def eval_train_epoch(num_batches=None): if num_batches is None: num_batches = 0 eval_train_iter = iter(eval_train_ds) np_iter = data_utils.iterator_as_numpy( itertools.islice(eval_train_iter, num_batches)) for batch in np_iter: yield data_utils.maybe_pad_batch(batch, eval_host_batch_size)
def valid_epoch(num_batches=None): if num_batches is None: num_batches = max_eval_steps valid_iter = iter(eval_ds) np_iter = data_utils.iterator_as_numpy( itertools.islice(valid_iter, num_batches)) for batch in np_iter: yield data_utils.maybe_pad_batch(batch, eval_host_batch_size)
def train_iterator_fn(): return data_utils.iterator_as_numpy(iter(train_ds))