forked from tangger/lerobot
chore(docs): update instructions for change in device and use_amp (#843)
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@@ -135,14 +135,14 @@ python lerobot/scripts/train.py \
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--policy.type=act \
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--output_dir=outputs/train/act_aloha_test \
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--job_name=act_aloha_test \
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--device=cuda \
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--policy.device=cuda \
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--wandb.enable=true
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```
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Let's explain it:
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1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/aloha_test`.
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2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
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4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
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4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
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5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
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For more information on the `train` script see the previous tutorial: [`examples/4_train_policy_with_script.md`](../examples/4_train_policy_with_script.md)
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