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avisingh599 / reward-learning-rl

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering
https://sites.google.com/view/reward-learning-rl/
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ImportError: cannot import name 'constants' #24

Open Skylark0924 opened 4 years ago

Skylark0924 commented 4 years ago

Excuse me, I am confused about the above problem when I run the code:

softlearning run_example_local examples.classifier_rl --n_goal_examples 10 --t
ask=Image48SawyerDoorPullHookEnv-v0 --algorithm VICERAQ --num-samples 5 --n_epochs 300 --active_query_frequency 10

The whole error log is as follows:

/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/requests/__init__.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
  RequestsDependencyWarning)
Traceback (most recent call last):
  File "main.py", line 11, in <module>
    from softlearning.environments.utils import get_goal_example_environment_from_variant
  File "/home/lab/Github/reward-learning-rl/softlearning/environments/utils.py", line 8, in <module>
    from .adapters.dm_control_adapter import DmControlAdapter
  File "/home/lab/Github/reward-learning-rl/softlearning/environments/adapters/dm_control_adapter.py", line 6, in <module>
    from dm_control import suite
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/suite/__init__.py", line 28, in <module>
    from dm_control.suite import acrobot
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/suite/acrobot.py", line 24, in <module>
    from dm_control import mujoco
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/mujoco/__init__.py", line 18, in <module>
    from dm_control.mujoco.engine import action_spec
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/mujoco/engine.py", line 44, in <module>
    from dm_control.mujoco import index
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/mujoco/index.py", line 92, in <module>
    from dm_control.mujoco.wrapper import util
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/mujoco/wrapper/__init__.py", line 23, in <module>
    from dm_control.mujoco.wrapper import mjbindings
  File "/home/lab/Github/dm_control-0260f3effcfe2b0fdb25d9652dc27ba34b52d226/dm_control/mujoco/wrapper/mjbindings/__init__.py", line 24, in <module>
    from dm_control.mujoco.wrapper.mjbindings import constants
ImportError: cannot import name 'constants'

Actually, I have used all the requirements you mentioned and the version of dm_control is correct. But there is one thing I need to mention is that https://github.com/deepmind/dm_control.git@0260f3effcfe2b0fdb25d9652dc27ba34b52d226 need mujoco200 in its setup.py. So I wonder how you use this version and mujoco150 at the same time.

Thanks a lot!

hartikainen commented 4 years ago

I think the error might be that dm_control is installed with -e flag. Can you try reinstalling without it and see if things start working?

I'm pretty sure this has nothing to do with mujoco version.

Skylark0924 commented 4 years ago

Thank you very much for responding to me so quickly! And what you said is indeed the solution. Now I can run the code, but another mistake comes out. All of the ray workers died or was killed 

(pid=20636) 2019-12-18 11:54:58.253453: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
(pid=20636) 2019-12-18 11:54:58.263643: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3500000000 Hz
(pid=20636) 2019-12-18 11:54:58.265115: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x55585ca51290 executing computations on platform Host. Devices:
(pid=20636) 2019-12-18 11:54:58.265164: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>
(pid=20636) Using seed 8695
(pid=20636) Fatal Python error: Segmentation fault
(pid=20636) 
(pid=20636) Stack (most recent call first):
(pid=20636)   File "/home/lab/Github/multiworld-master/multiworld/envs/mujoco/mujoco_env.py", line 152 in initialize_camera
(pid=20636)   File "/home/lab/Github/multiworld-master/multiworld/core/image_env.py", line 75 in __init__
(pid=20636)   File "/home/lab/Github/multiworld-master/multiworld/envs/mujoco/__init__.py", line 466 in create_image_48_sawyer_door_pull_hook_v0
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/gym/envs/registration.py", line 86 in make
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/gym/envs/registration.py", line 125 in make
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/gym/envs/registration.py", line 183 in make
(pid=20636)   File "/home/lab/Github/reward-learning-rl/softlearning/environments/utils.py", line 48 in get_goal_example_environment_from_variant
(pid=20636)   File "/home/lab/Github/reward-learning-rl/examples/classifier_rl/main.py", line 30 in _build
(pid=20636)   File "/home/lab/Github/reward-learning-rl/examples/development/main.py", line 77 in _train
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/trainable.py", line 151 in train
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/function_manager.py", line 783 in actor_method_executor
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/worker.py", line 887 in _process_task
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/worker.py", line 990 in _wait_for_and_process_task
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/worker.py", line 1039 in main_loop
(pid=20636)   File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/workers/default_worker.py", line 98 in <module>
2019-12-18 11:55:00,107 ERROR trial_runner.py:494 -- Error processing event.
Traceback (most recent call last):
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/trial_runner.py", line 443, in _process_trial
    result = self.trial_executor.fetch_result(trial)
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 315, in fetch_result
    result = ray.get(trial_future[0])
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/worker.py", line 2193, in get
    raise value
ray.exceptions.RayActorError: The actor died unexpectedly before finishing this task.
2019-12-18 11:55:00,109 INFO ray_trial_executor.py:179 -- Destroying actor for trial 4a399b7f-algorithm=VICERAQ-seed=8695. If your trainable is slow to initialize, consider setting reuse_actors=True to reduce actor creation overheads.
2019-12-18 11:55:00,110 ERROR worker.py:1672 -- A worker died or was killed while executing task 000000002ceace92ce444f4ed49ec6617ee3c70c.
== Status ==
Using FIFO scheduling algorithm.
Resources requested: 0/20 CPUs, 0/2 GPUs
Memory usage on this node: 7.6/67.2 GB
Result logdir: /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T11-54-39-2019-12-18T11-54-39
Number of trials: 5 ({'ERROR': 5})
ERROR trials:
 - 337b24bd-algorithm=VICERAQ-seed=5170:    ERROR, 1 failures: /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T11-54-39-2019-12-18T11-54-39/337b24bd-algorithm=VICERAQ-seed=5170_2019-12-18_11-54-39o43g6jsz/error_2019-12-18_11-54-44.txt
 - f0bcf517-algorithm=VICERAQ-seed=6842:    ERROR, 1 failures: /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T11-54-39-2019-12-18T11-54-39/f0bcf517-algorithm=VICERAQ-seed=6842_2019-12-18_11-54-44ccuk2jv5/error_2019-12-18_11-54-48.txt
 - 51db80cc-algorithm=VICERAQ-seed=6234:    ERROR, 1 failures: /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T11-54-39-2019-12-18T11-54-39/51db80cc-algorithm=VICERAQ-seed=6234_2019-12-18_11-54-48rwrncgft/error_2019-12-18_11-54-52.txt
 - f3f442e9-algorithm=VICERAQ-seed=8672:    ERROR, 1 failures: /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T11-54-39-2019-12-18T11-54-39/f3f442e9-algorithm=VICERAQ-seed=8672_2019-12-18_11-54-52jx2r68m6/error_2019-12-18_11-54-56.txt
 - 4a399b7f-algorithm=VICERAQ-seed=8695:    ERROR, 1 failures: /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T11-54-39-2019-12-18T11-54-39/4a399b7f-algorithm=VICERAQ-seed=8695_2019-12-18_11-54-563zft1ykk/error_2019-12-18_11-55-00.txt

Traceback (most recent call last):
  File "/home/lab/anaconda3/envs/softlearning/bin/softlearning", line 11, in <module>
    load_entry_point('softlearning', 'console_scripts', 'softlearning')()
  File "/home/lab/Github/reward-learning-rl/softlearning/scripts/console_scripts.py", line 202, in main
    return cli()
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 764, in __call__
    return self.main(*args, **kwargs)
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 717, in main
    rv = self.invoke(ctx)
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 1137, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 956, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 555, in invoke
    return callback(*args, **kwargs)
  File "/home/lab/Github/reward-learning-rl/softlearning/scripts/console_scripts.py", line 71, in run_example_local_cmd
    return run_example_local(example_module_name, example_argv)
  File "/home/lab/Github/reward-learning-rl/examples/instrument.py", line 228, in run_example_local
    reuse_actors=True)
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/tune.py", line 253, in run
    raise TuneError("Trials did not complete", errored_trials)
ray.tune.error.TuneError: ('Trials did not complete', [337b24bd-algorithm=VICERAQ-seed=5170, f0bcf517-algorithm=VICERAQ-seed=6842, 51db80cc-algorithm=VICERAQ-seed=6234, f3f442e9-algorithm=VICERAQ-seed=8672, 4a399b7f-algorithm=VICERAQ-seed=8695])

So sorry to bother you so much!

hartikainen commented 4 years ago

The main reason for the failure happens is this line:

(pid=20636) Fatal Python error: Segmentation fault

It's unclear where that comes from. Could you try setting a breakpoint (either breakpoint() or import pdb; pdb.set_trace()) somewhere in the beginning of the main function, running the code with the sequential debug mode (softlearning run_example_debug ...), and then stepping through the code to see where it crashes. It's easier to give advice once we know where in code the issue actually happens.

Skylark0924 commented 4 years ago

I found that it is an error caused by ray.tune

/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/experiment.py(115)__init__()->None
-> self.spec = spec
(Pdb) r
> /home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/tune.py(200)run()
-> checkpoint_dir = _find_checkpoint_dir(experiment)
(Pdb) r
2019-12-18 21:24:28,480 INFO tune.py:64 -- Did not find checkpoint file in /home/lab/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-12-18T21-22-34-2019-12-18T21-22-33.
2019-12-18 21:24:28,481 INFO tune.py:211 -- Starting a new experiment.
== Status ==
Using FIFO scheduling algorithm.
Resources requested: 0/20 CPUs, 0/2 GPUs
Memory usage on this node: 8.3/67.2 GB

Using seed 8002
Fatal Python error: Segmentation fault

Stack (most recent call first):
  File "/home/lab/Github/multiworld-master/multiworld/envs/mujoco/mujoco_env.py", line 152 in initialize_camera
  File "/home/lab/Github/multiworld-master/multiworld/core/image_env.py", line 75 in __init__
  File "/home/lab/Github/multiworld-master/multiworld/envs/mujoco/__init__.py", line 466 in create_image_48_sawyer_door_pull_hook_v0
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/gym/envs/registration.py", line 86 in make
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/gym/envs/registration.py", line 125 in make
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/gym/envs/registration.py", line 183 in make
  File "/home/lab/Github/reward-learning-rl/softlearning/environments/utils.py", line 48 in get_goal_example_environment_from_variant
  File "/home/lab/Github/reward-learning-rl/examples/classifier_rl/main.py", line 32 in _build
  File "/home/lab/Github/reward-learning-rl/examples/development/main.py", line 77 in _train
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/trainable.py", line 151 in train
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/actor.py", line 479 in _actor_method_call
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/actor.py", line 138 in _remote
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/actor.py", line 124 in remote
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 111 in _train
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 143 in _start_trial
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 201 in start_trial
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/trial_runner.py", line 271 in step
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/ray/tune/tune.py", line 235 in run
  File "/home/lab/Github/reward-learning-rl/examples/instrument.py", line 237 in run_example_local
  File "/home/lab/Github/reward-learning-rl/examples/instrument.py", line 264 in run_example_debug
  File "/home/lab/Github/reward-learning-rl/softlearning/scripts/console_scripts.py", line 81 in run_example_debug_cmd
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 555 in invoke
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 956 in invoke
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 1137 in invoke
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 717 in main
  File "/home/lab/anaconda3/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 764 in __call__
  File "/home/lab/Github/reward-learning-rl/softlearning/scripts/console_scripts.py", line 202 in main
  File "/home/lab/anaconda3/envs/softlearning/bin/softlearning", line 11 in <module>
Segmentation fault (core dumped)

Is this useful to you?

hartikainen commented 4 years ago

I'm pretty sure it doesn't come from Tune itself, but it looks it does because the code is run through Tune and thus the errors get propagated through it.

Could you try stepping in the main function using pdb and checking where it fails? It's very likely that if fails in the RLAlgorithm.train.

hit618 commented 4 years ago

@Skylark0924 hello! I have the same error (Fatal Python error: Segmentation fault), are you solve it? Could you give me some advice, thank you very much!

Skylark0924 commented 4 years ago

@hit618 Sorry, I couldn't fix it at the end. That might be a problem caused by the firewall and the incomplete install of the env.