


'''simple docstring'''






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


lowercase							=logging.get_logger(__name__)

lowercase							='▁'

lowercase							={'vocab_file': 'sentencepiece.bpe.model'}

lowercase							={
    'vocab_file': {
        'facebook/mbart-large-en-ro': (
            'https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'
        ),
        'facebook/mbart-large-cc25': (
            'https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

lowercase							={
    'facebook/mbart-large-en-ro': 1024,
    'facebook/mbart-large-cc25': 1024,
}

# fmt: off
lowercase							=['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN']






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										=VOCAB_FILES_NAMES
       UpperCAmelCase										=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase										=PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase										=["input_ids", "attention_mask"]

       UpperCAmelCase										=[]
       UpperCAmelCase										=[]






       def __init__(      self  ,							snake_case  ,							snake_case="<s>"  ,							snake_case="</s>"  ,							snake_case="</s>"  ,							snake_case="<s>"  ,							snake_case="<unk>"  ,							snake_case="<pad>"  ,							snake_case="<mask>"  ,							snake_case=None  ,							snake_case=None  ,							snake_case=None  ,							snake_case = None  ,							snake_case=None  ,							**snake_case  ,							)						->  Union[str, Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       str							   =AddedToken(snake_case  ,							lstrip=snake_case  ,							rstrip=snake_case) if isinstance(snake_case  ,							snake_case) else mask_token

          _UpperCAmelCase       :       Any							   ={} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              bos_token=snake_case  ,							eos_token=snake_case  ,							unk_token=snake_case  ,							sep_token=snake_case  ,							cls_token=snake_case  ,							pad_token=snake_case  ,							mask_token=snake_case  ,							tokenizer_file=snake_case  ,							src_lang=snake_case  ,							tgt_lang=snake_case  ,							additional_special_tokens=snake_case  ,							sp_model_kwargs=self.sp_model_kwargs  ,							**snake_case  ,							)

          _UpperCAmelCase       :       Optional[int]							   =spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.Load(str(snake_case))
          _UpperCAmelCase       :       Dict							   =vocab_file

          # Original fairseq vocab and spm vocab must be "aligned":
          # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
          # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
          # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
          # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

          # Mimic fairseq token-to-id alignment for the first 4 token
          _UpperCAmelCase       :       Dict							   ={'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

          # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
          _UpperCAmelCase       :       Tuple							   =1

          _UpperCAmelCase       :       int							   =len(self.sp_model)
          _UpperCAmelCase       :       int							   ={
              code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(snake_case)
          }
          _UpperCAmelCase       :       Optional[int]							   ={v: k for k, v in self.lang_code_to_id.items()}
          _UpperCAmelCase       :       str							   =len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

          self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
          _UpperCAmelCase       :       Optional[Any]							   ={v: k for k, v in self.fairseq_tokens_to_ids.items()}
          _UpperCAmelCase       :       Union[str, Any]							   =list(self.lang_code_to_id.keys())

          if additional_special_tokens is not None:
             # Only add those special tokens if they are not already there.
             self._additional_special_tokens.extend(
                 [t for t in additional_special_tokens if t not in self._additional_special_tokens])

          _UpperCAmelCase       :       Optional[int]							   =src_lang if src_lang is not None else 'en_XX'
          _UpperCAmelCase       :       Any							   =self.lang_code_to_id[self._src_lang]
          _UpperCAmelCase       :       str							   =tgt_lang
          self.set_src_lang_special_tokens(self._src_lang)






       def __getstate__(      self)						->  Union[str, Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       Tuple							   =self.__dict__.copy()
          _UpperCAmelCase       :       int							   =None
          _UpperCAmelCase       :       Optional[int]							   =self.sp_model.serialized_model_proto()
          return state






       def __setstate__(      self  ,							snake_case)						->  Optional[Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       Union[str, Any]							   =d

          # for backward compatibility
          if not hasattr(self  ,							'sp_model_kwargs'):
             _UpperCAmelCase       :       Tuple							   ={}

          _UpperCAmelCase       :       Optional[int]							   =spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.LoadFromSerializedProto(self.sp_model_proto)






       @property
       def       lowerCAmelCase		(      self)						->  Optional[int]:




          '''simple docstring'''
          return len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset + 1  # Plus 1 for the mask token






       @property
       def       lowerCAmelCase		(      self)						->  str:




          '''simple docstring'''
          return self._src_lang






       @src_lang.setter
       def       lowerCAmelCase		(      self  ,							snake_case)						->  None:




          '''simple docstring'''
          _UpperCAmelCase       :       str							   =new_src_lang
          self.set_src_lang_special_tokens(self._src_lang)






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None  ,							snake_case = False)						->  List[int]:




          '''simple docstring'''

          if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=snake_case  ,							token_ids_a=snake_case  ,							already_has_special_tokens=snake_case)

          _UpperCAmelCase       :       int							   =[1] * len(self.prefix_tokens)
          _UpperCAmelCase       :       int							   =[1] * len(self.suffix_tokens)
          if token_ids_a is None:
             return prefix_ones + ([0] * len(snake_case)) + suffix_ones
          return prefix_ones + ([0] * len(snake_case)) + ([0] * len(snake_case)) + suffix_ones






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  List[int]:




          '''simple docstring'''
          if token_ids_a is None:
             return self.prefix_tokens + token_ids_a + self.suffix_tokens
          # We don't expect to process pairs, but leave the pair logic for API consistency
          return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  List[int]:




          '''simple docstring'''
          _UpperCAmelCase       :       int							   =[self.sep_token_id]
          _UpperCAmelCase       :       Any							   =[self.cls_token_id]

          if token_ids_a is None:
             return len(cls + token_ids_a + sep) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case  ,							snake_case  ,							snake_case  ,							**snake_case)						->  str:




          '''simple docstring'''
          if src_lang is None or tgt_lang is None:
             raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model')
          _UpperCAmelCase       :       List[Any]							   =src_lang
          _UpperCAmelCase       :       List[Any]							   =self(snake_case  ,							add_special_tokens=snake_case  ,							return_tensors=snake_case  ,							**snake_case)
          _UpperCAmelCase       :       Optional[Any]							   =self.convert_tokens_to_ids(snake_case)
          _UpperCAmelCase       :       Union[str, Any]							   =tgt_lang_id
          return inputs






       def       lowerCAmelCase		(      self)						->  Optional[int]:




          '''simple docstring'''
          _UpperCAmelCase       :       str							   ={self.convert_ids_to_tokens(snake_case): i for i in range(self.vocab_size)}
          vocab.update(self.added_tokens_encoder)
          return vocab






       def       lowerCAmelCase		(      self  ,							snake_case)						->  List[str]:




          '''simple docstring'''
          return self.sp_model.encode(snake_case  ,							out_type=snake_case)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Optional[int]:




          '''simple docstring'''
          if token in self.fairseq_tokens_to_ids:
             return self.fairseq_tokens_to_ids[token]
          _UpperCAmelCase       :       int							   =self.sp_model.PieceToId(snake_case)

          # Need to return unknown token if the SP model returned 0
          return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






       def       lowerCAmelCase		(      self  ,							snake_case)						->  int:




          '''simple docstring'''
          if index in self.fairseq_ids_to_tokens:
             return self.fairseq_ids_to_tokens[index]
          return self.sp_model.IdToPiece(index - self.fairseq_offset)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Tuple:




          '''simple docstring'''
          _UpperCAmelCase       :       List[str]							   =''.join(snake_case).replace(snake_case  ,							' ').strip()
          return out_string






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  Tuple[str]:




          '''simple docstring'''
          if not os.path.isdir(snake_case):
             logger.error(f"Vocabulary path ({save_directory}) should be a directory")
             return
          _UpperCAmelCase       :       Dict							   =os.path.join(
              snake_case  ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

          if os.path.abspath(self.vocab_file) != os.path.abspath(snake_case) and os.path.isfile(self.vocab_file):
             copyfile(self.vocab_file  ,							snake_case)
          elif not os.path.isfile(self.vocab_file):
             with open(snake_case  ,							'wb') as fi:
                _UpperCAmelCase       :       int							   =self.sp_model.serialized_model_proto()
                fi.write(snake_case)

          return (out_vocab_file,)






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = "en_XX"  ,							snake_case = None  ,							snake_case = "ro_RO"  ,							**snake_case  ,							)						->  BatchEncoding:




          '''simple docstring'''
          _UpperCAmelCase       :       int							   =src_lang
          _UpperCAmelCase       :       Union[str, Any]							   =tgt_lang
          return super().prepare_seqaseq_batch(snake_case  ,							snake_case  ,							**snake_case)






       def       lowerCAmelCase		(      self)						->  Optional[Any]:




          '''simple docstring'''
          return self.set_src_lang_special_tokens(self.src_lang)






       def       lowerCAmelCase		(      self)						->  Optional[Any]:




          '''simple docstring'''
          return self.set_tgt_lang_special_tokens(self.tgt_lang)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  None:




          '''simple docstring'''
          _UpperCAmelCase       :       List[str]							   =self.lang_code_to_id[src_lang]
          _UpperCAmelCase       :       Dict							   =[]
          _UpperCAmelCase       :       Optional[int]							   =[self.eos_token_id, self.cur_lang_code]






       def       lowerCAmelCase		(      self  ,							snake_case)						->  None:




          '''simple docstring'''
          _UpperCAmelCase       :       int							   =self.lang_code_to_id[lang]
          _UpperCAmelCase       :       List[str]							   =[]
          _UpperCAmelCase       :       Optional[int]							   =[self.eos_token_id, self.cur_lang_code]






'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


lowercase							=logging.get_logger(__name__)

lowercase							={
    'facebook/levit-128S': 'https://huggingface.co/facebook/levit-128S/resolve/main/config.json',
    # See all LeViT models at https://huggingface.co/models?filter=levit
}






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="levit"






       def __init__(      self  ,							snake_case=2_2_4  ,							snake_case=3  ,							snake_case=3  ,							snake_case=2  ,							snake_case=1  ,							snake_case=1_6  ,							snake_case=[1_2_8, 2_5_6, 3_8_4]  ,							snake_case=[4, 8, 1_2]  ,							snake_case=[4, 4, 4]  ,							snake_case=[1_6, 1_6, 1_6]  ,							snake_case=0  ,							snake_case=[2, 2, 2]  ,							snake_case=[2, 2, 2]  ,							snake_case=0.02  ,							**snake_case  ,							)						->  Any:




          '''simple docstring'''
          super().__init__(**snake_case)
          _UpperCAmelCase       :       List[str]							   =image_size
          _UpperCAmelCase       :       str							   =num_channels
          _UpperCAmelCase       :       int							   =kernel_size
          _UpperCAmelCase       :       Any							   =stride
          _UpperCAmelCase       :       Tuple							   =padding
          _UpperCAmelCase       :       Optional[int]							   =hidden_sizes
          _UpperCAmelCase       :       List[str]							   =num_attention_heads
          _UpperCAmelCase       :       List[Any]							   =depths
          _UpperCAmelCase       :       Any							   =key_dim
          _UpperCAmelCase       :       List[Any]							   =drop_path_rate
          _UpperCAmelCase       :       int							   =patch_size
          _UpperCAmelCase       :       Tuple							   =attention_ratio
          _UpperCAmelCase       :       Any							   =mlp_ratio
          _UpperCAmelCase       :       Optional[Any]							   =initializer_range
          _UpperCAmelCase       :       str							   =[
              ['Subsample', key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
              ['Subsample', key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
          ]






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										=version.parse("1.11"    )






       @property
       def       lowerCAmelCase		(      self)						->  Mapping[str, Mapping[int, str]]:




          '''simple docstring'''
          return OrderedDict(
              [
                  ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
              ])






       @property
       def       lowerCAmelCase		(      self)						->  float:




          '''simple docstring'''
          return 1E-4

