p-doom/crowd-code-dataset-0.2 huggingface dataset:
[tab] weekend-job-starter.sh (shellscript)
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_12_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_20_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_50_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_6_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_8_actions.sbatch



sbatch slurm/jobs/mihir/horeka/lr_tuning/tokenizer/train_tokenizer_lr_1e-4.sbatch
sbatch slurm/jobs/mihir/horeka/lr_tuning/tokenizer/train_tokenizer_lr_5e-5.sbatch


sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_16_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_1_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_2_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_4_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_8_nodes.sbatch


sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/1_train_dyn_36M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/2_train_dyn_110M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/3_train_dyn_180M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/4_train_dyn_270M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/5_train_dyn_500M.sbatch
[tab] slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_1_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=1
#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/big-runs/dynamics-cotraining-batchsize-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-batchsize-scaling/%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_chunked

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/dynamics-cotraining-batchsize-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=48 \
    --min_lr=0 \
    --max_lr=1e-5 \
    --log_image_interval=1000 \
    --log \
    --log_checkpoint_interval=1000 \
    --name=dynamics-batch-size-scaling-1-node-$slurm_job_id \
    --tags dynamics batch-size-scaling 1-node \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_4_nodes.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=4
#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/big-runs/dynamics-cotraining-batchsize-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-batchsize-scaling/%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_chunked

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/dynamics-cotraining-batchsize-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=192 \
    --min_lr=0 \
    --max_lr=2.1e-5 \
    --log_image_interval=1000 \
    --log \
    --log_checkpoint_interval=1000 \
    --name=dynamics-batch-size-scaling-4-node-$slurm_job_id \
    --tags dynamics batch-size-scaling 4-node \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_6_actions.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/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --job-name=dynamics_cotraining_action_space_scaling_6

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/dynamics-cotraining-actionspace-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.5e-5 \
    --log_image_interval=1000 \
    --log \
    --num_latent_actions=6 \
    --log_checkpoint_interval=1000 \
    --name=dynamics-cotraining-action-space-scaling-6-$slurm_job_id \
    --tags dynamics cotraining action-space-scaling 6 \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_8_actions.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/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --job-name=dynamics_cotraining_action_space_scaling_8

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/dynamics-cotraining-actionspace-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.5e-5 \
    --log_image_interval=1000 \
    --log \
    --num_latent_actions=8 \
    --log_checkpoint_interval=1000 \
    --name=dynamics-cotraining-action-space-scaling-8-$slurm_job_id \
    --tags dynamics cotraining action-space-scaling 8 \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_12_actions.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/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --job-name=dynamics_cotraining_action_space_scaling_12

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/dynamics-cotraining-actionspace-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.5e-5 \
    --log_image_interval=1000 \
    --log \
    --num_latent_actions=12 \
    --log_checkpoint_interval=1000 \
    --name=dynamics-cotraining-action-space-scaling-12-$slurm_job_id \
    --tags dynamics cotraining action-space-scaling 12 \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_20_actions.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/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --job-name=dynamics_cotraining_action_space_scaling_20

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/dynamics-cotraining-actionspace-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.5e-5 \
    --log_image_interval=1000 \
    --log \
    --num_latent_actions=20 \
    --log_checkpoint_interval=1000 \
    --name=dynamics-cotraining-action-space-scaling-20-$slurm_job_id \
    --tags dynamics cotraining action-space-scaling 20 \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_50_actions.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/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-actionspace-scaling/%x_%j.log
#SBATCH --job-name=dynamics_cotraining_action_space_scaling_50

# 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=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/big-runs/dynamics-cotraining-actionspace-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

env | grep SLURM

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.5e-5 \
    --log_image_interval=1000 \
    --log \
    --num_latent_actions=50 \
    --log_checkpoint_interval=1000 \
    --name=dynamics-cotraining-action-space-scaling-50-$slurm_job_id \
    --tags dynamics cotraining action-space-scaling 50 \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir
[tab] slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/2_train_dyn_110M.sbatch (shellscript)
#!/usr/bin/env bash

#SBATCH --nodes=6
#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/big-runs/dynamics-cotraining-modelsize-scaling/%x_%j.log
#SBATCH --error=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/logs/logs_mihir/big-runs/dynamics-cotraining-modelsize-scaling/%x_%j.log
#SBATCH --job-name=train_dynamics_modelsize_scaling_110M_6_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_chunked

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/dynamics-cotraining-modelsize-scaling/$job_name
mkdir -p $CHECKPOINT_DIR

tokenizer_ckpt_dir=/hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/checkpoints/train_tokenizer_batch_size_scaling_16_node/3321526/tokenizer_22000/

env | grep SLURM

srun python train_dynamics.py \
    --save_ckpt \
    --ckpt_dir $CHECKPOINT_DIR \
    --batch_size=96 \
    --min_lr=0 \
    --max_lr=1.5e-5 \
    --log_image_interval=1000 \
    --log \
    --log_checkpoint_interval=1000 \
    --name=dynamics-modelsize-scaling-110M-$slurm_job_id \
    --tags dynamics modelsize-scaling 110M \
    --entity instant-uv \
    --project jafar \
    --tokenizer_checkpoint=$tokenizer_ckpt_dir \
    --data_dir $array_records_dir \
    --dyna_dim=768 \
    --dyna_num_blocks=16 \
    --dyna_num_heads=12
[tab] weekend-job-requeuer.sh (shellscript)
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_12_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_20_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_50_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_6_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_8_actions.sbatch



sbatch slurm/jobs/mihir/horeka/lr_tuning/tokenizer/train_tokenizer_lr_1e-4.sbatch
sbatch slurm/jobs/mihir/horeka/lr_tuning/tokenizer/train_tokenizer_lr_5e-5.sbatch


sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_16_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_1_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_2_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_4_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_8_nodes.sbatch


sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/1_train_dyn_36M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/2_train_dyn_110M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/3_train_dyn_180M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/4_train_dyn_270M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/5_train_dyn_500M.sbatch
[content] weekend-job-requeuer.sh (shellscript)
echo "requeueing modelsize scaling runs"
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/1_train_dyn_36M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/2_train_dyn_110M.sbatch
sbatch slurm/jobs/mihir/horeka/modelsize_scaling/dynamics/3_train_dyn_180M.sbatch
[content] weekend-job-requeuer.sh (shellscript)
echo "requeueing batchsize scaling runs: [4,16]nodes"
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_16_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_4_nodes.sbatch
[content] weekend-job-requeuer.sh (shellscript)
echo "requeueing batchsize scaling runs: [1,2]nodes"
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_1_nodes.sbatch
sbatch slurm/jobs/mihir/horeka/batchsize_scaling/dynamics_cotraining/sqrt_lr/train_dynamics_2_nodes.sbatch
[content] weekend-job-requeuer.sh (shellscript)
echo "requeueing actionspace scaling jobs"
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_12_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_20_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_50_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_6_actions.sbatch
sbatch slurm/jobs/mihir/horeka/action_space_scaling/co_training/train_dynamics_cotraining_8_actions.sbatch