seongun-kim
commented
2 months ago It seems there is an issue related to MuJoCo.
Based on the information you provided, it's difficult to determine why addr, defined in mujoco_py/generated/wrappers.pxi at line 2535, doesn't fall within line 2536-2537.
Can you check whether self.door_angle_idx in sawyer_door_hook.py at line 83 belongs to one of the following types: int, np.int32, or np.int64?
When I run the following command, the error occured： python ./scripts/SawyerDoorHook/vuvc.py ./log --gpu_id 0 --snapshot_gap 20 --seed 0 --spec default
This is the output in terminal: pygame 2.5.2 (SDL 2.28.3, Python 3.6.13) Hello from the pygame community. https://www.pygame.org/contribute.html No personal conf_private.py found. doodad not detected 2024-05-09 19:34:31.871201 Öйú±ê׼ʱ¼ä | Variant: 2024-05-09 19:34:31.871201 Öйú±ê׼ʱ¼ä | { "args": { "env_id": "SawyerDoorHookResetFreeEnv-v1", "base_logdir": "./log", "log_dir": "/{}/vcrllogs/{}/vuvc/{}/seed{}", "render": false, "use_gpu": true, "gpu_id": 0, "snapshot_mode": "gap_and_last", "snapshot_gap": 20, "seed": 0, "spec": "default" }, "skewfit_variant": { "exploration_goal_sampling_mode": "custom_goal_sampler", "evaluation_goal_sampling_mode": "presampled", "custom_goal_sampler": "replay_buffer", "presampled_goals_path": "E:\College\RL\project2\multiworld\envs\mujoco\goals\door_goals.npy", "presample_goals": true }, "qf_kwargs": { "hidden_sizes": [ 400, 300 ] }, "policy_kwargs": { "hidden_sizes": [ 400, 300 ] }, "vae_kwargs": { "representation_size": 16, "decoder_output_activation": "<function identity at 0x000002F0585D1048>", "decoder_distribution": "gaussian_identity_variance", "input_channels": 3, "architecture": { "conv_args": { "kernel_sizes": [ 5, 3, 3 ], "n_channels": [ 16, 32, 64 ], "strides": [ 3, 2, 2 ] }, "conv_kwargs": { "hidden_sizes": [], "batch_norm_conv": false, "batch_norm_fc": false }, "deconv_args": { "hidden_sizes": [], "deconv_input_width": 3, "deconv_input_height": 3, "deconv_input_channels": 64, "deconv_output_kernel_size": 6, "deconv_output_strides": 3, "deconv_output_channels": 3, "kernel_sizes": [ 3, 3 ], "n_channels": [ 32, 16 ], "strides": [ 2, 2 ] }, "deconv_kwargs": { "batch_norm_deconv": false, "batch_norm_fc": false } } }, "replay_buffer_kwargs": { "start_skew_epoch": 10, "max_size": 100000, "fraction_goals_rollout_goals": 0.2, "fraction_goals_env_goals": 0.5, "exploration_rewards_type": "None", "vae_priority_type": "vae_prob", "priority_function_kwargs": { "sampling_method": "importance_sampling", "decoder_distribution": "gaussian_identity_variance", "num_latents_to_sample": 10 }, "power": -0.5, "relabeling_goal_sampling_mode": "custom_goal_sampler", "disagreement_method": "var" }, "sac_trainer_kwargs": { "reward_scale": 1, "discount": 0.99, "soft_target_tau": 0.001, "target_update_period": 1, "use_automatic_entropy_tuning": true }, "vae_trainer_kwargs": { "beta": 20, "lr": 0.001 }, "image_env_kwargs": { "imsize": 48, "init_camera": "<function sawyer_door_env_camera_v0 at 0x000002F0549C4A60>", "transpose": true, "normalize": true, "non_presampled_goal_img_is_garbage": true }, "vae_wrapped_env_kwargs": { "sample_from_true_prior": true, "reward_params": { "type": "latent_distance" } }, "algo_kwargs": { "batch_size": 1024, "num_epochs": 170, "num_eval_steps_per_epoch": 500, "num_expl_steps_per_train_loop": 500, "num_trains_per_train_loop": 1000, "min_num_steps_before_training": 10000, "vae_training_schedule": "<function custom_schedule at 0x000002F058A0AC80>", "oracle_data": false, "vae_save_period": 50, "parallel_vae_train": false, "max_path_length": 100 }, "generate_vae_dataset_kwargs": { "N": 2, "test_p": 0.9, "use_cached": true, "show": false, "oracle_dataset": false, "n_random_steps": 1, "env_id": "SawyerDoorHookResetFreeEnv-v1", "imsize": 48, "init_camera": "<function sawyer_door_env_camera_v0 at 0x000002F0549C4A60>", "non_presampled_goal_img_is_garbage": true } } D:\myDownload\Anaconda3\anaconda3\envs\vcrl\lib\site-packages\gym\envs\registration.py:14: PkgResourcesDeprecationWarning: Parameters to load are deprecated. Call .resolve and .require separately. result = entry_point.load(False)
[SawyerPushAndReachXYEnv] init {'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 10} WARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype. WARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype. WARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype. WARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype. WARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype. Traceback (most recent call last): File "./scripts/SawyerDoorHook/vuvc.py", line 182, in
self.reset()
File "E:\College\RL\project2\multiworld\envs\mujoco\sawyer_xyz\sawyer_door_hook.py", line 177, in reset
ob = self.reset_model()
File "E:\College\RL\project2\multiworld\envs\mujoco\sawyer_xyz\sawyer_door_hook.py", line 173, in reset_model
return self._get_obs()
File "E:\College\RL\project2\multiworld\envs\mujoco\sawyer_xyz\sawyer_door_hook.py", line 110, in _get_obs
angle = self.get_door_angle()
File "E:\College\RL\project2\multiworld\envs\mujoco\sawyer_xyz\sawyer_door_hook.py", line 136, in get_door_angle
return np.array([self.data.get_joint_qpos('doorjoint')])
File "mujoco_py\generated/wrappers.pxi", line 2539, in mujoco_py.cymj.PyMjData.get_joint_qpos
TypeError: 'numpy.intc' object is not iterable
I have followed https://github.com/openai/mujoco-py/compare/master...aaronsnoswell:fix-windows-support to fix this problem, and referred to https://github.com/openai/mujoco-py/issues/324, but it didn't work, can anybody help me with that? I would be appreciate it.