Instructions to use wsagi/ACT-PickOrange with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use wsagi/ACT-PickOrange with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload train_config.json (v0.4.0 ckpt-18k)
Browse files- train_config.json +12 -25
train_config.json
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@@ -1,7 +1,7 @@
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{
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"dataset": {
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"repo_id": "LightwheelAI/leisaac-pick-orange",
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"root": "/home/david/work/LeIsaac/datasets/raw/leisaac-pick-orange",
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"episodes": null,
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"image_transforms": {
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"enable": false,
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"revision": null,
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"use_imagenet_stats": true,
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"video_backend": "pyav",
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"return_uint8": false,
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"streaming": false
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},
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"env": null,
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},
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"device": "cuda",
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"use_amp": false,
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"use_peft": false,
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"push_to_hub": false,
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"repo_id": null,
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"private": null,
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"tags": null,
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"license": null,
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"pretrained_path":
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"chunk_size": 100,
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"n_action_steps": 100,
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"normalization_mapping": {
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},
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"vision_backbone": "resnet18",
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"pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
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"replace_final_stride_with_dilation":
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"pre_norm": false,
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"dim_model": 512,
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"n_heads": 8,
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"optimizer_weight_decay": 0.0001,
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"optimizer_lr_backbone": 1e-05
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},
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"output_dir": "
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"job_name": "act-
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"resume":
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"seed": 1000,
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"cudnn_deterministic": false,
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"num_workers": 4,
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"batch_size": 8,
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"
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"persistent_workers": true,
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"steps": 10000,
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"eval_freq": 20000,
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"log_freq": 200,
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"tolerance_s": 0.0001,
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"save_checkpoint": true,
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"save_freq": 2000,
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"use_policy_training_preset": true,
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"scheduler": null,
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"eval": {
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"n_episodes": 50,
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"batch_size":
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"use_async_envs":
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},
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"wandb": {
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"enable": false,
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"entity": null,
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"notes": null,
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"run_id": null,
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"mode": null
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"add_tags": true
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},
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"
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"
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"rabc_progress_path": null,
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"rabc_kappa": 0.01,
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"rabc_epsilon": 1e-06,
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"rabc_head_mode": "sparse",
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"rename_map": {},
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"checkpoint_path": null
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}
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{
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"dataset": {
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"repo_id": "LightwheelAI/leisaac-pick-orange",
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"root": "/home/david/work/isaaclab-experience/LeIsaac/datasets/raw/leisaac-pick-orange",
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"episodes": null,
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"image_transforms": {
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"enable": false,
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"revision": null,
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"use_imagenet_stats": true,
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"video_backend": "pyav",
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"streaming": false
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},
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"env": null,
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},
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"device": "cuda",
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"use_amp": false,
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"push_to_hub": false,
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"repo_id": null,
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"private": null,
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"tags": null,
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"license": null,
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"pretrained_path": "LeIsaac/outputs/act-v040-baseline/checkpoints/last/pretrained_model",
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"chunk_size": 100,
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"n_action_steps": 100,
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"normalization_mapping": {
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},
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"vision_backbone": "resnet18",
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"pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
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"replace_final_stride_with_dilation": 0,
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"pre_norm": false,
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"dim_model": 512,
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"n_heads": 8,
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"optimizer_weight_decay": 0.0001,
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"optimizer_lr_backbone": 1e-05
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},
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"output_dir": "LeIsaac/outputs/act-v040-baseline",
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"job_name": "act-v040-baseline",
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"resume": true,
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"seed": 1000,
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"num_workers": 4,
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"batch_size": 8,
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"steps": 20000,
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"eval_freq": 20000,
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"log_freq": 200,
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"save_checkpoint": true,
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"save_freq": 2000,
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"use_policy_training_preset": true,
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"scheduler": null,
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"eval": {
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"n_episodes": 50,
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"batch_size": 50,
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"use_async_envs": false
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},
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"wandb": {
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"enable": false,
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"entity": null,
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"notes": null,
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"run_id": null,
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"mode": null
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},
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"checkpoint_path": "LeIsaac/outputs/act-v040-baseline/checkpoints/last",
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"rename_map": {}
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}
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