import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu







@require_cpu
class __snake_case       (		unittest.TestCase	):




   def 			__a		(					self    :       Any   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   torch.nn.Linear(10 ,			10   )
     SCREAMING_SNAKE_CASE__    							=   torch.optim.SGD(model.parameters() ,			0.1   )
     SCREAMING_SNAKE_CASE__    							=   Accelerator()
     SCREAMING_SNAKE_CASE__    							=   accelerator.prepare(_lowercase   )
     try:
       pickle.loads(pickle.dumps(_lowercase   )   )
     except Exception as e:
       self.fail(f"""Accelerated optimizer pickling failed with {e}"""   )
     AcceleratorState._reset_state()

import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
   import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__lowerCamelCase    :				Any							     =	logging.get_logger(__name__)

__lowerCamelCase    :				Optional[Any]							     =	{'''vocab_file''': '''vocab.txt'''}

__lowerCamelCase    :				Union[str, Any]							     =	{
    '''vocab_file''': {
        '''openbmb/cpm-ant-10b''': '''https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt''',
    },
}

__lowerCamelCase    :				Optional[Any]							     =	{
    '''openbmb/cpm-ant-10b''': 1024,
}



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: str			)							->      Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   collections.OrderedDict()
  with open(__UpperCamelCase				,  """r"""				,  encoding="""utf-8"""			) as reader:
    SCREAMING_SNAKE_CASE__    							=   reader.readlines()
  for index, token in enumerate(__UpperCamelCase			):
    SCREAMING_SNAKE_CASE__    							=   token.rstrip("""\n"""			)
    SCREAMING_SNAKE_CASE__    							=   index
  return vocab







class __snake_case       (		lowerCamelCase_	):




   def __init__(					self    :       Optional[int] ,			_lowercase    :       Optional[Any] ,			_lowercase    :       int="<unk>" ,			_lowercase    :       int=2_00   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   vocab
     SCREAMING_SNAKE_CASE__    							=   unk_token
     SCREAMING_SNAKE_CASE__    							=   max_input_chars_per_word




   def 			__a		(					self    :       Optional[int] ,			_lowercase    :       List[Any]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   list(_lowercase   )
     if len(_lowercase   ) > self.max_input_chars_per_word:
       return [self.unk_token]

     SCREAMING_SNAKE_CASE__    							=   0
     SCREAMING_SNAKE_CASE__    							=   []
     while start < len(_lowercase   ):
       SCREAMING_SNAKE_CASE__    							=   len(_lowercase   )
       SCREAMING_SNAKE_CASE__    							=   None
       while start < end:
         SCREAMING_SNAKE_CASE__    							=   """""".join(chars[start:end]   )
         if substr in self.vocab:
           SCREAMING_SNAKE_CASE__    							=   substr
           break
         end -= 1
       if cur_substr is None:
         sub_tokens.append(self.unk_token   )
         start += 1
       else:
         sub_tokens.append(_lowercase   )
         SCREAMING_SNAKE_CASE__    							=   end

     return sub_tokens







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							VOCAB_FILES_NAMES
   lowerCAmelCase_														=							PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase_														=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase_														=							["input_ids", "attention_mask"]
   lowerCAmelCase_														=							False




   def __init__(					self    :       int ,			_lowercase    :       str ,			_lowercase    :       List[Any]="<d>" ,			_lowercase    :       List[Any]="</d>" ,			_lowercase    :       Union[str, Any]="<s>" ,			_lowercase    :       List[str]="</s>" ,			_lowercase    :       str="<pad>" ,			_lowercase    :       int="<unk>" ,			_lowercase    :       List[str]="</n>" ,			_lowercase    :       Tuple="</_>" ,			_lowercase    :       Any="left" ,			**_lowercase    :       Any ,			):



     """simple docstring"""






     requires_backends(self ,			["""jieba"""]   )
     super().__init__(
         bod_token=_lowercase ,			eod_token=_lowercase ,			bos_token=_lowercase ,			eos_token=_lowercase ,			pad_token=_lowercase ,			unk_token=_lowercase ,			line_token=_lowercase ,			space_token=_lowercase ,			padding_side=_lowercase ,			**_lowercase ,			)
     SCREAMING_SNAKE_CASE__    							=   bod_token
     SCREAMING_SNAKE_CASE__    							=   eod_token
     SCREAMING_SNAKE_CASE__    							=   load_vocab(_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   self.encoder[space_token]
     SCREAMING_SNAKE_CASE__    							=   self.encoder[line_token]

     del self.encoder[space_token]
     del self.encoder[line_token]

     SCREAMING_SNAKE_CASE__    							=   collections.OrderedDict(sorted(self.encoder.items() ,			key=lambda _lowercase   : x[1]   )   )
     SCREAMING_SNAKE_CASE__    							=   {v: k for k, v in self.encoder.items()}

     SCREAMING_SNAKE_CASE__    							=   WordpieceTokenizer(vocab=self.encoder ,			unk_token=self.unk_token   )




   @property
   def 			__a		(					self    :       Optional[Any]   ):



     """simple docstring"""






     return self.encoder[self.bod_token]




   @property
   def 			__a		(					self    :       List[Any]   ):



     """simple docstring"""






     return self.encoder[self.eod_token]




   @property
   def 			__a		(					self    :       Any   ):



     """simple docstring"""






     return self.encoder["\n"]




   @property
   def 			__a		(					self    :       Union[str, Any]   ):



     """simple docstring"""






     return len(self.encoder   )




   def 			__a		(					self    :       int   ):



     """simple docstring"""






     return dict(self.encoder ,			**self.added_tokens_encoder   )




   def 			__a		(					self    :       Union[str, Any] ,			_lowercase    :       str   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   []
     for x in jieba.cut(_lowercase ,			cut_all=_lowercase   ):
       output_tokens.extend(self.wordpiece_tokenizer.tokenize(_lowercase   )   )
     return output_tokens




   def 			__a		(					self    :       int ,			_lowercase    :       Any ,			**_lowercase    :       Any   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   [i for i in token_ids if i >= 0]
     SCREAMING_SNAKE_CASE__    							=   [
         x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
     ]
     return super()._decode(_lowercase ,			**_lowercase   )




   def 			__a		(					self    :       Optional[int] ,			_lowercase    :       List[Any]   ):



     """simple docstring"""






     return token in self.encoder




   def 			__a		(					self    :       List[str] ,			_lowercase    :       List[str]   ):



     """simple docstring"""






     return "".join(_lowercase   )




   def 			__a		(					self    :       Optional[int] ,			_lowercase    :       Any   ):



     """simple docstring"""






     return self.encoder.get(_lowercase ,			self.encoder.get(self.unk_token   )   )




   def 			__a		(					self    :       Tuple ,			_lowercase    :       List[Any]   ):



     """simple docstring"""






     return self.decoder.get(_lowercase ,			self.unk_token   )




   def 			__a		(					self    :       Optional[Any] ,			_lowercase    :       str ,			_lowercase    :       Optional[str] = None   ):



     """simple docstring"""






     if os.path.isdir(_lowercase   ):
       SCREAMING_SNAKE_CASE__    							=   os.path.join(
           _lowercase ,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )
     else:
       SCREAMING_SNAKE_CASE__    							=   (filename_prefix + """-""" if filename_prefix else """""") + save_directory
     SCREAMING_SNAKE_CASE__    							=   0
     if " " in self.encoder:
       SCREAMING_SNAKE_CASE__    							=   self.encoder[""" """]
       del self.encoder[" "]
     if "\n" in self.encoder:
       SCREAMING_SNAKE_CASE__    							=   self.encoder["""\n"""]
       del self.encoder["\n"]
     SCREAMING_SNAKE_CASE__    							=   collections.OrderedDict(sorted(self.encoder.items() ,			key=lambda _lowercase   : x[1]   )   )
     with open(_lowercase ,			"""w""" ,			encoding="""utf-8"""   ) as writer:
       for token, token_index in self.encoder.items():
         if index != token_index:
           logger.warning(
               f"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
               """ Please check that the vocabulary is not corrupted!"""   )
           SCREAMING_SNAKE_CASE__    							=   token_index
         writer.write(token + """\n"""   )
         index += 1
     return (vocab_file,)




   def 			__a		(					self    :       int ,			_lowercase    :       List[int] ,			_lowercase    :       List[int] = None   ):



     """simple docstring"""






     if token_ids_a is None:
       return [self.bos_token_id] + token_ids_a
     return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a




   def 			__a		(					self    :       Union[str, Any] ,			_lowercase    :       List[int] ,			_lowercase    :       Optional[List[int]] = None ,			_lowercase    :       bool = False   ):



     """simple docstring"""






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

     if token_ids_a is not None:
       return [1] + ([0] * len(_lowercase   )) + [1] + ([0] * len(_lowercase   ))
     return [1] + ([0] * len(_lowercase   ))
