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CALVIN_ABC-D_RUN.md

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Running

Notice

For convenience, some checkpoints, such as the MAE-pretrained ViT-B model, are provided for manual download. Users must update the following paths accordingly. Relevant checkpoints can be acquired from the website.

  • pretrain.sh, finetune.sh, scratch, eval.sh: Please update the following:

    • calvin_dataset_path to the directory where you have stored the CALVIN ABC-D data.
    • save_checkpoint_path to the parent directory where your experiment checkpoints are saved. Recommend to create a checkpoints folder in the project root directory.
    • finetune_from_pretrained_ckpt to the location of your pre-trained checkpoint.
    • resume_from_checkpoint to the location of your fine-tuned checkpoint.
    • vit_checkpoint_path to the location of your ViT checkpoint (downloaded from the website). Recommend to be stored in checkpoints/vit_mae/mae_pretrain_vit_base.pth.
  • networkx: Due to compatibility issues between the networkx library in CALVIN and Python 3.10, we provide a compatible version of networkx.zip on the website. Download and unzip it, then replace the existing networkx library in the following path:

Seer

Pre-train

# Pre-train Seer on Calvin ABC-D dataset
bash scripts/CALVIN_ABC_D/Seer/pretrain.sh
# Pre-train Seer-Large on Calvin ABC-D dataset
bash scripts/CALVIN_ABC_D/Seer-Large/pretrain.sh

Fine-tune

# Fine-tune Seer on Calvin ABC-D dataset
bash scripts/CALVIN_ABC_D/Seer/finetune.sh
# Fine-tune Seer-Large on Calvin ABC-D dataset
bash scripts/CALVIN_ABC_D/Seer-Large/finetune.sh

Train from Scratch

# Train Seer on Calvin ABC-D dataset from scratch
bash scripts/CALVIN_ABC_D/Seer/scratch.sh
# Train Seer-Large on Calvin ABC-D dataset from scratch
bash scripts/CALVIN_ABC_D/Seer-Large/scratch.sh

Eval

# Evaluate Seer on Calvin ABC-D benchmark
bash scripts/CALVIN_ABC_D/Seer/eval.sh
# Evaluate Seer-Large on Calvin ABC-D benchmark
bash scripts/CALVIN_ABC_D/Seer-Large/eval.sh