def test_tf_experimental_inputs_disabled(): pipeline = get_image_pipeline(4, 4, 'cpu', 0) dali_tf.DALIDataset(pipeline, input_datasets={ "test": tf.data.Dataset.from_tensors(np.int32([42, 42])) })
def test_tf_dataset_wrong_placement_gpu(): batch_size = 12 num_threads = 4 iterations = 10 pipeline = get_image_pipeline(batch_size, num_threads, 'gpu', 0) with tf.device('/cpu:0'): dataset = get_dali_dataset_from_pipeline(pipeline, 'cpu', 0) run_dataset_in_graph(dataset, iterations)
def test_tf_dataset_wrong_placement_gpu(): batch_size = 12 num_threads = 4 pipeline = get_image_pipeline(batch_size, num_threads, 'gpu', 0) with tf.device('/cpu:0'): dataset = get_dali_dataset_from_pipeline(pipeline, 'cpu', 0) for sample in dataset: pass
def test_different_num_shapes_dtypes(): batch_size = 12 num_threads = 4 dataset_pipe, shapes, dtypes = get_image_pipeline(batch_size, num_threads, 'cpu') dtypes = tuple(dtypes[0:2]) with tf.device('/cpu:0'): dali_tf.DALIDataset(pipeline=dataset_pipe, batch_size=batch_size, output_shapes=shapes, output_dtypes=dtypes, num_threads=num_threads)