


from pathlib import Path

import fire
from tqdm import tqdm






def 							__lowercase       (			__lowerCAmelCase							:    Any="ro" ,   __lowerCAmelCase							:    List[Any]="en" ,   __lowerCAmelCase							:    Optional[int]="wmt16" ,   __lowerCAmelCase							:    str=None       ):






							"""simple docstring"""




							try:
														import datasets
							except (ModuleNotFoundError, ImportError):
														raise ImportError('run pip install datasets'       )
							a__					=					F'{src_lang}-{tgt_lang}'
							print(F'Converting {dataset}-{pair}'       )
							a__					=					datasets.load_dataset(__lowerCAmelCase ,   __lowerCAmelCase       )
							if save_dir is None:
														a__					=					F'{dataset}-{pair}'
							a__					=					Path(__lowerCAmelCase       )
							save_dir.mkdir(exist_ok=__lowerCAmelCase       )

							for split in ds.keys():
														print(F'Splitting {split} with {ds[split].num_rows} records'       )

														# to save to val.source, val.target like summary datasets
														a__					=					'val' if split == 'validation' else split
														a__					=					save_dir.joinpath(F'{fn}.source'       )
														a__					=					save_dir.joinpath(F'{fn}.target'       )
														a__					=					src_path.open('w+'       )
														a__					=					tgt_path.open('w+'       )

														# reader is the bottleneck so writing one record at a time doesn't slow things down
														for x in tqdm(ds[split]       ):
																					a__					=					x['translation']
																					src_fp.write(ex[src_lang] + '\n'       )
																					tgt_fp.write(ex[tgt_lang] + '\n'       )

							print(F'Saved {dataset} dataset to {save_dir}'       )


if __name__ == "__main__":
						fire.Fire(download_wmt_dataset)








from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case							:	Optional[int]					      =				logging.get_logger(__name__)

snake_case							:	Union[str, Any]					      =				{
    '''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
    '''uclanlp/visualbert-vqa-pre''': '''https://huggingface.co/uclanlp/visualbert-vqa-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-vqa-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-vqa-coco-pre/resolve/main/config.json'''
    ),
    '''uclanlp/visualbert-vcr''': '''https://huggingface.co/uclanlp/visualbert-vcr/resolve/main/config.json''',
    '''uclanlp/visualbert-vcr-pre''': '''https://huggingface.co/uclanlp/visualbert-vcr-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-vcr-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-vcr-coco-pre/resolve/main/config.json'''
    ),
    '''uclanlp/visualbert-nlvr2''': '''https://huggingface.co/uclanlp/visualbert-nlvr2/resolve/main/config.json''',
    '''uclanlp/visualbert-nlvr2-pre''': '''https://huggingface.co/uclanlp/visualbert-nlvr2-pre/resolve/main/config.json''',
    '''uclanlp/visualbert-nlvr2-coco-pre''': (
        '''https://huggingface.co/uclanlp/visualbert-nlvr2-coco-pre/resolve/main/config.json'''
    )
    # See all VisualBERT models at https://huggingface.co/models?filter=visual_bert
}







class 	snake_case_       (lowerCamelCase_				):
					UpperCAmelCase__ :   Dict   				=      '''visual_bert'''
					def __init__(				self       :Optional[int]      ,__snake_case       :Any=3_05_22      ,__snake_case       :str=7_68      ,__snake_case       :Any=5_12      ,__snake_case       :Any=12      ,__snake_case       :int=12      ,__snake_case       :str=30_72      ,__snake_case       :int="gelu"      ,__snake_case       :Optional[int]=0.1      ,__snake_case       :str=0.1      ,__snake_case       :Union[str, Any]=5_12      ,__snake_case       :Tuple=2      ,__snake_case       :Union[str, Any]=0.02      ,__snake_case       :Optional[Any]=1E-12      ,__snake_case       :Optional[Any]=False      ,__snake_case       :int=True      ,__snake_case       :Any=1      ,__snake_case       :Optional[int]=0      ,__snake_case       :Tuple=2      ,**__snake_case       :Any      ,) ->   Union[str, Any]:
												super().__init__(pad_token_id=__snake_case      ,bos_token_id=__snake_case      ,eos_token_id=__snake_case      ,**__snake_case				)

												a__					=					vocab_size
												a__					=					max_position_embeddings
												a__					=					hidden_size
												a__					=					visual_embedding_dim
												a__					=					num_hidden_layers
												a__					=					num_attention_heads
												a__					=					intermediate_size
												a__					=					hidden_act
												a__					=					hidden_dropout_prob
												a__					=					attention_probs_dropout_prob
												a__					=					initializer_range
												a__					=					type_vocab_size
												a__					=					layer_norm_eps
												a__					=					bypass_transformer
												a__					=					special_visual_initialize




