More training scripts

_ShA-fb-train.sh

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+#!/bin/sh
+#SBATCH -N 1
+#SBATCH -n 1
+#SBATCH --partition=Teach-Standard
+#SBATCH --gres=gpu:4
+#SBATCH --mem=24000
+#SBATCH --time=3-00:00:00
+
+set -e
+
+export CUDA_HOME=/opt/cuda-9.0.176.1/
+export CUDNN_HOME=/opt/cuDNN-7.0/
+export STUDENT_ID=$(whoami)
+
+export LD_LIBRARY_PATH=${CUDNN_HOME}/lib64:${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+export LIBRARY_PATH=${CUDNN_HOME}/lib64:${LIBRARY_PATH}
+export CPATH=${CUDNN_HOME}/include:$CPATH
+export PATH=${CUDA_HOME}/bin:${PATH}
+export PYTHON_PATH=$PATH
+
+mkdir -p /disk/scratch/${STUDENT_ID}
+export TMPDIR=/disk/scratch/${STUDENT_ID}/
+export TMP=/disk/scratch/${STUDENT_ID}/
+
+source /home/${STUDENT_ID}/miniconda3/bin/activate mlp-cuda
+
+python train.py \
+	--pth_tar './pretrained/deit-base-patch16-384/pytorch_model.bin' \
+	--model 'stn' \
+	--save_path ./save/ShanghaiA-fb-stn-$(date -Iminutes) \
+	--batch_size 4 \
+	--gpus 0,1,2,3 \
+	--print_freq 100 \
+	--epochs 1000
+