AdilZouitine
2f3370e42f
Add maniskill support.
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Co-authored-by: Michel Aractingi <michel.aractingi@gmail.com >
2025-02-14 19:53:29 +00:00
Michel Aractingi
7ae368e983
Fixed bug in the action scale of the intervention actions and offline dataset actions. (scale by inverse delta)
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Co-authored-by: Adil Zouitine <adizouitinegm@gmail.com >
2025-02-14 15:17:16 +01:00
Michel Aractingi
36711d766a
Modified crop_dataset_roi interface to automatically write the cropped parameters to a json file in the meta of the dataset
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-14 12:32:45 +01:00
Michel Aractingi
c9e50bb9b1
Optimized the replay buffer from the memory side to store data on cpu instead of a gpu device and send the batches to the gpu.
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 18:03:57 +01:00
Michel Aractingi
95de8e273d
nit
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 17:12:57 +01:00
Michel Aractingi
b07d95f0dd
removed uncomment in actor server
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 16:53:33 +01:00
Michel Aractingi
d9a70376d8
Changed the init_final value to center the starting mean and std of the policy
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 16:42:43 +01:00
Michel Aractingi
0c32008466
Changed bounds for a new so100 robot
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 15:43:30 +01:00
Michel Aractingi
c462a478c7
Hardcoded some normalization parameters. TODO refactor
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Added masking actions on the level of the intervention actions and offline dataset
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 14:27:14 +01:00
Michel Aractingi
459f22ed30
fix log_alpha in modeling_sac: change to nn.parameter
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added pretrained vision model in policy
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 11:26:24 +01:00
Michel Aractingi
dc086dc21f
Added logging for interventions to monitor the rate of interventions through time
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Added an s keyboard command to force success in the case the reward classifier fails
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-13 11:04:49 +01:00
Michel Aractingi
b9217b06db
Added possiblity to record and replay delta actions during teleoperation rather than absolute actions
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-12 19:25:41 +01:00
Yoel
6868c88ef1
[PORT-Hilserl] classifier fixes ( #695 )
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Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co >
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-11 11:39:17 +01:00
Michel Aractingi
a7db3959f5
- Added JointMaskingActionSpace wrapper in gym_manipulator in order to select which joints will be controlled. For example, we can disable the gripper actions for some tasks.
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- Added Nan detection mechanisms in the actor, learner and gym_manipulator for the case where we encounter nans in the loop.
- changed the non-blocking in the `.to(device)` functions to only work for the case of cuda because they were causing nans when running the policy on mps
- Added some joint clipping and limits in the env, robot and policy configs. TODO clean this part and make the limits in one config file only.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-11 11:34:46 +01:00
Michel Aractingi
d51374ce12
Several fixes to move the actor_server and learner_server code from the maniskill environment to the real robot environment.
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-10 16:03:39 +01:00
Eugene Mironov
b63738674c
[HIL-SERL port] Add Reward classifier benchmark tracking to chose best visual encoder ( #688 )
2025-02-06 18:39:51 +01:00
Michel Aractingi
12525242ce
- Added lerobot/scripts/server/gym_manipulator.py that contains all the necessary wrappers to run a gym-style env around the real robot.
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- Added `lerobot/scripts/server/find_joint_limits.py` to test the min and max angles of the motion you wish the robot to explore during RL training.
- Added logic in `manipulator.py` to limit the maximum possible joint angles to allow motion within a predefined joint position range. The limits are specified in the yaml config for each robot. Checkout the so100.yaml.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-06 16:29:37 +01:00
Michel Aractingi
7d5a9530f7
fixed bug in crop_dataset_roi.py
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added missing buffer.pt in server dir
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-05 18:22:50 +00:00
Michel Aractingi
e0527b4a6b
Added additional wrappers for the environment: Action repeat, keyboard interface, reset wrapper
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Tested the reset mechanism and keyboard interface and the convert wrapper on the robots.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-04 17:41:14 +00:00
Michel Aractingi
efb1982eec
Added crop_dataset_roi.py that allows you to load a lerobotdataset -> crop its images -> create a new lerobot dataset with the cropped and resized images.
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 17:48:35 +00:00
Michel Aractingi
2211209be5
- Added base gym env class for the real robot environment.
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- Added several wrappers around the base gym env robot class.
- Including: time limit, reward classifier, crop images, preprocess observations.
- Added an interactive script crop_roi.py where the user can interactively select the roi in the observation images and return the correct crop values that will improve the policy and reward classifier performance.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:59 +00:00
Michel Aractingi
506821c7df
- Refactor observation encoder in modeling_sac.py
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- added `torch.compile` to the actor and learner servers.
- organized imports in `train_sac.py`
- optimized the parameters push by not sending the frozen pre-trained encoder.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
Michel Aractingi
7c89bd1018
Cleaned learner_server.py. Added several block function to improve readability.
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
Michel Aractingi
367dfe51c6
Added support for checkpointing the policy. We can save and load the policy state dict, optimizers state, optimization step and interaction step
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Added functions for converting the replay buffer from and to LeRobotDataset. When we want to save the replay buffer, we convert it first to LeRobotDataset format and save it locally and vice-versa.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
Michel Aractingi
e856ffc91e
Removed unnecessary time.sleep in the streaming server on the learner side
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
Michel Aractingi
42618f4bd6
- Added additional logging information in wandb around the timings of the policy loop and optimization loop.
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- Optimized critic design that improves the performance of the learner loop by a factor of 2
- Cleaned the code and fixed style issues
- Completed the config with actor_learner_config field that contains host-ip and port elemnts that are necessary for the actor-learner servers.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
Michel Aractingi
36576c958f
FREEDOM, added back the optimization loop code in learner_server.py
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Ran experiment with pushcube env from maniskill. The learning seem to work.
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
Michel Aractingi
322a78a378
Added server directory in lerobot/scripts that contains scripts and the protobuf message types to split training into two processes, acting and learning. The actor rollouts the policy and collects interaction data while the learner recieves the data, trains the policy and sends the updated parameters to the actor. The two scripts are ran simultaneously
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Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com >
2025-02-03 15:07:58 +00:00
AdilZouitine
d75b44f89f
Stable version of rlpd + drq
2025-02-03 15:07:57 +00:00
Adil Zouitine
7d2970fdfe
Change SAC policy implementation with configuration and modeling classes
2025-02-03 15:07:50 +00:00
Adil Zouitine
c1d4bf4b63
SAC works
2025-02-03 15:06:18 +00:00
Adil Zouitine
be965019bd
Add rlpd tricks
2025-02-03 15:06:18 +00:00
Adil Zouitine
a0a50de8c9
SAC works
2025-02-03 15:06:18 +00:00
Adil Zouitine
472a7f58ad
[WIP] correct sac implementation
2025-02-03 15:06:14 +00:00
Pradeep Kadubandi
068efce3f8
Fix for the issue https://github.com/huggingface/lerobot/issues/638 ( #639 )
2025-02-03 15:04:03 +00:00
Mishig
100f54ee07
[viz] Fixes & updates to html visualizer ( #617 )
2025-02-03 15:04:03 +00:00
Ville Kuosmanen
a1b5d0faf2
fix(visualise): use correct language description for each episode id ( #604 )
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Co-authored-by: Simon Alibert <75076266+aliberts@users.noreply.github.com >
2025-02-03 15:04:03 +00:00
Mishig
0a4e9e25d0
[vizualizer] for LeRobodDataset V2 ( #576 )
2025-02-03 15:04:02 +00:00
Michel Aractingi
3bb5ed5e91
Extend reward classifier for multiple camera views ( #626 )
2025-01-13 13:57:49 +01:00
Eugene Mironov
c5bca1cf0f
[Port HIL_SERL] Final fixes for the Reward Classifier ( #598 )
2025-01-06 11:34:00 +01:00
Michel Aractingi
35de91ef2b
added temporary fix for missing task_index key in online environment
2024-12-30 13:47:28 +00:00
Michel Aractingi
dc54d357ca
Added normalization schemes and style checks
2024-12-29 12:51:21 +00:00
Michel Aractingi
08ec971086
added optimizer and sac to factory.py
2024-12-23 14:12:03 +01:00
Michel Aractingi
668d493bf9
Update lerobot/scripts/train_hilserl_classifier.py
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Co-authored-by: Yoel <yoel.chornton@gmail.com >
2024-12-17 02:44:31 +07:00
Eugene Mironov
1020bc3108
Fixup
2024-12-17 02:42:53 +07:00
Michel Aractingi
7fcf638c0d
Add human intervention mechanism and eval_robot script to evaluate policy on the robot ( #541 )
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Co-authored-by: Yoel <yoel.chornton@gmail.com >
2024-12-17 02:41:31 +07:00
Yoel
e35546f58e
Reward classifier and training ( #528 )
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Co-authored-by: Daniel Ritchie <daniel@brainwavecollective.ai >
Co-authored-by: resolver101757 <kelster101757@hotmail.com >
Co-authored-by: Jannik Grothusen <56967823+J4nn1K@users.noreply.github.com >
Co-authored-by: Remi <re.cadene@gmail.com >
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co >
2024-12-17 02:41:29 +07:00
Simon Alibert
4c41f6fcc6
Fix example 6 ( #572 )
2024-12-11 10:32:18 +01:00
Michel Aractingi
8e7d6970ea
Control simulated robot with real leader ( #514 )
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Co-authored-by: Remi <remi.cadene@huggingface.co >
2024-12-03 12:20:05 +01:00
Remi
286bca37cc
Fix missing local_files_only in record/replay ( #540 )
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Co-authored-by: Simon Alibert <alibert.sim@gmail.com >
2024-12-03 10:53:21 +01:00