p-doom/crowd-code-dataset-0.2 huggingface dataset:
[tab] slurm/jobs/mihir/horeka/yolo-runs/train_dynamics_new_arch_speedrun.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=2
#SBATCH --ntasks-per-node=4
#SBATCH --time=48:00:00
#SBATCH --partition=accelerated
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:4
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/%x_%j.log
#SBATCH --job-name=train_dyn_yolorun_new_arch

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_new/open_ai_minecraft_arrayrecords_chunked

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=$ws_dir/checkpoints/$job_name/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/tokenizer-lr-scaling/train_tokenizer_lr_sweep_1e-4

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --num_steps=1001 \
    --warmup_steps=0 \
    --wsd_decay_steps=0 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=8 \
    --init_lr=1e-3 \
    --max_lr=1e-3 \
    --log_image_interval=100 \
    --log \
    --log_checkpoint_interval=100 \
    --name=dynamics-new-arch-speedrun-new-$slurm_job_id \
    --tags dynamics \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir \
    --dyna_dim=128 \
    --dyna_num_blocks=2 \
    --dyna_num_heads=4
[tab] slurm-3359333.out (plaintext)

============================= JOB FEEDBACK =============================

Job ID: 3359333
Cluster: hk
User/Group: tum_cte0515/hk-project-p0023960
Account: hk-project-p0023960
State: CANCELLED (exit code 0)
Partition: accelerated
Nodes: 1
Cores per node: 6
Nodelist: hkn0734
CPU Utilized: 00:00:00
CPU Efficiency: 0.00% of 00:01:48 core-walltime
Job Wall-clock time: 00:00:18
Starttime: Sat Jul 19 12:34:28 2025
Endtime: Sat Jul 19 12:34:46 2025
Memory Utilized: 0.00 MB (estimated maximum)
Memory Efficiency: 0.00% of 0.00 MB (0.00 MB/node)
[tab] slurm/jobs/mihir/horeka/yolo-runs/train_dynamics_new_arch.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=2
#SBATCH --ntasks-per-node=4
#SBATCH --time=48:00:00
#SBATCH --partition=accelerated
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:4
#SBATCH --output=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/%x_%j.log
#SBATCH --job-name=train_dyn_yolorun_new_arch

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_new/open_ai_minecraft_arrayrecords_chunked

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

CHECKPOINT_DIR=$ws_dir/checkpoints/$job_name/shift-spatial/$slurm_job_id
mkdir -p $CHECKPOINT_DIR

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/tokenizer-lr-scaling/train_tokenizer_lr_sweep_1e-4

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --num_steps=1000 \
    --warmup_steps=0 \
    --wsd_decay_steps=0 \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=8 \
    --init_lr=1e-3 \
    --max_lr=1e-3 \
    --log_image_interval=100 \
    --log \
    --log_checkpoint_interval=100 \
    --name=dynamics-new-arch-speedrun-shift-temporal-$slurm_job_id \
    --tags dynamics \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir \
    --dyna_dim=128 \
    --dyna_num_blocks=2 \
    --dyna_num_heads=4