def get_eval_op(): dataset = DataGenerator( sample_range=config.eval_samples, shuffle_samples=True, max_patches_per_sample=config.max_patches_per_sample ).make_dataset( split_lhs_rhs=False ) X, Y = dataset.make_one_shot_iterator().get_next() ops = model_eval(X, Y, params={'n_candidates': tf.constant(config.n_candidates)}) return ops
def get_train_op_old(): dataset = DataGenerator( sample_range=config.train_samples, # we have 236 samples shuffle_samples=True, max_patches_per_sample=config.max_patches_per_sample ).make_dataset( split_lhs_rhs=True ) lhs, lhs_label, rhs, rhs_label = dataset.make_one_shot_iterator().get_next() ops = model_train(lhs, lhs_label, rhs, rhs_label, params={'n_candidates': tf.constant(config.n_candidates)}) return ops