Configured mnist-runscripts to follow tempate convention.

video_prediction_savp/HPC_scripts/DataPreprocess_to_tf_movingmnist.sh

-#!/bin/bash -x
-#SBATCH --account=deepacf
-#SBATCH --nodes=1
-#SBATCH --ntasks=1
-##SBATCH --ntasks-per-node=1
-#SBATCH --cpus-per-task=1
-#SBATCH --output=DataPreprocess_to_tf-out.%j
-#SBATCH --error=DataPreprocess_to_tf-err.%j
-#SBATCH --time=00:20:00
-#SBATCH --partition=devel
-#SBATCH --mail-type=ALL
-#SBATCH --mail-user=b.gong@fz-juelich.de
-
-
-# Name of virtual environment 
-VIRT_ENV_NAME="vp"
-
-# Loading mouldes
-source ../env_setup/modules_train.sh
-# Activate virtual environment if needed (and possible)
-if [ -z ${VIRTUAL_ENV} ]; then
-   if [[ -f ../${VIRT_ENV_NAME}/bin/activate ]]; then
-      echo "Activating virtual environment..."
-      source ../${VIRT_ENV_NAME}/bin/activate
-   else 
-      echo "ERROR: Requested virtual environment ${VIRT_ENV_NAME} not found..."
-      exit 1
-   fi
-fi
-
-# declare directory-variables which will be modified appropriately during Preprocessing (invoked by mpi_split_data_multi_years.py)
-
-source_dir=/p/project/deepacf/deeprain/video_prediction_shared_folder/preprocessedData/moving_mnist 
-destination_dir=/p/project/deepacf/deeprain/video_prediction_shared_folder/preprocessedData/moving_mnist
-
-# run Preprocessing (step 2 where Tf-records are generated)
-srun python ../video_prediction/datasets/moving_mnist.py ${source_dir} ${destination_dir}/tfrecords