import numpy as np import tensorflow as tf class Parameters: # data level image_count = 3670 image_size = 384 batch_size = 12 num_grad_accumulation = 8 label_smooth = 0.05 class_number = 5 val_split = 0.2 autotune = tf.data.AUTOTUNE # hparams epochs = 10 lr_sched = "cosine_restart" lr_base = 0.016 lr_min = 0 lr_decay_epoch = 2.4 lr_warmup_epoch = 5 lr_decay_factor = 0.97 scaled_lr = lr_base * (batch_size / 256.0) scaled_lr_min = lr_min * (batch_size / 256.0) num_validation_sample = int(image_count * val_split) num_training_sample = image_count - num_validation_sample train_step = int(np.ceil(num_training_sample / float(batch_size))) total_steps = train_step * epochs