import tensorflow_datasets as tfds
data_dir = "../../../data/vtab/"

# TODO: Uncomment the dataset you want to download

# caltech101
# dataset_builder = tfds.builder("caltech101:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# cifar100
# dataset_builder = tfds.builder("cifar100:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()
#
# clevr
# dataset_builder = tfds.builder("clevr:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# # dmlab
# dataset_builder = tfds.builder("dmlab:2.0.1", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# # dsprites
# dataset_builder = tfds.builder("dsprites:2.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# dtd
# dataset_builder = tfds.builder("dtd:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# eurosat
# subset="rgb"
# dataset_name = "eurosat/{}:2.*.*".format(subset)
# dataset_builder = tfds.builder(dataset_name, data_dir=data_dir)
# dataset_builder.download_and_prepare()

# oxford_flowers102
# dataset_builder = tfds.builder("oxford_flowers102:2.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# oxford_iiit_pet
# dataset_builder = tfds.builder("oxford_iiit_pet:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# patch_camelyon
# dataset_builder = tfds.builder("patch_camelyon:2.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# smallnorb
# dataset_builder = tfds.builder("smallnorb:2.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# svhn
# dataset_builder = tfds.builder("svhn_cropped:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# sun397
# dataset_builder = tfds.builder("sun397/tfds:4.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# dataset_builder = tfds.builder("resisc45:3.*.*", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# dataset_builder = tfds.builder("kitti:3.2.0", data_dir=data_dir)
# dataset_builder.download_and_prepare()

# config_and_version = "btgraham-300" + ":3.*.*"
# dataset_builder = tfds.builder("diabetic_retinopathy_detection/{}".format(config_and_version), data_dir=data_dir)
# dataset_builder.download_and_prepare()
