150 lines
6.7 KiB
Python
150 lines
6.7 KiB
Python
MODEL_STORAGE_BASE_PATH = "/path/to/this/project/saved_models"
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DATASET_STORAGE_BASE_PATH = "/path/to/this/project/datasets"
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TRAIN_TEMP_DATA_BASE_PATH = "/path/to/this/project/train_temp"
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TEST_TEMP_DATA_BASE_PATH = "/path/to/this/project/test_temp"
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TEST_RUNS = [
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# CIFAR-10 dataset
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# {
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# 'name': "CIFAR-10 on basic auto-encoder",
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# 'encoder_model': "models.basic_encoder.BasicAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.cifar10_dataset.Cifar10Dataset",
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# 'dataset_kwargs': {"path": "cifar-10-batches-py"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "CIFAR-10 on sparse L1 auto-encoder",
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# 'encoder_model': "models.sparse_encoder.SparseL1AutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.cifar10_dataset.Cifar10Dataset",
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# 'dataset_kwargs': {"path": "cifar-10-batches-py"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "CIFAR-10 on denoising auto-encoder",
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# 'encoder_model': "models.denoising_encoder.DenoisingAutoEncoder",
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# 'encoder_kwargs': {'input_corruption_model': "models.gaussian_corruption.GaussianCorruption"},
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# 'dataset_model': "models.cifar10_dataset.Cifar10Dataset",
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# 'dataset_kwargs': {"path": "cifar-10-batches-py"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "CIFAR-10 on contractive auto-encoder",
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# 'encoder_model': "models.contractive_encoder.ContractiveAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.cifar10_dataset.Cifar10Dataset",
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# 'dataset_kwargs': {"path": "cifar-10-batches-py"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "CIFAR-10 on variational auto-encoder",
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# 'encoder_model': "models.variational_encoder.VariationalAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.cifar10_dataset.Cifar10Dataset",
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# 'dataset_kwargs': {"path": "cifar-10-batches-py"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# MNIST dataset
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# {
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# 'name': "MNIST on basic auto-encoder",
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# 'encoder_model': "models.basic_encoder.BasicAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.mnist_dataset.MNISTDataset",
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# 'dataset_kwargs': {"path": "mnist"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "MNIST on sparse L1 auto-encoder",
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# 'encoder_model': "models.sparse_encoder.SparseL1AutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.mnist_dataset.MNISTDataset",
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# 'dataset_kwargs': {"path": "mnist"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "MNIST on denoising auto-encoder",
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# 'encoder_model': "models.denoising_encoder.DenoisingAutoEncoder",
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# 'encoder_kwargs': {'input_corruption_model': "models.gaussian_corruption.GaussianCorruption"},
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# 'dataset_model': "models.mnist_dataset.MNISTDataset",
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# 'dataset_kwargs': {"path": "mnist"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "MNIST on contractive auto-encoder",
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# 'encoder_model': "models.contractive_encoder.ContractiveAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.mnist_dataset.MNISTDataset",
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# 'dataset_kwargs': {"path": "mnist"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "MNIST on variational auto-encoder",
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# 'encoder_model': "models.variational_encoder.VariationalAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.mnist_dataset.MNISTDataset",
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# 'dataset_kwargs': {"path": "mnist"},
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# 'corruption_model': "models.gaussian_corruption.GaussianCorruption",
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# 'corruption_kwargs': {},
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# },
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# US Weather Events dataset
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# {
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# 'name': "US Weather Events on basic auto-encoder",
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# 'encoder_model': "models.basic_encoder.BasicAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.usweather_dataset.USWeatherEventsDataset",
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# 'dataset_kwargs': {"path": "weather-events"},
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# 'corruption_model': "models.random_corruption.RandomCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "US Weather Events on sparse L1 auto-encoder",
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# 'encoder_model': "models.sparse_encoder.SparseL1AutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.usweather_dataset.USWeatherEventsDataset",
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# 'dataset_kwargs': {"path": "weather-events"},
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# 'corruption_model': "models.random_corruption.RandomCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "US Weather Events on denoising auto-encoder",
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# 'encoder_model': "models.denoising_encoder.DenoisingAutoEncoder",
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# 'encoder_kwargs': {'input_corruption_model': "models.random_corruption.RandomCorruption"},
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# 'dataset_model': "models.usweather_dataset.USWeatherEventsDataset",
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# 'dataset_kwargs': {"path": "weather-events"},
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# 'corruption_model': "models.random_corruption.RandomCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "US Weather Events on contractive auto-encoder",
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# 'encoder_model': "models.contractive_encoder.ContractiveAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.usweather_dataset.USWeatherEventsDataset",
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# 'dataset_kwargs': {"path": "weather-events"},
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# 'corruption_model': "models.random_corruption.RandomCorruption",
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# 'corruption_kwargs': {},
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# },
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# {
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# 'name': "US Weather Events on variational auto-encoder",
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# 'encoder_model': "models.variational_encoder.VariationalAutoEncoder",
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# 'encoder_kwargs': {},
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# 'dataset_model': "models.usweather_dataset.USWeatherEventsDataset",
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# 'dataset_kwargs': {"path": "weather-events"},
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# 'corruption_model': "models.random_corruption.RandomCorruption",
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# 'corruption_kwargs': {},
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# },
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]
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