset(self, path:dict, config_path=None)->dict: """ - Convert Robohive format into roboset format + Convert RoboHive format into roboset format """ path_keys = path.keys() diff --git a/myosuite/physics/mj_sim_scene.py b/myosuite/physics/mj_sim_scene.py index 75fc692d..6cc0a3f8 100644 --- a/myosuite/physics/mj_sim_scene.py +++ b/myosuite/physics/mj_sim_scene.py @@ -1,7 +1,7 @@ """ ================================================= Copyright (C) 2018 Vikash Kumar, Copyright (C) 2019 The ROBEL Authors Author :: Vikash Kumar (vikashplus@gmail.com) -Source :: https://github.com/vikashplus/robohive +Source :: https://github.com/vikashplus/myosuite License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ diff --git a/myosuite/physics/mjpy_sim_scene.py b/myosuite/physics/mjpy_sim_scene.py index ce999c5f..ce5228b3 100644 --- a/myosuite/physics/mjpy_sim_scene.py +++ b/myosuite/physics/mjpy_sim_scene.py @@ -1,7 +1,7 @@ """ ================================================= Copyright (C) 2018 Vikash Kumar, Copyright (C) 2019 The ROBEL Authors Author :: Vikash Kumar (vikashplus@gmail.com) -Source :: https://github.com/vikashplus/robohive +Source :: https://github.com/vikashplus/myosuite License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ diff --git a/myosuite/physics/sim_scene.py b/myosuite/physics/sim_scene.py index ac28ef19..bfcf3ff2 100644 --- a/myosuite/physics/sim_scene.py +++ b/myosuite/physics/sim_scene.py @@ -1,7 +1,7 @@ """ ================================================= Copyright (C) 2018 Vikash Kumar, Copyright (C) 2019 The ROBEL Authors Author :: Vikash Kumar (vikashplus@gmail.com) -Source :: https://github.com/vikashplus/robohive +Source :: https://github.com/vikashplus/myosuite License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ diff --git a/myosuite/physics/sim_scene_test.py b/myosuite/physics/sim_scene_test.py index 3ef350f7..edb832be 100644 --- a/myosuite/physics/sim_scene_test.py +++ b/myosuite/physics/sim_scene_test.py @@ -1,7 +1,7 @@ """ ================================================= Copyright (C) 2018 Vikash Kumar, Copyright (C) 2019 The ROBEL Authors Author :: Vikash Kumar (vikashplus@gmail.com) -Source :: https://github.com/vikashplus/robohive +Source :: https://github.com/vikashplus/myosuite License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ diff --git a/myosuite/robot/robot.py b/myosuite/robot/robot.py index c962f2dc..762f2851 100644 --- a/myosuite/robot/robot.py +++ b/myosuite/robot/robot.py @@ -780,7 +780,7 @@ def reset(self, # close connection and exit out of the robot def close(self): - # prompt("Closing {}".format(self.name), 'white', 'on_grey', flush=True) + prompt("Closing {}".format(self.name), 'white', 'on_grey', flush=True) if self.is_hardware: status = self.hardware_close() prompt("Closed (Status: {})".format(status), 'white', 'on_grey', flush=True) @@ -792,7 +792,7 @@ def __del__(self): def demo_robot(): - import gym + from myosuite.utils.import_utils import import_gym; gym = import_gym() prompt("Starting Robot===================") env = gym.make('FrankaReachFixed-v0') diff --git a/myosuite/utils/curriculum_utils.py b/myosuite/utils/curriculum_utils.py new file mode 100644 index 00000000..ef39ed97 --- /dev/null +++ b/myosuite/utils/curriculum_utils.py @@ -0,0 +1,38 @@ + +class curriculum(): + """ + Set up an curriculum factoring the current progress of agents + """ + def __init__(self, + threshold = 90.0, # value above which curriculum is active + rate = 1.0/100.0, # rate of progress for curriculum + start = 0.0, # starting value of curriculum + end = 1.0, # ending value of curriculum + filter_coef = 0.95, # filter for updating the progress + ): + + self._threshold = threshold + self._rate = rate + self._start = start + self._end = end + self._filter_coef = filter_coef + + self._value = 0.0 # curriculum's current value + self._progress = 0.0 # curriculum's measure of overall progress + + assert self._rate>0, "rate should always be positive" + + # update the curriculum based on current progress made by the agent + def update(self, current_success): + # update the progress measure + self._progress = self._progress*self._filter_coef + current_success*(1.-self._filter_coef) + + # if sufficient progress, bump curriculum + if self._value <= 1.0: # if not saturated + if(current_success>=self._threshold): # if maintaining quality + if(self._progress>=self._threshold): # if progress is satisfactory + self._value += self._rate + + # get the current curriculum status + def status(self): + return self._start + self._value*(self._end - self._start) \ No newline at end of file diff --git a/myosuite/utils/examine_env.py b/myosuite/utils/examine_env.py index 4003d3a4..d457f939 100644 --- a/myosuite/utils/examine_env.py +++ b/myosuite/utils/examine_env.py @@ -5,7 +5,7 @@ License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -import gym +from myosuite.utils.import_utils import import_gym; gym = import_gym() from myosuite.utils.paths_utils import plot as plotnsave_paths import click import numpy as np @@ -28,7 +28,7 @@ class rand_policy(): def __init__(self, env, seed): self.env = env - self.env.action_space.np_random.seed(seed) # requires exlicit seeding + self.env.action_space.seed(seed) # requires explicit seeding def get_action(self, obs): # return self.env.np_random.uniform(high=self.env.action_space.high, low=self.env.action_space.low) diff --git a/myosuite/utils/implement_for.py b/myosuite/utils/implement_for.py new file mode 100644 index 00000000..c1b4e102 --- /dev/null +++ b/myosuite/utils/implement_for.py @@ -0,0 +1,211 @@ +from __future__ import annotations +import collections +import inspect +import sys +from copy import copy +from functools import wraps +from importlib import import_module +from typing import Union, Callable, Dict +from packaging.version import parse + +class implement_for: + """A version decorator that checks the version in the environment and implements a function with the fitting one. + + If specified module is missing or there is no fitting implementation, call of the decorated function + will lead to the explicit error. + In case of intersected ranges, last fitting implementation is used. + + This wrapper also works to implement different backends for a same function (eg. gym vs gymnasium, + numpy vs jax-numpy etc). + + Args: + module_name (str or callable): version is checked for the module with this + name (e.g. "gym"). If a callable is provided, it should return the + module. + from_version: version from which implementation is compatible. Can be open (None). + to_version: version from which implementation is no longer compatible. Can be open (None). + + Examples: + >>> @implement_for("gym", "0.13", "0.14") + >>> def fun(self, x): + ... # Older gym versions will return x + 1 + ... return x + 1 + ... + >>> @implement_for("gym", "0.14", "0.23") + >>> def fun(self, x): + ... # More recent gym versions will return x + 2 + ... return x + 2 + ... + >>> @implement_for(lambda: import_module("gym"), "0.23", None) + >>> def fun(self, x): + ... # More recent gym versions will return x + 2 + ... return x + 2 + ... + >>> @implement_for("gymnasium", "0.27", None) + >>> def fun(self, x): + ... # If gymnasium is to be used instead of gym, x+3 will be returned + ... return x + 3 + ... + + This indicates that the function is compatible with gym 0.13+, but doesn't with gym 0.14+. + """ + + # Stores pointers to fitting implementations: dict[func_name] = func_pointer + _implementations = {} + _setters = [] + _cache_modules = {} + + def __init__( + self, + module_name: Union[str, Callable], + from_version: str = None, + to_version: str = None, + ): + self.module_name = module_name + self.from_version = from_version + self.to_version = to_version + implement_for._setters.append(self) + + @staticmethod + def check_version(version, from_version, to_version): + return (from_version is None or parse(version) >= parse(from_version)) and ( + to_version is None or parse(version) < parse(to_version) + ) + + @staticmethod + def get_class_that_defined_method(f): + """Returns the class of a method, if it is defined, and None otherwise.""" + out = f.__globals__.get(f.__qualname__.split(".")[0], None) + return out + + @classmethod + def get_func_name(cls, fn): + # produces a name like torchrl.module.Class.method or torchrl.module.function + first = str(fn).split(".")[0][len(" str: + """Imports module and returns its version.""" + if not callable(module_name): + module = cls._cache_modules.get(module_name, None) + if module is None: + if module_name in sys.modules: + sys.modules[module_name] = module = import_module(module_name) + else: + cls._cache_modules[module_name] = module = import_module( + module_name + ) + else: + module = module_name() + return module.__version__ + + _lazy_impl = collections.defaultdict(list) + + def _delazify(self, func_name): + for local_call in implement_for._lazy_impl[func_name]: + out = local_call() + return out + + def __call__(self, fn): + # function names are unique + self.func_name = self.get_func_name(fn) + self.fn = fn + implement_for._lazy_impl[self.func_name].append(self._call) + + @wraps(fn) + def _lazy_call_fn(*args, **kwargs): + # first time we call the function, we also do the replacement. + # This will cause the imports to occur only during the first call to fn + return self._delazify(self.func_name)(*args, **kwargs) + + return _lazy_call_fn + + def _call(self): + + # If the module is missing replace the function with the mock. + fn = self.fn + func_name = self.func_name + implementations = implement_for._implementations + + @wraps(fn) + def unsupported(*args, **kwargs): + raise ModuleNotFoundError( + f"Supported version of '{func_name}' has not been found." + ) + + self.do_set = False + # Return fitting implementation if it was encountered before. + if func_name in implementations: + try: + # check that backends don't conflict + version = self.import_module(self.module_name) + if self.check_version(version, self.from_version, self.to_version): + self.do_set = True + if not self.do_set: + return implementations[func_name].fn + except ModuleNotFoundError: + # then it's ok, there is no conflict + return implementations[func_name].fn + else: + try: + version = self.import_module(self.module_name) + if self.check_version(version, self.from_version, self.to_version): + self.do_set = True + except ModuleNotFoundError: + return unsupported + if self.do_set: + self.module_set() + return fn + return unsupported + + @classmethod + def reset(cls, setters_dict: Dict[str, implement_for] = None): + """Resets the setters in setter_dict. + + ``setter_dict`` is a copy of implementations. We just need to iterate through its + values and call :meth:`~.module_set` for each. + + """ + if setters_dict is None: + setters_dict = copy(cls._implementations) + for setter in setters_dict.values(): + setter.module_set() + + def __repr__(self): + return ( + f"{self.__class__.__name__}(" + f"module_name={self.module_name}({self.from_version, self.to_version}), " + f"fn_name={self.fn.__name__}, cls={self._get_cls(self.fn)}, is_set={self.do_set})" + ) diff --git a/myosuite/utils/import_utils.py b/myosuite/utils/import_utils.py index dbbb493b..ae29b00e 100644 --- a/myosuite/utils/import_utils.py +++ b/myosuite/utils/import_utils.py @@ -1,4 +1,17 @@ import importlib +import importlib.util +import os +from os.path import expanduser +#import git + + +def import_gym(): + if importlib.util.find_spec("gymnasium"): + import gymnasium as gg + elif importlib.util.find_spec("gym"): + import gym as gg + return gg + def mujoco_py_isavailable(): help = """ @@ -77,6 +90,59 @@ def vc_isavailable(): if importlib.util.find_spec("vc_models") is None: raise ModuleNotFoundError(help) +def simhive_isavailable(robohive_version): + help = """ + RoboHive environments requires SimHive for simulation assets. + Steps: + (1) Ensure RoboHive is installed and visible (pip show robohive) + (2) Ensure RoboHive is initialized before using. Options - + (a) robohive_init + (b) python -m robohive_init + """ + file_dir = os.path.dirname(os.path.abspath(__file__)) + if not os.path.exists(os.path.join(file_dir, "../simhive")): + raise ModuleNotFoundError(help) + + # Check if touch file for SimHive exists + file_name = os.path.join(file_dir, "../simhive", 'simhive-version') + if os.path.isfile(file_name): + # Recover SimHive version + with open(file_name, 'r') as file: + simhive_version = file.read() + + # Ensure that SimHive version matches RoboHive version + assert simhive_version==robohive_version, f"Version Mismatch: SimHive({simhive_version}) != RoboHive({robohive_version}). \nReinitialize RoboHive (python -m robohive_init)" + + +def fetch_git(repo_url, commit_hash, clone_directory, clone_path=None): + if clone_path is None: + clone_path = os.path.join(expanduser("~"), ".robohive") + clone_directory = os.path.join(clone_path, clone_directory) + + try: + # Create the clone directory if it doesn't exist + os.makedirs(clone_directory, exist_ok=True) + + # Clone the repository to the specified path + if not os.path.exists(os.path.join(clone_directory,'.git')): + repo = git.Repo.clone_from(repo_url, clone_directory) + print(f"{repo_url} cloned at {clone_directory}") + else: + repo = git.Repo(clone_directory) + origin = repo.remote('origin') + origin.fetch() + + # Check out the specific commit if not already + current_commit_hash = repo.head.commit.hexsha + if current_commit_hash != commit_hash: + repo.git.checkout(commit_hash) + print(f"{repo_url}@{commit_hash} fetched at {clone_directory}") + + except git.GitCommandError as e: + print(f"Error: {e}") + + return clone_directory + if __name__ == '__main__': mujoco_py_isavailable() diff --git a/myosuite/utils/paths_utils.py b/myosuite/utils/paths_utils.py index b99299b1..29237ba5 100644 --- a/myosuite/utils/paths_utils.py +++ b/myosuite/utils/paths_utils.py @@ -237,7 +237,7 @@ def render(rollout_path, render_format:str="mp4", cam_names:list=["left"]): print("\nSaving: " + file_name_mp4) -# parse path from robohive format into robopen dataset format +# parse path from myosuite format into robopen dataset format def path2dataset(path:dict, config_path=None)->dict: """ Convert Robohive format into roboset format From af13c63ea7f73912ad37854ecd01359dd2ee6cce Mon Sep 17 00:00:00 2001 From: Vittorio Caggiano Date: Tue, 12 Dec 2023 00:26:19 -0600 Subject: [PATCH 02/62] fix simplified gym import --- README.md | 3 +- docs/source/tutorials/1_Get_Started.ipynb | 3 +- docs/source/tutorials/2_Load_policy.ipynb | 5 +- .../tutorials/3_Analyse_movements.ipynb | 5 +- docs/source/tutorials/4_Train_policy.ipynb | 5 +- docs/source/tutorials/4a_deprl.ipynb | 17 ++---- .../source/tutorials/4c_Train_SB_policy.ipynb | 5 +- .../tutorials/5_Move_Hand_Fingers.ipynb | 3 +- myosuite/envs/env_base.py | 2 +- myosuite/envs/env_variants.py | 3 +- myosuite/envs/myo/myobase/__init__.py | 5 +- myosuite/envs/myo/myobase/key_turn_v0.py | 4 +- myosuite/envs/myo/myobase/obj_hold_v0.py | 4 +- myosuite/envs/myo/myobase/pen_v0.py | 4 +- myosuite/envs/myo/myobase/pose_v0.py | 3 +- myosuite/envs/myo/myobase/reach_v0.py | 3 +- myosuite/envs/myo/myobase/reorient_sar_v0.py | 3 +- myosuite/envs/myo/myobase/walk_v0.py | 5 +- myosuite/envs/myo/myochallenge/__init__.py | 4 +- myosuite/envs/myo/myochallenge/baoding_v1.py | 3 +- myosuite/envs/myo/myochallenge/chasetag_v0.py | 3 +- myosuite/envs/myo/myochallenge/relocate_v0.py | 3 +- myosuite/envs/myo/myochallenge/reorient_v0.py | 3 +- myosuite/envs/myo/myodm/__init__.py | 4 +- myosuite/envs/myo/myodm/myodm_v0.py | 3 +- myosuite/logger/examine_logs.py | 3 +- myosuite/logger/examine_reference.py | 3 +- myosuite/tests/test_envs.py | 57 ++++++++++++++----- myosuite/tests/test_myo.py | 19 +++++++ myosuite/tests/test_tutorials.sh | 7 ++- myosuite/utils/__init__.py | 16 ++++++ myosuite/utils/examine_env.py | 3 +- myosuite/utils/import_utils.py | 25 +++++--- 33 files changed, 156 insertions(+), 82 deletions(-) diff --git a/README.md b/README.md index a455a208..b770d112 100644 --- a/README.md +++ b/README.md @@ -59,8 +59,7 @@ It is possible to create and interface with MyoSuite environments just like any ```python -import myosuite -import gym +from myosuite.utils import gym env = gym.make('myoElbowPose1D6MRandom-v0') env.reset() for _ in range(1000): diff --git a/docs/source/tutorials/1_Get_Started.ipynb b/docs/source/tutorials/1_Get_Started.ipynb index fe733bd3..874354e6 100644 --- a/docs/source/tutorials/1_Get_Started.ipynb +++ b/docs/source/tutorials/1_Get_Started.ipynb @@ -22,8 +22,7 @@ } ], "source": [ - "import myosuite\n", - "import gym\n", + "from myosuite.utils import gym\n", "import skvideo.io\n", "import numpy as np\n", "import os" diff --git a/docs/source/tutorials/2_Load_policy.ipynb b/docs/source/tutorials/2_Load_policy.ipynb index 5af76be8..9c8dcbca 100644 --- a/docs/source/tutorials/2_Load_policy.ipynb +++ b/docs/source/tutorials/2_Load_policy.ipynb @@ -6,8 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "import myosuite\n", - "import gym\n", + "from myosuite.utils import gym\n", "import skvideo.io\n", "import numpy as np\n", "import os" @@ -79,7 +78,7 @@ " frames.append(frame)\n", " o = env.get_obs()\n", " a = pi.get_action(o)[0]\n", - " next_o, r, done, ifo = env.step(a) # take an action based on the current observation\n", + " next_o, r, done, *_, ifo = env.step(a) # take an action based on the current observation\n", "env.close()\n", "\n", "os.makedirs('videos', exist_ok=True)\n", diff --git a/docs/source/tutorials/3_Analyse_movements.ipynb b/docs/source/tutorials/3_Analyse_movements.ipynb index 120a0673..fe342f21 100644 --- a/docs/source/tutorials/3_Analyse_movements.ipynb +++ b/docs/source/tutorials/3_Analyse_movements.ipynb @@ -6,8 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "import myosuite\n", - "import gym\n", + "from myosuite.utils import gym\n", "import skvideo.io\n", "import numpy as np\n", "import os" @@ -45,7 +44,7 @@ " for _ in range(100): # 100 samples for each episode\n", " o = env.get_obs()\n", " a = pi.predict(o)[0]\n", - " next_o, r, done, ifo = env.step(a) # take a random action\n", + " next_o, r, done, *_, ifo = env.step(a) # take a random action\n", " \n", " data_store.append({\"action\":a.copy(), \n", " \"jpos\":env.sim.data.qpos.copy(), \n", diff --git a/docs/source/tutorials/4_Train_policy.ipynb b/docs/source/tutorials/4_Train_policy.ipynb index 5bf3bfa8..0c7e59e7 100644 --- a/docs/source/tutorials/4_Train_policy.ipynb +++ b/docs/source/tutorials/4_Train_policy.ipynb @@ -6,8 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "import myosuite\n", - "import gym\n", + "from myosuite.utils import gym\n", "import skvideo.io\n", "import numpy as np\n", "import os" @@ -122,7 +121,7 @@ " frames.append(frame[::-1,:,:])\n", " o = env.get_obs()\n", " a = pi.get_action(o)[0]\n", - " next_o, r, done, ifo = env.step(a) # take an action based on the current observation\n", + " next_o, r, done, *_, ifo = env.step(a) # take an action based on the current observation\n", "env.close()\n", "\n", "os.makedirs('videos', exist_ok=True)\n", diff --git a/docs/source/tutorials/4a_deprl.ipynb b/docs/source/tutorials/4a_deprl.ipynb index 5f374eba..deb9c257 100644 --- a/docs/source/tutorials/4a_deprl.ipynb +++ b/docs/source/tutorials/4a_deprl.ipynb @@ -29,10 +29,8 @@ } ], "source": [ - "\n", - "import gym, myosuite\n", - "import deprl\n", - "import gym" + "from myosuite.utils import gym\n", + "import deprl" ] }, { @@ -75,10 +73,10 @@ "source": [ "policy = deprl.load_baseline(env)\n", "\n", - "obs = env.reset()\n", + "obs = env.reset()[0]\n", "for _ in range(T):\n", " action = policy(obs)\n", - " obs, rew, done, info = env.step(action)\n", + " obs, rew, done, *_, info = env.step(action)\n", " if done:\n", " break\n", "env.close()\n", @@ -95,13 +93,6 @@ "source": [ "If you want to load your own policy, replace `deprl.load_baseline(env)` with `deprl.load(path, env)`. This will automatically load it for you. We also provide more advanced commands like `python -m deprl.play --path /folder/` to setup a visualization script." ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/docs/source/tutorials/4c_Train_SB_policy.ipynb b/docs/source/tutorials/4c_Train_SB_policy.ipynb index 0eda6259..ee256971 100644 --- a/docs/source/tutorials/4c_Train_SB_policy.ipynb +++ b/docs/source/tutorials/4c_Train_SB_policy.ipynb @@ -6,8 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "import myosuite\n", - "import gym\n", + "from myosuite.utils import gym\n", "import skvideo.io\n", "import numpy as np\n", "import os" @@ -92,7 +91,7 @@ " frames.append(frame[::-1,:,:])\n", " o = env.get_obs()\n", " a = pi.predict(o)[0]\n", - " next_o, r, done, ifo = env.step(a) # take an action based on the current observation\n", + " next_o, r, done, *_, ifo = env.step(a) # take an action based on the current observation\n", "env.close()\n", "\n", "os.makedirs('videos', exist_ok=True)\n", diff --git a/docs/source/tutorials/5_Move_Hand_Fingers.ipynb b/docs/source/tutorials/5_Move_Hand_Fingers.ipynb index 9e2d934a..d043218e 100644 --- a/docs/source/tutorials/5_Move_Hand_Fingers.ipynb +++ b/docs/source/tutorials/5_Move_Hand_Fingers.ipynb @@ -6,8 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "import myosuite\n", - "import gym\n", + "from myosuite.utils import gym\n", "import skvideo.io\n", "import numpy as np\n", "import os" diff --git a/myosuite/envs/env_base.py b/myosuite/envs/env_base.py index 733423c7..fd63ca66 100644 --- a/myosuite/envs/env_base.py +++ b/myosuite/envs/env_base.py @@ -7,7 +7,7 @@ # TODO: find how to make this compatible with gymnasium. Maybe a global variable that indicates what to use as backend? # from myosuite.utils.import_utils import import_gym; gym = import_gym() -from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np import os import time as timer diff --git a/myosuite/envs/env_variants.py b/myosuite/envs/env_variants.py index b2b4450d..45dc04f2 100644 --- a/myosuite/envs/env_variants.py +++ b/myosuite/envs/env_variants.py @@ -5,7 +5,8 @@ License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register +# from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register +from myosuite.utils import gym; register=gym.register import collections from copy import deepcopy from flatten_dict import flatten, unflatten diff --git a/myosuite/envs/myo/myobase/__init__.py b/myosuite/envs/myo/myobase/__init__.py index 00c2d0b0..ff021de0 100644 --- a/myosuite/envs/myo/myobase/__init__.py +++ b/myosuite/envs/myo/myobase/__init__.py @@ -3,8 +3,9 @@ Authors :: Vikash Kumar (vikashplus@gmail.com), Vittorio Caggiano (caggiano@gmail.com) ================================================= """ -from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register - +# from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register +from myosuite.utils import gym +register=gym.register from myosuite.envs.env_variants import register_env_variant import os diff --git a/myosuite/envs/myo/myobase/key_turn_v0.py b/myosuite/envs/myo/myobase/key_turn_v0.py index c22bd9f5..14a59c0c 100644 --- a/myosuite/envs/myo/myobase/key_turn_v0.py +++ b/myosuite/envs/myo/myobase/key_turn_v0.py @@ -5,8 +5,8 @@ import collections import numpy as np -from myosuite.utils.import_utils import import_gym; gym = import_gym() - +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/obj_hold_v0.py b/myosuite/envs/myo/myobase/obj_hold_v0.py index 1a2b938c..60b176a3 100644 --- a/myosuite/envs/myo/myobase/obj_hold_v0.py +++ b/myosuite/envs/myo/myobase/obj_hold_v0.py @@ -5,8 +5,8 @@ import collections import numpy as np -from myosuite.utils.import_utils import import_gym; gym = import_gym() - +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/pen_v0.py b/myosuite/envs/myo/myobase/pen_v0.py index e3f727ef..681d0a25 100644 --- a/myosuite/envs/myo/myobase/pen_v0.py +++ b/myosuite/envs/myo/myobase/pen_v0.py @@ -5,8 +5,8 @@ import collections import numpy as np -from myosuite.utils.import_utils import import_gym; gym = import_gym() - +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import euler2quat from myosuite.utils.vector_math import calculate_cosine diff --git a/myosuite/envs/myo/myobase/pose_v0.py b/myosuite/envs/myo/myobase/pose_v0.py index 091aa540..b9d89f4d 100644 --- a/myosuite/envs/myo/myobase/pose_v0.py +++ b/myosuite/envs/myo/myobase/pose_v0.py @@ -4,7 +4,8 @@ ================================================= """ import collections -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/reach_v0.py b/myosuite/envs/myo/myobase/reach_v0.py index c7b3b87f..aa92ddef 100644 --- a/myosuite/envs/myo/myobase/reach_v0.py +++ b/myosuite/envs/myo/myobase/reach_v0.py @@ -4,7 +4,8 @@ ================================================= """ import collections -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myobase/reorient_sar_v0.py b/myosuite/envs/myo/myobase/reorient_sar_v0.py index efb337e1..5930317e 100644 --- a/myosuite/envs/myo/myobase/reorient_sar_v0.py +++ b/myosuite/envs/myo/myobase/reorient_sar_v0.py @@ -5,7 +5,8 @@ import collections import numpy as np -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import euler2quat, mulQuat, negQuat, mat2quat diff --git a/myosuite/envs/myo/myobase/walk_v0.py b/myosuite/envs/myo/myobase/walk_v0.py index a95f0d03..82aabd3b 100644 --- a/myosuite/envs/myo/myobase/walk_v0.py +++ b/myosuite/envs/myo/myobase/walk_v0.py @@ -4,7 +4,8 @@ ================================================= """ import collections -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import quat2mat @@ -270,7 +271,7 @@ def get_randomized_initial_state(self): return qpos, qvel def step(self, *args, **kwargs): - obs, reward, done, info = super().step(*args, **kwargs) + obs, reward, done, *_, info = super().step(*args, **kwargs) self.steps += 1 return obs, reward, done, info diff --git a/myosuite/envs/myo/myochallenge/__init__.py b/myosuite/envs/myo/myochallenge/__init__.py index a8bd11bd..19beb7cf 100644 --- a/myosuite/envs/myo/myochallenge/__init__.py +++ b/myosuite/envs/myo/myochallenge/__init__.py @@ -1,5 +1,5 @@ -from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register - +# from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register +from myosuite.utils import gym; register=gym.register import os curr_dir = os.path.dirname(os.path.abspath(__file__)) diff --git a/myosuite/envs/myo/myochallenge/baoding_v1.py b/myosuite/envs/myo/myochallenge/baoding_v1.py index a9cee19b..81053948 100644 --- a/myosuite/envs/myo/myochallenge/baoding_v1.py +++ b/myosuite/envs/myo/myochallenge/baoding_v1.py @@ -5,7 +5,8 @@ import collections import enum -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np from myosuite.envs.myo.base_v0 import BaseV0 diff --git a/myosuite/envs/myo/myochallenge/chasetag_v0.py b/myosuite/envs/myo/myochallenge/chasetag_v0.py index 0dbc460e..3401d4bb 100644 --- a/myosuite/envs/myo/myochallenge/chasetag_v0.py +++ b/myosuite/envs/myo/myochallenge/chasetag_v0.py @@ -4,7 +4,8 @@ ================================================= """ import collections -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np import pink import os diff --git a/myosuite/envs/myo/myochallenge/relocate_v0.py b/myosuite/envs/myo/myochallenge/relocate_v0.py index c38eece5..bb64d19d 100644 --- a/myosuite/envs/myo/myochallenge/relocate_v0.py +++ b/myosuite/envs/myo/myochallenge/relocate_v0.py @@ -5,7 +5,8 @@ import collections import numpy as np -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import mat2euler, euler2quat diff --git a/myosuite/envs/myo/myochallenge/reorient_v0.py b/myosuite/envs/myo/myochallenge/reorient_v0.py index bdb3114e..7e35a3ee 100644 --- a/myosuite/envs/myo/myochallenge/reorient_v0.py +++ b/myosuite/envs/myo/myochallenge/reorient_v0.py @@ -5,7 +5,8 @@ import collections import numpy as np -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs.myo.base_v0 import BaseV0 from myosuite.utils.quat_math import mat2euler, euler2quat diff --git a/myosuite/envs/myo/myodm/__init__.py b/myosuite/envs/myo/myodm/__init__.py index 925b7c45..040de918 100644 --- a/myosuite/envs/myo/myodm/__init__.py +++ b/myosuite/envs/myo/myodm/__init__.py @@ -1,5 +1,5 @@ -from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register - +# from myosuite.utils.import_utils import import_gym; gym = import_gym(); register=gym.register +from myosuite.utils import gym; register=gym.register import collections import os import numpy as np diff --git a/myosuite/envs/myo/myodm/myodm_v0.py b/myosuite/envs/myo/myodm/myodm_v0.py index 1fd48cef..b5738a72 100644 --- a/myosuite/envs/myo/myodm/myodm_v0.py +++ b/myosuite/envs/myo/myodm/myodm_v0.py @@ -5,7 +5,8 @@ License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.envs import env_base from myosuite.logger.reference_motion import ReferenceMotion from myosuite.utils.quat_math import quat2euler, euler2quat, quatDiff2Vel, mat2quat diff --git a/myosuite/logger/examine_logs.py b/myosuite/logger/examine_logs.py index 04dcd8a2..f771fa4f 100644 --- a/myosuite/logger/examine_logs.py +++ b/myosuite/logger/examine_logs.py @@ -17,7 +17,8 @@ from myosuite.utils.paths_utils import plot as plotnsave_paths from myosuite.utils import tensor_utils -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import click import numpy as np import time diff --git a/myosuite/logger/examine_reference.py b/myosuite/logger/examine_reference.py index ba982d96..69b4fed1 100644 --- a/myosuite/logger/examine_reference.py +++ b/myosuite/logger/examine_reference.py @@ -1,5 +1,6 @@ import myosuite -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import time import click from tqdm import tqdm diff --git a/myosuite/tests/test_envs.py b/myosuite/tests/test_envs.py index 7721db32..ef309ac0 100644 --- a/myosuite/tests/test_envs.py +++ b/myosuite/tests/test_envs.py @@ -7,12 +7,26 @@ import unittest -import gym +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym import numpy as np import pickle import copy # import torch.testing - +import os +from flatten_dict import flatten + +def assert_close(prm1, prm2, atol=1e-05, rtol=1e-08): + if prm1 is None and prm2 is None: + return True + elif isinstance(prm1,dict) and isinstance(prm2, dict): + prm1_dict = flatten(prm1) + prm2_dict = flatten(prm2) + for key in prm1_dict.keys(): + assert_close(prm1_dict[key], prm2_dict[key], atol=atol, rtol=rtol) + else: + np.testing.assert_allclose(prm1, prm2, atol=atol, rtol=rtol) + # torch.testing.assert_close(prm1, prm2, atol=atol, rtol=rtol) class TestEnvs(unittest.TestCase): @@ -25,17 +39,25 @@ def check_envs(self, module_name, env_names, lite=False, input_seed=1234): def check_env(self, environment_id, input_seed): + + # Skip tests for envs that requires encoder downloading + ROBOHIVE_TEST = os.getenv('ROBOHIVE_TEST') + if ROBOHIVE_TEST == 'LITE': + if "r3m" in environment_id or "rrl" in environment_id or "vc1" in environment_id: + return + # test init env1 = gym.make(environment_id, seed=input_seed) assert env1.get_input_seed() == input_seed - # test reset - env1.env.reset() + # test reseed and reset + env1.seed(input_seed) + reset_obs1, *_ = env1.env.reset() # step u = 0.01*np.random.uniform(low=0, high=1, size=env1.env.sim.model.nu) # small controls - obs1, rwd1, done1, infos1 = env1.env.step(u.copy()) + obs1, rwd1, done1, *_, infos1 = env1.env.step(u.copy()) infos1 = copy.deepcopy(infos1) #info points to internal variables. - proprio1 = env1.env.get_proprioception() + proprio1_t, proprio1_vec, proprio1_dict = env1.env.get_proprioception() extero1 = env1.env.get_exteroception() assert len(obs1>0) # assert len(rwd1>0) @@ -50,26 +72,31 @@ def check_env(self, environment_id, input_seed): # serialize / deserialize env ------------ env2 = pickle.loads(pickle.dumps(env1)) - # test reset - env2.reset() # test seed assert env2.get_input_seed() == input_seed assert env1.get_input_seed() == env2.get_input_seed(), {env1.get_input_seed(), env2.get_input_seed()} # check input output spaces assert env1.action_space == env2.action_space, (env1.action_space, env2.action_space) assert env1.observation_space == env2.observation_space, (env1.observation_space, env2.observation_space) + + # test reseed and reset + env2.seed(input_seed) + reset_obs2, *_ = env2.env.reset() + assert_close(reset_obs1, reset_obs2) + # step - obs2, rwd2, done2, infos2 = env2.env.step(u) + obs2, rwd2, done2, *_, infos2 = env2.env.step(u) infos2 = copy.deepcopy(infos2) - proprio2 = env2.env.get_proprioception() + proprio2_t, proprio2_vec, proprio2_dict = env2.env.get_proprioception() extero2 = env2.env.get_exteroception() - np.testing.assert_allclose(obs1, obs2) - # np.testing.assert_allclose(proprio1, proprio2) - # np.testing.assert_allclose(extero1, extero2, atol=2, rtol=0.04) - np.testing.assert_allclose(rwd1, rwd2) + + assert_close(obs1, obs2) + assert_close(proprio1_vec, proprio2_vec)#, f"Difference in Proprio: {proprio1_vec-proprio2_vec}" + assert_close(extero1, extero2, atol=2, rtol=0.04)#, f"Difference in Extero {extero1}, {extero2}" + assert_close(rwd1, rwd2)#, "Difference in Rewards" assert (done1==done2), (done1, done2) assert len(infos1)==len(infos2), (infos1, infos2) - # torch.testing.assert_close(infos1, infos2) + assert_close(infos1, infos2) # reset env2.reset() diff --git a/myosuite/tests/test_myo.py b/myosuite/tests/test_myo.py index 36729735..05f46880 100644 --- a/myosuite/tests/test_myo.py +++ b/myosuite/tests/test_myo.py @@ -35,5 +35,24 @@ def test_myodm_envs(self): self.assertEqual(result.exception, None, result.exception) + def no_test_myomimic(self): + env_names=['MyoLegJump-v0', 'MyoLegLunge-v0', 'MyoLegSquat-v0', 'MyoLegLand-v0', 'MyoLegRun-v0', 'MyoLegWalk-v0'] + # Check the envs + self.check_envs('MyoDM', env_names) + + # Check trajectory playback + from myosuite.logger.examine_reference import examine_reference + for env in env_names: + print(f"Testing reference motion playback on: {env}") + runner = click.testing.CliRunner() + result = runner.invoke(examine_reference, ["--env_name", env, \ + "--horizon", -1, \ + "--num_playback", 1, \ + "--render", "none"]) + self.assertEqual(result.exception, None, result.exception) + + if __name__ == '__main__': unittest.main() + + diff --git a/myosuite/tests/test_tutorials.sh b/myosuite/tests/test_tutorials.sh index 45c1dd6c..c9405647 100644 --- a/myosuite/tests/test_tutorials.sh +++ b/myosuite/tests/test_tutorials.sh @@ -14,6 +14,7 @@ pip3 install scikit-learn pip3 install jupyter ipykernel tabulate matplotlib torch h5py pip3 install git+https://github.com/aravindr93/mjrl.git@pvr_beta_1vk # install from branch `pvr_beta_1vk` compatible with `mujoco` native binding pip3 install "stable-baselines3[extra]>=2.0.0a4" +pip3 install deprl python3 -m ipykernel install --user --name=$CONDA_DEFAULT_ENV # Tested tutorials @@ -21,8 +22,10 @@ declare -a StringArray=( "1_Get_Started.ipynb" \ "2_Load_policy.ipynb" \ "3_Analyse_movements.ipynb" \ - # "4_Train_policy.ipynb" \ - # "5_Move_Hand_Fingers.ipynb" \ + "4_Train_policy.ipynb" \ + "4a_deprl.ipynb" \ + # "4c_Train_SB_policy.ipynb" \ + # "5_Move_Hand_Fingers.ipynb" \ ) # Iterate the string array using for loop diff --git a/myosuite/utils/__init__.py b/myosuite/utils/__init__.py index e69de29b..8da0e4ef 100644 --- a/myosuite/utils/__init__.py +++ b/myosuite/utils/__init__.py @@ -0,0 +1,16 @@ +import importlib.util + +if importlib.util.find_spec("gymnasium"): + import gymnasium as gg + print('==>Gymnasium',gg.__version__) +elif importlib.util.find_spec("gym"): + import gym as gg + print('==>Gym',gg.__version__) + +class gym(): pass + +# https://stackoverflow.com/questions/21434332/how-to-extend-inheritance-a-module-in-python +for i in gg.__all__: + setattr(gym, i, getattr(gg, i)) +setattr(gym, '__version__', getattr(gg, '__version__')) + diff --git a/myosuite/utils/examine_env.py b/myosuite/utils/examine_env.py index d457f939..3660442b 100644 --- a/myosuite/utils/examine_env.py +++ b/myosuite/utils/examine_env.py @@ -5,7 +5,8 @@ License :: Under Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ================================================= """ -from myosuite.utils.import_utils import import_gym; gym = import_gym() +# from myosuite.utils.import_utils import import_gym; gym = import_gym() +from myosuite.utils import gym from myosuite.utils.paths_utils import plot as plotnsave_paths import click import numpy as np diff --git a/myosuite/utils/import_utils.py b/myosuite/utils/import_utils.py index ae29b00e..df537f53 100644 --- a/myosuite/utils/import_utils.py +++ b/myosuite/utils/import_utils.py @@ -2,15 +2,26 @@ import importlib.util import os from os.path import expanduser -#import git -def import_gym(): - if importlib.util.find_spec("gymnasium"): - import gymnasium as gg - elif importlib.util.find_spec("gym"): - import gym as gg - return gg +# def import_gym(): +# if importlib.util.find_spec("gymnasium"): +# import gymnasium as gg +# elif importlib.util.find_spec("gym"): +# import gym as gg +# return gg + +# class import_gym(): +# def __init__(self): +# if importlib.util.find_spec("gymnasium"): +# import gymnasium as gg +# elif importlib.util.find_spec("gym"): +# import gym as gg + +# # https://stackoverflow.com/questions/21434332/how-to-extend-inheritance-a-module-in-python +# for i in gg.__all__: +# setattr(import_gym, i, getattr(gg, i)) + def mujoco_py_isavailable(): From e074db6926b76d958c9513f496f34b6108be331e Mon Sep 17 00:00:00 2001 From: Vittorio Caggiano Date: Wed, 13 Dec 2023 07:03:47 -0600 Subject: [PATCH 03/62] rewrite step totally oblivious to the gym version --- myosuite/envs/myo/myobase/walk_v0.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/myosuite/envs/myo/myobase/walk_v0.py b/myosuite/envs/myo/myobase/walk_v0.py index 82aabd3b..946ec3b5 100644 --- a/myosuite/envs/myo/myobase/walk_v0.py +++ b/myosuite/envs/myo/myobase/walk_v0.py @@ -271,10 +271,10 @@ def get_randomized_initial_state(self): return qpos, qvel def step(self, *args, **kwargs): - obs, reward, done, *_, info = super().step(*args, **kwargs) + results = super().step(*args, **kwargs) self.steps += 1 - return obs, reward, done, info - + return results + def reset(self): self.steps = 0 if self.reset_type == 'random': From ad4e66ab67449202a3eeff90c82021594c502846 Mon Sep 17 00:00:00 2001 From: Vittorio Caggiano Date: Wed, 13 Dec 2023 07:29:53 -0600 Subject: [PATCH 04/62] update doc with gym/gymnasium aspecific import --- docs/source/install.rst | 3 +-- docs/source/tutorials.rst | 21 ++++++----------- docs/source/tutorials/ElbowPose_policy.zip | Bin 0 -> 147865 bytes .../myoLeg/checkpoints/step_150000000.pt | Bin 0 -> 6512331 bytes .../myoLegWalk_20230514/myoLeg/config.yaml | 22 ++++++++++++++++++ docs/source/tutorials/videos/MyoSuite.mp4 | Bin 0 -> 45909 bytes docs/source/tutorials/videos/arm.mp4 | Bin 0 -> 77143 bytes docs/source/tutorials/videos/exo_arm.mp4 | Bin 0 -> 199357 bytes docs/source/tutorials/videos/temp.mp4 | Bin 0 -> 76809 bytes 9 files changed, 30 insertions(+), 16 deletions(-) create mode 100644 docs/source/tutorials/ElbowPose_policy.zip create mode 100644 docs/source/tutorials/baselines_DEPRL/myoLegWalk_20230514/myoLeg/checkpoints/step_150000000.pt create mode 100644 docs/source/tutorials/baselines_DEPRL/myoLegWalk_20230514/myoLeg/config.yaml create mode 100644 docs/source/tutorials/videos/MyoSuite.mp4 create mode 100644 docs/source/tutorials/videos/arm.mp4 create mode 100644 docs/source/tutorials/videos/exo_arm.mp4 create mode 100644 docs/source/tutorials/videos/temp.mp4 diff --git a/docs/source/install.rst b/docs/source/install.rst index 7420d1ff..4707cfea 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -60,8 +60,7 @@ For example, to use the ``myoElbowPose1D6MRandom-v0`` environment it is possible .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym env = gym.make('myoElbowPose1D6MRandom-v0') env.reset() for _ in range(1000): diff --git a/docs/source/tutorials.rst b/docs/source/tutorials.rst index 6d405ea4..e9b1237c 100644 --- a/docs/source/tutorials.rst +++ b/docs/source/tutorials.rst @@ -25,8 +25,7 @@ Example on how to use an environment e.g. send random movements .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym env = gym.make('myoElbowPose1D6MRandom-v0') env.reset() for _ in range(1000): @@ -43,8 +42,7 @@ Example on how to generate and visualize a movement e.g. index flexion, and visu .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym env = gym.make('myoHandPoseRandom-v0') env.reset() for _ in range(1000): @@ -60,8 +58,7 @@ Example on using a policy e.g. elbow flexion, and change non-stationaries .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym policy = "iterations/best_policy.pickle" import pickle @@ -83,8 +80,7 @@ This example shows how to add fatigue to a model. It tests random actions on a m .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym env = gym.make('myoElbowPose1D6MRandom-v0') env.reset() for _ in range(1000): @@ -108,8 +104,7 @@ This example shows how to add sarcopenia or muscle weakness to a model. It tests .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym env = gym.make('myoElbowPose1D6MRandom-v0') env.reset() for _ in range(1000): @@ -134,8 +129,7 @@ This example shows how load a model with physical tendon transfer. .. code-block:: python - import myosuite - import gym + from myosuite.utils import gym env = gym.make('myoHandKeyTurnFixed-v0') env.reset() for _ in range(1000): @@ -171,8 +165,7 @@ If you want to load and execute the pre-trained DEP-RL baseline. 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