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)