def input_seq_fn(): dict_inp = data.provide_data( dataset_name=dataset_name, parent_dir=dataset_parent_dir, subset=input_sequence_name, batch_size=batch_sz, crop_flag=False, seeds=None, use_appearance=False, shuffle=0) x_in = dict_inp['conditional_input'] return x_in
def input_val_fn(): dict_inp = data.provide_data( dataset_name=dataset_name, parent_dir=dataset_parent_dir, subset='val', batch_size=1, crop_flag=True, crop_size=opts.train_resolution, seeds=[0], max_examples=num_examples, use_appearance=opts.use_appearance, shuffle=0) x_in = dict_inp['conditional_input'] x_gt = dict_inp['expected_output'] # ground truth output x_app = dict_inp['peek_input'] return x_in, x_gt, x_app