def benchmark_iterate_hub_local_tensorflow_setup(
dataset_name, dataset_split, batch_size, prefetch_factor
):
dset = Dataset.from_tfds(dataset_name, split=dataset_split)
path = os.path.join(".", "hub_data", "tfds")
dset.store(path)
dset = Dataset(path, cache=False, storage_cache=False, mode="r")
loader = dset.to_tensorflow().batch(batch_size).prefetch(prefetch_factor)
return (loader,)
def time_iter_hub_local_tensorflow(
dataset_info, batch_size=BATCH_SIZE, prefetch_factor=PREFETCH_SIZE, process=None
):
dset = Dataset.from_tfds(dataset_info["name"], split=dataset_info["split"])
path = os.path.join(ROOT, "Hub_data", "tfds")
dset.store(path)
dset = Dataset(path, cache=False, storage_cache=False, mode="r")
loader = dset.to_tensorflow().batch(batch_size).prefetch(prefetch_factor)
with Timer("Hub (local) `.to_tensorflow()`"):
for batch in loader:
image = batch["image"]
label = batch["label"]
if process is not None:
process(image, label)
