def test_03_ds_print_func():
ds = create_dataset()
print(">>> print_ds_info:")
print_ds_info(ds)
print(">>> print_ds_performance:")
print_ds_performance(ds)
print(">>> print_ds_data:")
print_ds_data(ds)
self.samples.append([
np.random.rand(3, 4, 5).astype(np.float32),
np.random.randint(10, size=()).astype(np.int32)
])
def __len__(self):
return len(self.samples)
# define dataset
ds = de.GeneratorDataset(source=BaseDataset(),
column_names=['image', 'label'],
num_shards=num_shards,
shard_id=shard_id)
# map ops
ds = ds.map(input_columns=["image"],
operations=lambda img: img,
num_parallel_workers=8)
# batch & repeat
ds = ds.batch(batch_size=batch_size, drop_remainder=False)
ds = ds.repeat(count=1)
return ds
if __name__ == '__main__':
dataset = create_dataset()
ems.print_ds_info(dataset)
ems.print_ds_data(dataset)