def train_input_fn(): return dataset.input_fn( True, distribution_utils.per_device_batch_size(FLAGS.batch_size, num_gpus), ncf_dataset, FLAGS.epochs_between_evals)
def pred_input_fn(): return dataset.input_fn( False, distribution_utils.per_device_batch_size(batch_size, num_gpus), ncf_dataset)
def pred_input_fn(): return dataset.input_fn(False, per_device_batch_size(batch_size, num_gpus), ncf_dataset)
def train_input_fn(): return dataset.input_fn( True, per_device_batch_size(FLAGS.batch_size, num_gpus), ncf_dataset, FLAGS.epochs_between_evals)
def pred_input_fn(): return dataset.input_fn( False, per_device_batch_size(batch_size, num_gpus), ncf_dataset)
def pred_input_fn(): return dataset.input_fn( False, distribution_utils.per_device_batch_size(batch_size, num_gpus), ncf_dataset)
def pred_input_fn(): return dataset.input_fn(False, per_device_batch_size(batch_size, num_gpus), num_parallel_calls=num_parallel_calls)