def test_dtype(self):
    default_vocab = test_utils.sentencepiece_vocab()
    features = {'inputs': dataset_providers.Feature(vocabulary=default_vocab), 'targets': dataset_providers.Feature(dtype=tf.int64, vocabulary=default_vocab)}
    self.add_task('task_dtypes', self.function_source, preprocessors=(self.DEFAULT_PREPROCESSORS + (utils.map_over_dataset((lambda x: {k: (tf.cast(v, tf.int64) if (k == 'targets') else v) for (k, v) in x.items()})),)), output_features=features)
    self.verify_task_matches_fake_datasets('task_dtypes', use_cached=False)
def test_dtype(self):
    default_vocab = test_utils.sentencepiece_vocab()
    features = {'inputs': dataset_providers.Feature(vocabulary=default_vocab), 'targets': dataset_providers.Feature(dtype=tf.int64, vocabulary=default_vocab)}
    self.add_task('task_dtypes', self.function_source, preprocessors=(self.DEFAULT_PREPROCESSORS + (utils.map_over_dataset((lambda x: {k: (tf.cast(v, tf.int64) if (k == 'targets') else v) for (k, v) in x.items()})),)), output_features=features)
    self.verify_task_matches_fake_datasets('task_dtypes', use_cached=False)