p-doom/crowd-code-dataset-0.2 huggingface dataset:
[tab] slurm/jobs/mihir/berlin/diffusion/coinrun/ablations/dyn_dit_coinrun_lr_gt_actions.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --job-name=train_dyn_dit

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/dyn/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_checkpoint=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/coinrun_train_tokenizer_mae/32542

srun python jasmine/train_dynamics.py \
    --save_ckpt \
    --image_height=64 \
    --image_width=64 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=36 \
    --max_lr=1e-4 \
    --dyna_type=diffusion \
    --use_gt_actions \
    --num_actions=15 \
    --diffusion_denoise_steps=128 \
    --name=train_dyn_dit_coinrun_lr_1e-4_gt_actions_$slurm_job_id \
    --tags dyn diffusion coinrun lr_1e-4 gt_actions \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
    --tokenizer_type=mae \
    --tokenizer_checkpoint=$tokenizer_checkpoint \
[tab] slurm/jobs/mihir/berlin/diffusion/coinrun/ablations/dyn_dit_coinrun_no_ramp_loss.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --job-name=train_dyn_dit

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/dyn/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_checkpoint=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/coinrun_train_tokenizer_mae/32542


srun python jasmine/train_dynamics.py \
    --save_ckpt \
    --image_height=64 \
    --image_width=64 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=36 \
    --dyna_type=diffusion \
    --diffusion_denoise_steps=128 \
    --name=train_dyn_dit_coinrun_$slurm_job_id \
    --no_diffusion_use_ramp_weight \
    --tags dyn diffusion coinrun \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
    --tokenizer_type=mae \
    --tokenizer_checkpoint=$tokenizer_checkpoint \
[tab] slurm/jobs/mihir/berlin/diffusion/coinrun/dyn_dit_coinrun.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --job-name=train_dyn_dit

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/dyn/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_checkpoint=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/coinrun_train_tokenizer_mae/32542


srun python jasmine/train_dynamics.py \
    --save_ckpt \
    --image_height=64 \
    --image_width=64 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=36 \
    --dyna_type=diffusion \
    --diffusion_denoise_steps=128 \
    --name=train_dyn_dit_coinrun_$slurm_job_id \
    --tags dyn diffusion coinrun \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
    --tokenizer_type=mae \
    --tokenizer_checkpoint=$tokenizer_checkpoint \
[tab] slurm/jobs/mihir/berlin/diffusion/coinrun/dyn_dit_coinrun_lr_1e-4.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --job-name=train_dyn_dit

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/dyn/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_checkpoint=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/coinrun_train_tokenizer_mae/32542

srun python jasmine/train_dynamics.py \
    --save_ckpt \
    --image_height=64 \
    --image_width=64 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=36 \
    --max_lr=1e-4 \
    --dyna_type=diffusion \
    --diffusion_denoise_steps=128 \
    --name=train_dyn_dit_coinrun_lr_1e-4_$slurm_job_id \
    --tags dyn diffusion coinrun lr_1e-4 \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
    --tokenizer_type=mae \
    --tokenizer_checkpoint=$tokenizer_checkpoint \
[tab] slurm/jobs/mihir/berlin/diffusion/breakout/train_tokenizer_mae_dev.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/%x_%j.log
#SBATCH --job-name=train_tokenizer_mae_dev

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_breakout/breakout_episodes_80m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_breakout/breakout_episodes_80m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

export PYTHONUNBUFFERED=1

srun python jasmine/train_tokenizer.py \
    --save_ckpt \
    --image_height=10 \
    --image_width=10 \
    --tokenizer_type=mae \
    --patch_size=4 \
    --val_steps=10 \
    --val_interval=10 \
    --log_image_interval=10 \
    --log_checkpoint_interval=10 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_breakout_dev_$slurm_job_id \
    --tags tokenizer mae breakout \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
[tab] slurm/jobs/mihir/berlin/diffusion/breakout/dyn_dit_breakout_dev.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/dyn/diffusion/%x_%j.log
#SBATCH --job-name=train_dyn_dit

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_breakout/breakout_episodes_80m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_breakout/breakout_episodes_80m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/dyn/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_checkpoint=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/interactive/32627

export PYTHONUNBUFFERED=1

srun python jasmine/train_dynamics.py \
    --save_ckpt \
    --image_height=10 \
    --image_width=10 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=128 \
    --patch_size=4 \
    --log_interval 1 \
    --val_steps 1 \
    --val_interval 10 \
    --log_image_interval 10 \
    --dyna_type=diffusion \
    --diffusion_denoise_steps=32 \
    --no_diffusion_use_ramp_weight \
    --name=train_dyn_dit_breakout_dev \
    --tags dyn diffusion breakout \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
    --tokenizer_type=mae \
    --tokenizer_checkpoint=$tokenizer_checkpoint \
[tab] slurm/jobs/mihir/berlin/diffusion/coinrun/train_tokenizer_mae.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/%x_%j.log
#SBATCH --job-name=coinrun_train_tokenizer_mae

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

srun python jasmine/train_tokenizer.py \
    --save_ckpt \
    --tokenizer_type=mae \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_coinrun_$slurm_job_id \
    --tags tokenizer mae coinrun \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
[tab] slurm/jobs/mihir/berlin/diffusion/doom/train_tokenizer_mae.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=24:00:00
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --mem=100GB
#SBATCH --output=/fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/%x_%j.log
#SBATCH --error=/fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/%x_%j.log
#SBATCH --job-name=coinrun_train_tokenizer_mae

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_coinrun/coinrun_episodes_50m/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/fast/project/HFMI_ProFOUND/mihir/checkpoints/tokenizer/mae/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

srun python jasmine/train_tokenizer.py \
    --save_ckpt \
    --tokenizer_type=mae \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_coinrun_$slurm_job_id \
    --tags tokenizer mae coinrun \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \