




from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
       from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


UpperCAmelCase_									=	logging.get_logger(__name__)

UpperCAmelCase_									=	{
    'microsoft/deberta-v2-xlarge': 'https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json',
    'microsoft/deberta-v2-xxlarge': 'https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json',
    'microsoft/deberta-v2-xlarge-mnli': (
        'https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json'
    ),
    'microsoft/deberta-v2-xxlarge-mnli': (
        'https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json'
    ),
}





class     lowerCamelCase__(					A__):
      UpperCAmelCase__      :	List[Any]    		=   'deberta-v2'
      def __init__(				self: List[str]    ,       UpperCamelCase_: Dict=12_81_00    ,       UpperCamelCase_: List[str]=15_36    ,       UpperCamelCase_: Union[str, Any]=24    ,       UpperCamelCase_: Optional[Any]=24    ,       UpperCamelCase_: Union[str, Any]=61_44    ,       UpperCamelCase_: Any="gelu"    ,       UpperCamelCase_: int=0.1    ,       UpperCamelCase_: str=0.1    ,       UpperCamelCase_: Dict=5_12    ,       UpperCamelCase_: int=0    ,       UpperCamelCase_: Union[str, Any]=0.02    ,       UpperCamelCase_: str=1E-7    ,       UpperCamelCase_: List[str]=False    ,       UpperCamelCase_: Dict=-1    ,       UpperCamelCase_: Dict=0    ,       UpperCamelCase_: str=True    ,       UpperCamelCase_: Dict=None    ,       UpperCamelCase_: Dict=0    ,       UpperCamelCase_: int="gelu"    ,       **UpperCamelCase_: Any    ,       ):
             super().__init__(**UpperCamelCase_   )

             __lowerCamelCase   =						hidden_size
             __lowerCamelCase   =						num_hidden_layers
             __lowerCamelCase   =						num_attention_heads
             __lowerCamelCase   =						intermediate_size
             __lowerCamelCase   =						hidden_act
             __lowerCamelCase   =						hidden_dropout_prob
             __lowerCamelCase   =						attention_probs_dropout_prob
             __lowerCamelCase   =						max_position_embeddings
             __lowerCamelCase   =						type_vocab_size
             __lowerCamelCase   =						initializer_range
             __lowerCamelCase   =						relative_attention
             __lowerCamelCase   =						max_relative_positions
             __lowerCamelCase   =						pad_token_id
             __lowerCamelCase   =						position_biased_input

             # Backwards compatibility
             if type(UpperCamelCase_   ) == str:
                    __lowerCamelCase   =						[x.strip() for x in pos_att_type.lower().split("""|"""   )]

             __lowerCamelCase   =						pos_att_type
             __lowerCamelCase   =						vocab_size
             __lowerCamelCase   =						layer_norm_eps

             __lowerCamelCase   =						kwargs.get("""pooler_hidden_size"""    ,       UpperCamelCase_   )
             __lowerCamelCase   =						pooler_dropout
             __lowerCamelCase   =						pooler_hidden_act





class     lowerCamelCase__(					A__):
      @property
      def 			lowerCAmelCase__						(				self: Optional[int]   ):


             if self.task == "multiple-choice":
                    __lowerCamelCase   =						{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
             else:
                    __lowerCamelCase   =						{0: '''batch''', 1: '''sequence'''}
             if self._config.type_vocab_size > 0:
                    return OrderedDict(
                        [("""input_ids""", dynamic_axis), ("""attention_mask""", dynamic_axis), ("""token_type_ids""", dynamic_axis)]   )
             else:
                    return OrderedDict([("""input_ids""", dynamic_axis), ("""attention_mask""", dynamic_axis)]   )
      @property
      def 			lowerCAmelCase__						(				self: Tuple   ):
             return 12




      def 			lowerCAmelCase__						(				self: str    ,       UpperCamelCase_: Tuple    ,       UpperCamelCase_: List[Any] = -1    ,       UpperCamelCase_: Optional[int] = -1    ,       UpperCamelCase_: str = -1    ,       UpperCamelCase_: Optional[Any] = False    ,       UpperCamelCase_: int = None    ,       UpperCamelCase_: Optional[Any] = 3    ,       UpperCamelCase_: Optional[int] = 40    ,       UpperCamelCase_: int = 40    ,       UpperCamelCase_: Union[str, Any] = None    ,       ):
             __lowerCamelCase   =						super().generate_dummy_inputs(preprocessor=UpperCamelCase_    ,       framework=UpperCamelCase_   )
             if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
                    del dummy_inputs["token_type_ids"]
             return dummy_inputs





'''simple docstring'''
from pathlib import Path

import fire
from tqdm import tqdm


def 			a      (			__a="ro" ,					__a="en" ,					__a="wmt16" ,					__a=None   )  ->	None:



					'''simple docstring'''






					try:
										import datasets
					except (ModuleNotFoundError, ImportError):
										raise ImportError('''run pip install datasets'''   )
					UpperCamelCase__   :int												= f'''{src_lang}-{tgt_lang}'''
					print(f'''Converting {dataset}-{pair}'''   )
					UpperCamelCase__   :Tuple												= datasets.load_dataset(__a ,					__a   )
					if save_dir is None:
										UpperCamelCase__   :Any												= f'''{dataset}-{pair}'''
					UpperCamelCase__   :Dict												= Path(__a   )
					save_dir.mkdir(exist_ok=__a   )

					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
										UpperCamelCase__   :Dict												= '''val''' if split == '''validation''' else split
										UpperCamelCase__   :List[Any]												= save_dir.joinpath(f'''{fn}.source'''   )
										UpperCamelCase__   :int												= save_dir.joinpath(f'''{fn}.target'''   )
										UpperCamelCase__   :Union[str, Any]												= src_path.open('''w+'''   )
										UpperCamelCase__   :Tuple												= 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]   ):
															UpperCamelCase__   :Union[str, Any]												= 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)