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
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