p-doom/crowd-code-dataset-0.2 huggingface dataset:
[tab] data/eval/handcrafted/git_push_complex.md (markdown)
# Assistant
``` bash
ls -la
```

# User
<stdout>
total 712
drwxr-xr-x  10 mihir.mahajan mihir.mahajan    361 Oct 28 20:10 .
drwxr-xr-x  14 mihir.mahajan mihir.mahajan    441 Nov 28 12:49 ..
drwxr-xr-x   5 mihir.mahajan mihir.mahajan    166 Oct 20 09:39 data
drwxr-xr-x   4 mihir.mahajan mihir.mahajan     52 Oct 29 11:50 gifs
drwxr-xr-x   8 mihir.mahajan mihir.mahajan    354 Oct 29 11:45 .git
-rw-r--r--   1 mihir.mahajan mihir.mahajan     68 Oct  7 14:57 .gitignore
drwxr-xr-x   6 mihir.mahajan mihir.mahajan    364 Oct 28 20:10 jasmine
-rw-r--r--   1 mihir.mahajan mihir.mahajan  11357 Oct  7 14:57 LICENSE
-rw-r--r--   1 mihir.mahajan mihir.mahajan     90 Oct  7 14:57 .pre-commit-config.yaml
-rw-r--r--   1 mihir.mahajan mihir.mahajan    435 Oct  7 14:57 pyproject.toml
-rw-r--r--   1 mihir.mahajan mihir.mahajan  10143 Oct 28 20:10 README.md
drwxr-xr-x   8 mihir.mahajan mihir.mahajan    166 Oct  7 14:57 slurm
drwxr-xr-x   3 mihir.mahajan mihir.mahajan     58 Oct  7 14:57 tests
-rw-r--r--   1 mihir.mahajan mihir.mahajan 253777 Oct  7 15:05 uv.lock
drwxr-xr-x   5 mihir.mahajan mihir.mahajan    197 Oct  7 17:55 .venv
drwxr-xr-x 110 mihir.mahajan mihir.mahajan   5104 Oct 29 10:40 wandb
</stdout>

# Assistant
``` bash
git status
```

# User
<stdout>
On branch chore/refactor-diffusion-branch
Your branch is up to date with 'origin/chore/refactor-diffusion-branch'.

Changes not staged for commit:
  (use "git add <file>..." to update what will be committed)
  (use "git restore <file>..." to discard changes in working directory)
        modified:   jasmine/baselines/diffusion/sample_diffusion.py
        modified:   jasmine/baselines/maskgit/sample_maskgit.py

Untracked files:
  (use "git add <file>..." to include in what will be committed)
        data/uv.lock
        slurm/
        uv.lock

no changes added to commit (use "git add" and/or "git commit -a")
</stdout>

# Assistant
```bash
git commit -am "Added sampling scripts for diffusion and maskgit baselines"
```

# User
<stdout>
black....................................................................Failed
- hook id: black
- files were modified by this hook

reformatted jasmine/baselines/diffusion/sample_diffusion.py
reformatted jasmine/baselines/maskgit/sample_maskgit.py

All done! ✨ 🍰 ✨
2 files reformatted.
</stdout>

# Assistant
```bash
git commit -am "Added sampling scripts for diffusion and maskgit baselines"
```

# User
<stdout>
black....................................................................Passed
[chore/refactor-diffusion-branch cf058bf] Added sampling scripts for diffusion and maskgit baselines
 2 files changed, 72 insertions(+)!
</stdout>

# Assistant
```bash
gi tpush
```

# User
<stdout>
bash: gi: command not found
</stdout>

# Assistant
```bash
git push
```



# Assistant
```bash
echo COMPLETE_TASK_AND_SUBMIT_FINAL_OUTPUT
```
[tab] /home/mihir.mahajan/Projects/jasmine/slurm/jobs/mihir/horeka/batchsize_scaling/tokenizer/sqrt_lr/train_tokenizer_1_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=4
#SBATCH --time=36:00:00
#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_tokenizer_batch_size_scaling_1_node

# 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/10fps_160x90

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

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

env | grep SLURM

srun python jasmine/train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=48 \
    --min_lr=0 \
    --max_lr=1e-4 \
    --log_image_interval=1000 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=tokenizer-batch-size-scaling-1-node-sqrt-lr-$slurm_job_id \
    --tags tokenizer batch-size-scaling 1-node sqrt-lr \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir
[tab] /home/mihir.mahajan/Projects/jasmine/slurm/jobs/mihir/horeka/batchsize_scaling/tokenizer/sqrt_lr/train_tokenizer_2_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=2
#SBATCH --ntasks-per-node=4
#SBATCH --time=36:00:00
#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_tokenizer_batch_size_scaling_2_node

# 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/10fps_160x90
array_records_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data_new/open_ai_minecraft_arrayrecords_chunked_subset

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

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

env | grep SLURM

srun python jasmine/train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.4e-4 \
    --log_image_interval=1000 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=tokenizer-batch-size-scaling-2-node-sqrt-lr-$slurm_job_id \
    --tags tokenizer batch-size-scaling 2-node sqrt-lr-scaling \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir
[tab] /home/mihir.mahajan/Projects/jasmine/slurm/jobs/mihir/horeka/batchsize_scaling/tokenizer/sqrt_lr/train_tokenizer_4_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=4
#SBATCH --ntasks-per-node=4
#SBATCH --time=36:00:00
#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_tokenizer_batch_size_scaling_4_node

# 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/10fps_160x90

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

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

env | grep SLURM

srun python jasmine/train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=192 \
    --min_lr=0 \
    --max_lr=2.00e-4 \
    --log_image_interval=1000 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=tokenizer-batch-size-scaling-4-node-sqrt-lr-$slurm_job_id \
    --tags tokenizer batch-size-scaling 4-node sqrt-lr \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir
[tab] /home/mihir.mahajan/Projects/jasmine/slurm/jobs/mihir/horeka/batchsize_scaling/tokenizer/sqrt_lr/train_tokenizer_8_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=8
#SBATCH --ntasks-per-node=4
#SBATCH --time=36:00:00
#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_tokenizer_batch_size_scaling_8_node

# 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/10fps_160x90

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

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

env | grep SLURM

srun python jasmine/train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=384 \
    --min_lr=0 \
    --max_lr=3e-4 \
    --log_image_interval=1000 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=tokenizer-batch-size-scaling-8-node-sqrt-lr-$slurm_job_id \
    --tags tokenizer batch-size-scaling 8-node sqrt-lr-scaling \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir
[tab] /home/mihir.mahajan/Projects/jasmine/slurm/jobs/mihir/horeka/batchsize_scaling/tokenizer/sqrt_lr/train_tokenizer_16_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=16
#SBATCH --ntasks-per-node=4
#SBATCH --time=36:00:00
#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_tokenizer_batch_size_scaling_16_node

# 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/10fps_160x90

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

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

env | grep SLURM

srun python jasmine/train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=768 \
    --min_lr=0 \
    --max_lr=4e-4 \
    --log_image_interval=1000 \
    --log_checkpoint_interval=1000 \
    --log \
    --name=tokenizer-batch-size-scaling-16-node-sqrt-lr-$slurm_job_id \
    --tags tokenizer batch-size-scaling 16-node sqrt-lr-scaling \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir
[tab] /home/mihir.mahajan/Projects/jasmine/slurm/jobs/mihir/horeka/batchsize_scaling/tokenizer/sqrt_lr/train_tokenizer_32_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=32
#SBATCH --ntasks-per-node=4
#SBATCH --time=05:00:00
#SBATCH --partition=accelerated
#SBATCH --cpus-per-task=5
#SBATCH --gres=gpu:4
#SBATCH --output=logs/logs_training/%x_%j.log
#SBATCH --error=logs/logs_training/%x_%j.log
#SBATCH --job-name=train_tokenizer_batch_size_scaling_32_node

# 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/10fps_160x90

job_name=$SLURM_JOB_NAME
slurm_job_id=$SLURM_JOB_ID

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

env | grep SLURM

srun python jasmine/train_tokenizer.py \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=1536 \
    --min_lr=3e-4 \
    --max_lr=3e-4 \
    --log_image_interval=250 \
    --log \
    --name=tokenizer-batch-size-scaling-32-node-sqrt-lr-$slurm_job_id \
    --tags tokenizer batch-size-scaling 32-node sqrt-lr-scaling \
    --entity instant-uv \
    --project jafar \
    --data_dir $array_records_dir