defload_data(root_dir:Optional[str]=None,translate_option:str="az_to_en")->Tuple[NumpyDataset,NumpyDataset,NumpyDataset]:"""Load and return the neural machine translation dataset from TED talks. Args: root_dir: The path to store the downloaded data. When `path` is not provided, the data will be saved into `fastestimator_data` under the user's home directory. translate_option: Options for translation languages. Available options are: "az_to_en", "az_tr_to_en", "be_ru_to_en", "be_to_en", "es_to_pt", "fr_to_pt", "gl_pt_to_en", "gl_to_en", "he_to_pt", "it_to_pt", "pt_to_en", "ru_to_en", "ru_to_pt", and "tr_to_en". Returns: (train_data, eval_data, test_data) """# Set up pathhome=str(Path.home())ifroot_dirisNone:root_dir=os.path.join(home,'fastestimator_data','tednmt')else:root_dir=os.path.join(os.path.abspath(root_dir),'tednmt')os.makedirs(root_dir,exist_ok=True)compressed_path=os.path.join(root_dir,'qi18naacl-dataset.tar.gz')extracted_path=os.path.join(root_dir,'datasets')ifnotos.path.exists(extracted_path):# Downloadifnotos.path.exists(compressed_path):print("Downloading data to {}".format(compressed_path))wget.download('http://www.phontron.com/data/qi18naacl-dataset.tar.gz',compressed_path,bar=bar_custom)# Extractprint("\nExtracting files ...")withtarfile.open(compressed_path)asf:f.extractall(root_dir)# process datadata_path=os.path.join(extracted_path,translate_option)assertos.path.exists(data_path),"folder {} does not exist, please verify translation options".format(data_path)train_ds=_create_dataset(data_path=data_path,translate_option=translate_option,extension="train")eval_ds=_create_dataset(data_path=data_path,translate_option=translate_option,extension="dev")test_ds=_create_dataset(data_path=data_path,translate_option=translate_option,extension="test")returntrain_ds,eval_ds,test_ds