Creates training iterator to access and augment the dataset

tefla.core.iter_ops.create_training_iters (cnf, data_set, standardizer, crop_size, epoch, parallel=True)

Args

• cnf: configs dict with all training and augmentation params
• data_set: an instance of the dataset class
• standardizer: data samples standardization; either samplewise or aggregate
• crop_size: training time crop_size of the data samples
• epoch: the current epoch number; used for data balancing
• parallel: iterator type; either parallel or queued

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Creates prediction iterator to access and augment the dataset

tefla.core.iter_ops.create_prediction_iter (cnf, standardizer, crop_size, preprocessor=None, sync=False)

Args

• cnf: configs dict with all training and augmentation params
• standardizer: data samples standardization; either samplewise or aggregate
• crop_size: training time crop_size of the data samples
• preprocessor: data processing or cropping function
• sync: a bool, if False, used parallel iterator

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