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nn_iigs6_epochs_experiments.sh
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#!/usr/bin/env bash
# CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 500
# CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 5000
# CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 50000
# CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 500000
# medium-size dataset: 210 seed files
#CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 500
#CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 5000
#CUDA_VISIBLE_DEVICES=1 python3.6 -m src.nn.ConvNet_IIGS6Lvl10 --epochs 50000
# @local: baselines
#PYTHON=/usr/bin/python3
#${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --epochs 50
#${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --epochs 500
#${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --epochs 5000
# @aic-ml: baselines w/ complex arch
#PYTHON=python3.6
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 5
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 50
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 500
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNetBaseline_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 5000
# @aic-ml: 1-file dataset
#PYTHON=python3.6
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNet_IIGS6Lvl10 --epochs 500
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNet_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 500
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNet_IIGS6Lvl10 --epochs 5000
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNet_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 5000
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNet_IIGS6Lvl10 --epochs 50000
#CUDA_VISIBLE_DEVICES=1 ${PYTHON} -m src.nn.ConvNet_IIGS6Lvl10 --extractor C-45,C-45,C-45 --regressor C-135,C-135,C-135 --epochs 50000