p-doom/crowd-code-dataset-0.2 huggingface dataset:
[content] train_dynamics.py (python)
+        wandb.init(
+            entity=args.entity,
+            project=args.project,
+            group="debug",
+            config=args,
+            name=args.name,
+            tags=args.tags,
+        )
[content] train_lam.py (python)
+        wandb.init(
+            entity=args.entity,
+            project=args.project,
+            group="debug",
+            config=args,
+            name=args.name,
+            tags=args.tags,
+        )
[content] train_tokenizer.py (python)
+        wandb.init(
+            entity=args.entity,
+            project=args.project,
+            group="debug",
+            config=args,
+            name=args.name,
+            tags=args.tags,
+        )
[content] train_tokenizer.py (python)
        if args.wandb_id:
            wandb_init_kwargs.update(
                {
                    "id": args.wandb_id,
                    "resume": "allow",
                }
            )
        wandb.init(**wandb_init_kwargs)
[content] train_tokenizer.py (python)
        wandb_init_kwargs = {
            "entity": args.entity,
            "project": args.project,
            "name": args.name,
            "tags": args.tags,
            "group": "debug",
            "config": args,
        }
[content] train_tokenizer.py (python)
        wandb.init(
            entity=args.entity,
            project=args.project,
            group="debug",
            config=args,
            name=args.name,
            tags=args.tags,
        )
[content] train_lam.py (python)
        wandb_init_kwargs = {
            "entity": args.entity,
            "project": args.project,
            "name": args.name,
            "tags": args.tags,
            "group": "debug",
            "config": args,
        }
        if args.wandb_id:
            wandb_init_kwargs.update(
                {
                    "id": args.wandb_id,
                    "resume": "allow",
                }
            )
        wandb.init(**wandb_init_kwargs)
[content] train_dynamics.py (python)
        wandb_init_kwargs = {
            "entity": args.entity,
            "project": args.project,
            "name": args.name,
            "tags": args.tags,
            "group": "debug",
            "config": args,
        }
        if args.wandb_id:
            wandb_init_kwargs.update(
                {
                    "id": args.wandb_id,
                    "resume": "allow",
                }
            )
        wandb.init(**wandb_init_kwargs)
[tab] slurm/jobs/mihir/horeka/jafar_og_reproduction/og_coinrun_lam_reproduction.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=2-00:00:00
#SBATCH --cpus-per-task=8
#SBATCH --gres=gpu:1
#SBATCH --partition=accelerated
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/jafar_og_reproduction/lam/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/jafar_og_reproduction/lam/%x_%j.log
#SBATCH --job-name=train_lam_coinrun_og_reproduction

# Log the sbatch script
cat $0

source .venv/bin/activate

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

tags="coinrun_og reproduction 10m_dataset lam repro_mihir"

npy_records_dir="/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_coinrun/coinrun_episodes_10m"

CHECKPOINT_DIR="/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/mihir/jafar_og_reproduction/lam/$job_name/$slurm_job_id"
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

srun python train_lam.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --log_image_interval=1000 \
    --log \
    --name="${job_name}_${slurm_job_id}" \
    --tags $tags \
    --entity instant-uv \
    --project jafar \
    --data_dir $npy_records_dir
[tab] slurm/jobs/mihir/horeka/jafar_og_reproduction/og_coinrun_tokenizer_repoduction.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=2-00:00:00
#SBATCH --cpus-per-task=8
#SBATCH --gres=gpu:1
#SBATCH --partition=accelerated
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/jafar_og_reproduction/tokenizer/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/jafar_og_reproduction/tokenizer/%x_%j.log
#SBATCH --job-name=train_tokenizer_coinrun_og_reproduction

# Log the sbatch script
cat $0

source .venv/bin/activate

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

tags="coinrun_og reproduction 10m_dataset tokenizer repro_mihir"

npy_records_dir="/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_coinrun/coinrun_episodes_10m"

CHECKPOINT_DIR="/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/mihir/jafar_og_reproduction/tokenizer/$job_name/$slurm_job_id"

mkdir -p $CHECKPOINT_DIR

env | grep SLURM

srun python train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --log_image_interval=1000 \
    --patch_size=16 \
    --log \
    --name="${job_name}_${slurm_job_id}" \
    --tags $tags \
    --entity instant-uv \
    --project jafar \
    --data_dir $npy_records_dir
[tab] slurm/jobs/mihir/horeka/jafar_og_reproduction/og_coinrun_dynamics_reproduction.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=2-00:00:00
#SBATCH --cpus-per-task=8
#SBATCH --gres=gpu:1
#SBATCH --partition=accelerated
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/jafar_og_reproduction/dynamics/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/jafar_og_reproduction/dynamics/%x_%j.log
#SBATCH --job-name=train_dynamics_coinrun_og_reproduction

# Log the sbatch script
cat $0

source .venv/bin/activate

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

tags="coinrun_og dynanmics 10m_dataset repro_mihir"

npy_records_dir="/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_coinrun/coinrun_episodes_10m"

# TODO mihir: update the tokenizer and lam checkpoints
tokenizer_ckpt_dir=""
lam_ckpt_dir=""

CHECKPOINT_DIR="/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/mihir/jafar_og_reproduction/dynamics/${job_name}/${slurm_job_id}"
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

srun python train_dynamics.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --tokenizer_checkpoint="${tokenizer_ckpt_dir}" \
    --lam_checkpoint="${lam_ckpt_dir}" \
    --log_image_interval=1000 \
    --log \
    --name="${job_name}_${slurm_job_id}" \
    --tags ${tags} \
    --entity instant-uv \
    --project jafar \
    --data_dir $npy_records_dir