Fix training issue

HPC_scripts/train_era5.sh

@@ -6,9 +6,9 @@
 #SBATCH --cpus-per-task=1
 #SBATCH --output=train_era5-out.%j
 #SBATCH --error=train_era5-err.%j
-#SBATCH --time=23:20:00
+#SBATCH --time=00:20:00
 #SBATCH --gres=gpu:1
-#SBATCH --partition=gpus
+#SBATCH --partition=develgpus
 #SBATCH --mail-type=ALL
 #SBATCH --mail-user=b.gong@fz-juelich.de
 ##jutil env activate -p cjjsc42
@@ -24,5 +24,5 @@ module load cuDNN/7.5.1.10-CUDA-10.1.105
 
 #srun  python scripts/train.py --input_dir data/kth --dataset kth  --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir logs/kth/ours_savp
 
-srun python ../scripts/train_v2.py --input_dir ../data/era5_size_64_64_3_3t_norm --dataset era5  --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir ../logs/era5_size_64_64_3_3t_norm/ours_savp
+srun python ../scripts/train_v2.py --input_dir ../data/era5_size_64_64_3_3t_norm --dataset era5  --model savp --model_hparams_dict ../hparams/kth/ours_savp/model_hparams.json --output_dir ../logs/era5_size_64_64_3_3t_norm/ours_savp
 #srun  python scripts/train.py --input_dir data/era5 --dataset era5  --model savp --model_hparams_dict hparams/kth/ours_savp/model_hparams.json --output_dir logs/era5/ours_savp

env_setup/requirements.txt

@@ -2,4 +2,3 @@ opencv-python
 scipy
 scikit-image
 pandas
-netCDF4

scripts/generate_transfer_learning_finetune.py

@@ -4,17 +4,30 @@ from __future__ import print_function
 
 import argparse
 import errno
+import json
 import os
 import math
+import random
+import cv2
+import numpy as np
 import tensorflow as tf
+import pickle
+from random import seed
 import random
 import json
 import numpy as np
+#from six.moves import cPickle
 import matplotlib
 matplotlib.use('Agg')
 import matplotlib.pyplot as plt
 import matplotlib.gridspec as gridspec
+import matplotlib.animation as animation
+import pandas as pd
+import re
 from video_prediction import datasets, models
+from matplotlib.colors import LinearSegmentedColormap
+#from matplotlib.ticker import MaxNLocator
+#from video_prediction.utils.ffmpeg_gif import save_gif
 from skimage.metrics import structural_similarity as ssim
 import pickle