def eval_input_fn():
source_and_target_files = list(
zip(eval_source_files, eval_target_files))
shuffle(source_and_target_files)
source = tf.data.TFRecordDataset(
[s for s, _ in source_and_target_files])
target = tf.data.TFRecordDataset(
[t for _, t in source_and_target_files])
dataset = DatasetSource(source, target, hparams)
dataset = dataset.prepare_and_zip().filter_by_max_output_length(
).repeat().group_by_batch(batch_size=1)
return dataset.dataset
def predict_input_fn():
source = tf.data.TFRecordDataset(list(test_source_files))
target = tf.data.TFRecordDataset(list(test_target_files))
dataset = DatasetSource(source, target, hparams)
batched = dataset.prepare_and_zip().filter_by_max_output_length().group_by_batch(batch_size=1)
return batched.dataset