Olga (Geya) Xu, 260520542
- numpy==1.14.2
- torch.egg==info
- torchvision==0.2.0
- torch==0.4.0a0+6a41e2d
python run_mnist.py
usage: run_mnist.py [-h] [--batch-size BATCH_SIZE] [--max-layers MAX_LAYERS] [--alpha ALPHA] [--gamma GAMMA] [-lr LEARNING_RATE] [--num-episodes NUM_EPISODES] [--model-dir MODEL_DIR] [--model-name MODEL_NAME] [--save-freq SAVE_FREQ]
python run_cifar.py
usage: run_cifar10.py [-h] [--batch-size BATCH_SIZE] [--max-layers MAX_LAYERS] [--alpha ALPHA] [--gamma GAMMA] [-lr LEARNING_RATE] [--num-episodes NUM_EPISODES] [--model-dir MODEL_DIR] [--model-name MODEL_NAME] [--check-memory] [--save-freq SAVE_FREQ] [--load-model LOAD_MODEL]
python test_mnist.py --load-model [MODEL]
usage: test_mnist.py [-h] [--batch-size BATCH_SIZE] [--max-layers MAX_LAYERS] [--alpha ALPHA] [-lr LEARNING_RATE] [--num-epochs NUM_EPOCHS] [--model-dir MODEL_DIR] [--model-name MODEL_NAME] [--load-path LOAD_PATH]
python test_cifar.py --load-model [MODEL]
usage: test_cifar.py [-h] [--batch-size BATCH_SIZE] [--alpha ALPHA] [-lr LEARNING_RATE] [--num-epochs NUM_EPOCHS] [--model-dir MODEL_DIR] [--model-name MODEL_NAME] [--load-path LOAD_PATH]
python print_experience_tree.py --load-model [MODEL]
usage: print_experience_tree.py [-h] --load-model LOAD_MODEL
- Neural Architecture Search with Reinforcement Learning [arxiv]
- Convolutional Neural Network Architecture Seach with Q-Learning [paper]
Special thanks to the authors in [reinforce.py] for their REINFORCE implementation and the authors in [main.py] for their residual block implementation. I have used some parts of their implementation.