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