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dlr: add RANDSEED to slurm
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1 changed files with 2 additions and 1 deletions
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@ -43,6 +43,7 @@ show_help() {
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echo -e " LEARNING_RATE The learning rate to use. Default: 0.001." >&2;
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echo -e " UPSAMPLE How much to upsample by at the beginning of the model. A value of disables upscaling. Default: 2." >&2;
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echo -e " STEPS_PER_EXECUTION How many steps to perform before surfacing from the GPU to e.g. do callbacks. Default: 16." >&2;
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echo -e " RANDSEED The random seed to use when shuffling filepaths. Default: unset, which means use a random value." >&2;
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echo -e " JIT_COMPILE Set to any value to compile the model with XLA." >&2;
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echo -e " PREDICT_COUNT The number of items from the (SCRAMBLED) dataset to make a prediction for." >&2;
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echo -e " POSTFIX Postfix to append to the output dir (auto calculated)." >&2;
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@ -74,7 +75,7 @@ echo -e ">>> DIR_OUTPUT: ${DIR_OUTPUT}";
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echo -e ">>> Additional args: ${ARGS}";
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export PATH=$HOME/software/bin:$PATH;
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export IMAGE_SIZE BATCH_SIZE DIR_RAINFALLWATER PATH_HEIGHTMAP PATH_COLOURMAP STEPS_PER_EPOCH DIR_OUTPUT PATH_CHECKPOINT EPOCHS PREDICT_COUNT NO_REMOVE_ISOLATED_PIXELS LOSS LEARNING_RATE DICE_LOG_COSH WATER_THRESHOLD UPSAMPLE STEPS_PER_EXECUTION JIT_COMPILE;
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export IMAGE_SIZE BATCH_SIZE DIR_RAINFALLWATER PATH_HEIGHTMAP PATH_COLOURMAP STEPS_PER_EPOCH DIR_OUTPUT PATH_CHECKPOINT EPOCHS PREDICT_COUNT NO_REMOVE_ISOLATED_PIXELS LOSS LEARNING_RATE DICE_LOG_COSH WATER_THRESHOLD UPSAMPLE STEPS_PER_EXECUTION JIT_COMPILE RANDSEED;
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echo ">>> Installing requirements";
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conda run -n py38 pip install -q -r requirements.txt;
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