p-doom/crowd-code-dataset-0.2 huggingface dataset:
[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=doom_train_tokenizer_mae

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 \
    --image_height=60 \
    --image_width=80 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_$slurm_job_id \
    --tags tokenizer mae doom \
    --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 copy.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=doom_train_tokenizer_mae

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 \
    --image_height=60 \
    --image_width=80 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_$slurm_job_id \
    --tags tokenizer mae doom \
    --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_4_gpu.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=doom_train_tokenizer_mae

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 \
    --image_height=60 \
    --image_width=80 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_$slurm_job_id \
    --tags tokenizer mae doom \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \
[tab] /fast/project/HFMI_ProFOUND/mihir/logs/train/tokenizer/mae/doom_train_tokenizer_mae_2048_32742.log (log)
#!/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=doom_train_tokenizer_mae_2048

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 \
    --image_height=60 \
    --image_width=80 \
    --batch_size=2048 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_2048_$slurm_job_id \
    --tags tokenizer mae doom \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \

wandb: Currently logged in as: mihir-mahajan2002 (instant-uv) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
wandb: setting up run 6r0mvhpu
wandb: Tracking run with wandb version 0.22.1
wandb: Run data is saved locally in /fast/home/mihir.mahajan/Projects/jasmine/wandb/run-20251024_190548-6r0mvhpu
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run train_tokenizer_mae_doom_2048_32742
wandb: ⭐️ View project at https://wandb.ai/instant-uv/jafar
wandb: 🚀 View run at https://wandb.ai/instant-uv/jafar/runs/6r0mvhpu
Running on 1 devices.
Counting all components: ['decoder', 'encoder', 'mask_patch']
Parameter counts:
{'decoder': 17228096, 'encoder': 17228832, 'mask_patch': 768, 'total': 34457696}
[tab] slurm/jobs/mihir/horeka/coinrun/big-model/train_dyn_big_model_no_flash_attn_single_gpu.sh (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=05:00:00
#SBATCH --partition=accelerated-h100
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:1
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/coinrun/dynamics/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/coinrun/dynamics/%x_%j.log
#SBATCH --job-name=train_dyn_no_flash_attn_single_gpu

# Log the sbatch script
cat $0

module unload mpi/openmpi/5.0
module unload devel/cuda/12.4
source .venv/bin/activate

array_records_dir_train=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_coinrun/coinrun_episodes_500m_gt_actions_split/train
array_records_dir_val=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_coinrun/coinrun_episodes_500m_gt_actions_split/val

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/dyn/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_checkpoint=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/tokenizer/interactive/3583033

env | grep SLURM

export JAX_COMPILER_ENABLE_REMAT_PASS=False

srun python jasmine/train_dynamics.py \
    --save_ckpt \
    --image_height=64 \
    --image_width=64 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=8 \
    --num_steps=5000 \
    --wsd_decay_steps=0 \
    --warmup_steps=0 \
    --dyna_dim=2048 \
    --dyna_num_blocks=16 \
    --dyna_num_heads=32 \
    --dyna_ffn_dim=8192 \
    --patch_size=2 \
    --no-use-flash-attention \
    --log \
    --name=coinrun-dyn-big-model-no-flash-attn-single-gpu-bs-8-$slurm_job_id \
    --tags dyn coinrun big-model no-flash-attn single-gpu \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --tokenizer_checkpoint $tokenizer_checkpoint
[tab] slurm/jobs/mihir/berlin/diffusion/doom/train_tokenizer_mae_bs_512.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=doom_train_tokenizer_mae_2048

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 JAX_COMPILER_ENABLE_REMAT_PASS=False

srun python jasmine/train_tokenizer.py \
    --save_ckpt \
    --tokenizer_type=mae \
    --image_height=60 \
    --image_width=80 \
    --batch_size=2048 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_2048_$slurm_job_id \
    --tags tokenizer mae doom \
    --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_bs_512 copy.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=doom_train_tokenizer_mae_2048

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 JAX_COMPILER_ENABLE_REMAT_PASS=False

srun python jasmine/train_tokenizer.py \
    --save_ckpt \
    --tokenizer_type=mae \
    --image_height=60 \
    --image_width=80 \
    --batch_size=2048 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_2048_$slurm_job_id \
    --tags tokenizer mae doom \
    --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_bs_1024.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=doom_train_tokenizer_mae_2048

cat $0

source .venv/bin/activate

array_records_dir_train=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/train
array_records_dir_val=/fast/project/HFMI_ProFOUND/mihir/data/data_doom/doom_episodes_50m_60x80/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 JAX_COMPILER_ENABLE_REMAT_PASS=False

srun python jasmine/train_tokenizer.py \
    --save_ckpt \
    --tokenizer_type=mae \
    --image_height=60 \
    --image_width=80 \
    --batch_size=2048 \
    --ckpt_dir $CHECKPOINT_DIR \
    --name=train_tokenizer_mae_doom_2048_$slurm_job_id \
    --tags tokenizer mae doom \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir_train \
    --val_data_dir $array_records_dir_val \