def test_gluon_iterator_sparse_batch():
from nvidia.dali.plugin.mxnet import DALIGluonIterator as GluonIterator
from mxnet.ndarray.ndarray import NDArray
num_gpus = 1
batch_size = 16
pipes, _ = create_pipeline(
lambda gpu: COCOReaderPipeline(batch_size=batch_size,
num_threads=4,
shard_id=gpu,
num_gpus=num_gpus,
data_paths=data_sets[0],
random_shuffle=True,
stick_to_shard=False,
shuffle_after_epoch=False,
pad_last_batch=True,
return_labels=True), batch_size,
num_gpus)
dali_train_iter = GluonIterator(
pipes,
pipes[0].epoch_size("Reader"),
[GluonIterator.SPARSE_TAG, GluonIterator.DENSE_TAG],
fill_last_batch=True)
for it in dali_train_iter:
labels, ids = it[0] # gpu 0
# labels should be a sparse batch: a list of per-sample NDArray's
# ids should be a dense batch: a single NDarray reprenseting the batch
assert isinstance(labels, (tuple, list))
assert len(labels) == batch_size
assert isinstance(labels[0], NDArray)
assert isinstance(ids, NDArray)
def test_gluon_iterator_not_fill_last_batch_pad_last_batch():
from nvidia.dali.plugin.mxnet import DALIGluonIterator as GluonIterator
num_gpus = 1
batch_size = 100
pipes, data_size = create_pipeline(
lambda gpu: COCOReaderPipeline(batch_size=batch_size,
num_threads=4,
shard_id=gpu,
num_gpus=num_gpus,
data_paths=data_sets[0],
random_shuffle=False,
stick_to_shard=False,
shuffle_after_epoch=False,
pad_last_batch=True), batch_size,
num_gpus)
dali_train_iter = GluonIterator(pipes,
size=pipes[0].epoch_size("Reader"),
fill_last_batch=False)
img_ids_list, img_ids_list_set, mirrored_data, _, _ = \
gather_ids(dali_train_iter, lambda x: x[0].squeeze().asnumpy(), lambda x: 0, data_size)
assert len(img_ids_list) == data_size
assert len(img_ids_list_set) == data_size
assert len(set(mirrored_data)) != 1
dali_train_iter.reset()
next_img_ids_list, next_img_ids_list_set, next_mirrored_data, pad, remainder = \
gather_ids(dali_train_iter, lambda x: x[0].squeeze().asnumpy(), lambda x: 0, data_size)
assert len(next_img_ids_list) == data_size
assert len(next_img_ids_list_set) == data_size
assert len(set(next_mirrored_data)) != 1
def test_stop_iteration_gluon():
from nvidia.dali.plugin.mxnet import DALIGluonIterator as GluonIterator
fw_iter = lambda pipe, size, auto_reset: GluonIterator(
pipe, size, [GluonIterator.DENSE_TAG], auto_reset=auto_reset)
iter_name = "GluonIterator"
for batch_size, epochs, iter_num, auto_reset, infinite in stop_teration_case_generator(
):
yield check_stop_iter, fw_iter, iter_name, batch_size, epochs, iter_num, auto_reset, infinite
def test_stop_iteration_gluon_fail_single():
from nvidia.dali.plugin.mxnet import DALIGluonIterator as GluonIterator
fw_iter = lambda pipe, size, auto_reset: GluonIterator(
pipe, size=size, auto_reset=auto_reset)
check_stop_iter_fail_single(fw_iter)
