Remove sbatch*.sh
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@ -11,6 +11,9 @@ rl
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nautilus/*.yaml
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*.key
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# Slurm
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sbatch*.sh
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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25
sbatch.sh
25
sbatch.sh
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@ -1,25 +0,0 @@
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#!/bin/bash
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#SBATCH --nodes=1 # total number of nodes (N to be defined)
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#SBATCH --ntasks-per-node=1 # number of tasks per node (here 8 tasks, or 1 task per GPU)
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#SBATCH --gres=gpu:1 # number of GPUs reserved per node (here 8, or all the GPUs)
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#SBATCH --cpus-per-task=8 # number of cores per task (8x8 = 64 cores, or all the cores)
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#SBATCH --time=2-00:00:00
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#SBATCH --output=/home/rcadene/slurm/%j.out
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#SBATCH --error=/home/rcadene/slurm/%j.err
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#SBATCH --qos=low
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#SBATCH --mail-user=re.cadene@gmail.com
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#SBATCH --mail-type=ALL
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CMD=$@
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echo "command: $CMD"
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apptainer exec --nv \
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~/apptainer/nvidia_cuda:12.2.2-devel-ubuntu22.04.sif $SHELL
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source ~/.bashrc
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#conda activate fowm
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conda activate lerobot
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export DATA_DIR="data"
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srun $CMD
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@ -1,17 +0,0 @@
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#!/bin/bash
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#SBATCH --nodes=1 # total number of nodes (N to be defined)
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#SBATCH --ntasks-per-node=1 # number of tasks per node (here 8 tasks, or 1 task per GPU)
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#SBATCH --qos=normal # number of GPUs reserved per node (here 8, or all the GPUs)
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#SBATCH --partition=hopper-prod
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#SBATCH --gres=gpu:1 # number of GPUs reserved per node (here 8, or all the GPUs)
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#SBATCH --cpus-per-task=12 # number of cores per task
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#SBATCH --mem-per-cpu=11G
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#SBATCH --time=12:00:00
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#SBATCH --output=/admin/home/remi_cadene/slurm/%j.out
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#SBATCH --error=/admin/home/remi_cadene/slurm/%j.err
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#SBATCH --mail-user=remi_cadene@huggingface.co
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#SBATCH --mail-type=ALL
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CMD=$@
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echo "command: $CMD"
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srun $CMD
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