diff --git a/README.md b/README.md index a99357c336fc755c441902e960d522140e0f1c9a..ecb63787f09bad39ba5ee883be3bbaa7fb6ec6c1 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ This project need to work with [Workflow_parallel_frame_prediction project](http - Clone this repo: ```bash git clone -b master https://gitlab.version.fz-juelich.de/gong1/video_prediction_savp.git -git clone -b master https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction +git clone -b master https://gitlab.version.fz-juelich.de/gong1/workflow_parallel_frame_prediction.git cd video_prediction_savp ``` - Install TensorFlow >= 1.9 and dependencies from http://tensorflow.org/ diff --git a/bash/workflow_era5.sh b/bash/workflow_era5.sh index e343d83faa02a19b9a6da167de3609ef95158fc9..01d16bfdf7f38ffe00495ba31f85349d9ce68335 100755 --- a/bash/workflow_era5.sh +++ b/bash/workflow_era5.sh @@ -9,6 +9,7 @@ set -e MODEL=$1 TRAIN_MODE=$2 EXP_NAME=$3 +RETRAIN=1 #if we continue training the model or using the existing end-to-end model, 1 means continue training, and 1 means use the existing one DATA_ETL_DIR=/p/scratch/deepacf/${USER}/ DATA_EXTRA_DIR=${DATA_ETL_DIR}/extractedData/${EXP_NAME} DATA_PREPROCESS_DIR=${DATA_ETL_DIR}/preprocessedData/${EXP_NAME} @@ -69,11 +70,16 @@ fi if [ "$TRAIN_MODE" == "pre_trained" ]; then echo "step3: Using kth pre_trained model" elif [ "$TRAIN_MODE" == "end_to_end" ]; then - echo "Step3: Training Starts " - python ./scripts/train_v2.py --input_dir $DATA_PREPROCESS_TF_DIR --dataset era5 \ - --model ${MODEL} --model_hparams_dict hparams/kth/${method_dir}/model_hparams.json \ - --output_dir ${TRAIN_OUTPUT_DIR} - echo "Training ends " + echo "step3: End-to-end training" + if [ "$RETRAIN" == 1 ]; then + echo "Using the existing end-to-end model" + else + echo "Step3: Training Starts " + python ./scripts/train_v2.py --input_dir $DATA_PREPROCESS_TF_DIR --dataset era5 \ + --model ${MODEL} --model_hparams_dict hparams/kth/${method_dir}/model_hparams.json \ + --output_dir ${TRAIN_OUTPUT_DIR} --checkpoint ${CHECKPOINT_DIR_DIR} + echo "Training ends " + fi else echo "TRAIN_MODE is end_to_end or pre_trained" exit 1 diff --git a/bash/workflow_era5_macOS.sh b/bash/workflow_era5_macOS.sh index baa9f95352d6aa6ca7fac1af7311b72072b69993..78b5101d810d9818cfb720154e9c42cc321f44a3 100755 --- a/bash/workflow_era5_macOS.sh +++ b/bash/workflow_era5_macOS.sh @@ -9,6 +9,8 @@ set -e MODEL=$1 TRAIN_MODE=$2 EXP_NAME=$3 +RETRAIN=1 #if we continue training the model or using the existing end-to-end model, 1 means continue training, and 1 means use the existing one +DATA_ETL_DIR=/p/scratch/deepacf/${USER}/ DATA_ETL_DIR=/p/scratch/deepacf/${USER}/ DATA_EXTRA_DIR=${DATA_ETL_DIR}/extractedData/${EXP_NAME} DATA_PREPROCESS_DIR=${DATA_ETL_DIR}/preprocessedData/${EXP_NAME} @@ -69,11 +71,16 @@ fi if [ "$TRAIN_MODE" == "pre_trained" ]; then echo "step3: Using kth pre_trained model" elif [ "$TRAIN_MODE" == "end_to_end" ]; then - echo "Step3: Training Starts " - python ./scripts/train_v2.py --input_dir $DATA_PREPROCESS_TF_DIR --dataset era5 \ - --model ${MODEL} --model_hparams_dict hparams/kth/${method_dir}/model_hparams.json \ - --output_dir ${TRAIN_OUTPUT_DIR} - echo "Training ends " + echo "step3: End-to-end training" + if [ "$RETRAIN" == 1 ]; then + echo "Using the existing end-to-end model" + else + echo "Training Starts " + python ./scripts/train_v2.py --input_dir $DATA_PREPROCESS_TF_DIR --dataset era5 \ + --model ${MODEL} --model_hparams_dict hparams/kth/${method_dir}/model_hparams.json \ + --output_dir ${TRAIN_OUTPUT_DIR} --checkpoint ${CHECKPOINT_DIR} + echo "Training ends " + fi else echo "TRAIN_MODE is end_to_end or pre_trained" exit 1 @@ -82,5 +89,5 @@ fi #########Generate results################# echo "Step4: Postprocessing start" python ./scripts/generate_transfer_learning_finetune.py --input_dir ${DATA_PREPROCESS_TF_DIR} \ ---dataset_hparams sequence_length=20 --checkpoint ${CHECKPOINT_DIR_DIR} --mode test --results_dir ${RESULTS_OUTPUT_DIR} \ +--dataset_hparams sequence_length=20 --checkpoint ${CHECKPOINT_DIR} --mode test --results_dir ${RESULTS_OUTPUT_DIR} \ --batch_size 4 --dataset era5 \ No newline at end of file