

'''simple docstring'''

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


lowercase__         =      logging.get_logger(__name__)


lowercase__         =      {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

lowercase__         =      {
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
}

lowercase__         =      {
    "allenai/longformer-base-4096": 4096,
    "allenai/longformer-large-4096": 4096,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4096,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4096,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4096,
}




@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 				UpperCamelCase(					):
 UpperCAmelCase	:     Optional[Any]						 =			(
     list(range(ord('!'     )  ,	ord('~'     ) + 1     )     ) + list(range(ord('¡'     )  ,	ord('¬'     ) + 1     )     ) + list(range(ord('®'     )  ,	ord('ÿ'     ) + 1     )     )
 )
 UpperCAmelCase	:     Tuple						 =			bs[:]
 UpperCAmelCase	:     Dict						 =			0
 for b in range(2**8     ):
  if b not in bs:
   bs.append(__a     )
   cs.append(2**8 + n     )
   n += 1
 UpperCAmelCase	:     Union[str, Any]						 =			[chr(__a     ) for n in cs]
 return dict(zip(__a  ,	__a     )     )




def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     Optional[int]						 =			set()
 UpperCAmelCase	:     Tuple						 =			word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)     )
  UpperCAmelCase	:     Any						 =			char
 return pairs




class 	A_			(    __lowercase							):






     '''simple docstring'''



     UpperCAmelCase_						:     str  		=  VOCAB_FILES_NAMES
     UpperCAmelCase_						:     Dict  		=  PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase_						:     Tuple  		=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase_						:     Optional[int]  		=  ["""input_ids""", """attention_mask"""]


     def __init__(		self			:					Any					,      lowercase_			:					Dict					,      lowercase_			:					str					,      lowercase_			:					Union[str, Any]="replace"					,      lowercase_			:					Union[str, Any]="<s>"					,      lowercase_			:					List[str]="</s>"					,      lowercase_			:					Optional[int]="</s>"					,      lowercase_			:					Any="<s>"					,      lowercase_			:					str="<unk>"					,      lowercase_			:					List[Any]="<pad>"					,      lowercase_			:					Dict="<mask>"					,      lowercase_			:					Any=False					,      **lowercase_			:					Tuple					,      )						->     Tuple:
      UpperCAmelCase	:     Union[str, Any]						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else bos_token
      UpperCAmelCase	:     Dict						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else eos_token
      UpperCAmelCase	:     List[str]						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else sep_token
      UpperCAmelCase	:     List[Any]						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else cls_token
      UpperCAmelCase	:     List[Any]						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else unk_token
      UpperCAmelCase	:     Optional[int]						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      UpperCAmelCase	:     Any						 =			AddedToken(_a					,      lstrip=_a					,      rstrip=_a	) if isinstance(_a					,      _a	) else mask_token

      super().__init__(
          errors=_a					,      bos_token=_a					,      eos_token=_a					,      unk_token=_a					,      sep_token=_a					,      cls_token=_a					,      pad_token=_a					,      mask_token=_a					,      add_prefix_space=_a					,      **_a					,      )

      with open(_a					,      encoding='utf-8'	) as vocab_handle:
       UpperCAmelCase	:     List[Any]						 =			json.load(_a	)
      UpperCAmelCase	:     Optional[int]						 =			{v: k for k, v in self.encoder.items()}
      UpperCAmelCase	:     List[str]						 =			errors  # how to handle errors in decoding
      UpperCAmelCase	:     Optional[Any]						 =			bytes_to_unicode()
      UpperCAmelCase	:     str						 =			{v: k for k, v in self.byte_encoder.items()}
      with open(_a					,      encoding='utf-8'	) as merges_handle:
       UpperCAmelCase	:     Tuple						 =			merges_handle.read().split('\n'	)[1:-1]
      UpperCAmelCase	:     Tuple						 =			[tuple(merge.split()	) for merge in bpe_merges]
      UpperCAmelCase	:     Union[str, Any]						 =			dict(zip(_a					,      range(len(_a	)	)	)	)
      UpperCAmelCase	:     int						 =			{}
      UpperCAmelCase	:     List[Any]						 =			add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      UpperCAmelCase	:     Optional[int]						 =			re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'	)


     @property
     def        UpperCAmelCase_	(		self			:					Optional[Any]	)						->     Optional[int]:
      return len(self.encoder	)


     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     Optional[Any]:
      return dict(self.encoder					,      **self.added_tokens_encoder	)


     def        UpperCAmelCase_	(		self			:					List[str]					,      lowercase_			:					List[str]	)						->     int:
      if token in self.cache:
       return self.cache[token]
      UpperCAmelCase	:     List[Any]						 =			tuple(_a	)
      UpperCAmelCase	:     Optional[Any]						 =			get_pairs(_a	)

      if not pairs:
       return token

      while True:
       UpperCAmelCase	:     Optional[int]						 =			min(_a					,      key=lambda lowercase_	: self.bpe_ranks.get(_a					,      float('inf'	)	)	)
       if bigram not in self.bpe_ranks:
        break
       UpperCAmelCase ,			UpperCAmelCase	:     List[str]						 =			bigram
       UpperCAmelCase	:     List[Any]						 =			[]
       UpperCAmelCase	:     List[Any]						 =			0
       while i < len(_a	):
        try:
         UpperCAmelCase	:     str						 =			word.index(_a					,      _a	)
        except ValueError:
         new_word.extend(word[i:]	)
         break
        else:
         new_word.extend(word[i:j]	)
         UpperCAmelCase	:     List[str]						 =			j

        if word[i] == first and i < len(_a	) - 1 and word[i + 1] == second:
         new_word.append(first + second	)
         i += 2
        else:
         new_word.append(word[i]	)
         i += 1
       UpperCAmelCase	:     Any						 =			tuple(_a	)
       UpperCAmelCase	:     Optional[Any]						 =			new_word
       if len(_a	) == 1:
        break
       else:
        UpperCAmelCase	:     Optional[int]						 =			get_pairs(_a	)
      UpperCAmelCase	:     Optional[int]						 =			' '.join(_a	)
      UpperCAmelCase	:     Dict						 =			word
      return word


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					Tuple	)						->     Tuple:
      UpperCAmelCase	:     int						 =			[]
      for token in re.findall(self.pat					,      _a	):
       UpperCAmelCase	:     Dict						 =			''.join(
           self.byte_encoder[b] for b in token.encode('utf-8'	)	)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
       bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_a	).split(' '	)	)
      return bpe_tokens


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					List[Any]	)						->     int:
      return self.encoder.get(_a					,      self.encoder.get(self.unk_token	)	)


     def        UpperCAmelCase_	(		self			:					Union[str, Any]					,      lowercase_			:					Optional[Any]	)						->     Any:
      return self.decoder.get(_a	)


     def        UpperCAmelCase_	(		self			:					str					,      lowercase_			:					Any	)						->     List[Any]:
      UpperCAmelCase	:     int						 =			''.join(_a	)
      UpperCAmelCase	:     Optional[int]						 =			bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'					,      errors=self.errors	)
      return text


     def        UpperCAmelCase_	(		self			:					str					,      lowercase_			:					Union[str, Any]					,      lowercase_			:					Union[str, Any] = None	)						->     Tuple[str]:
      if not os.path.isdir(_a	):
       logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
       return
      UpperCAmelCase	:     Tuple						 =			os.path.join(
          _a					,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
      UpperCAmelCase	:     Tuple						 =			os.path.join(
          _a					,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']	)

      with open(_a					,      'w'					,      encoding='utf-8'	) as f:
       f.write(json.dumps(self.encoder					,      indent=2					,      sort_keys=_a					,      ensure_ascii=_a	) + '\n'	)

      UpperCAmelCase	:     int						 =			0
      with open(_a					,      'w'					,      encoding='utf-8'	) as writer:
       writer.write('#version: 0.2\n'	)
       for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,      key=lambda lowercase_	: kv[1]	):
        if index != token_index:
         logger.warning(
             f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
             ' Please check that the tokenizer is not corrupted!'	)
         UpperCAmelCase	:     List[str]						 =			token_index
        writer.write(' '.join(_a	) + '\n'	)
        index += 1

      return vocab_file, merge_file


     def        UpperCAmelCase_	(		self			:					Tuple					,      lowercase_			:					Any					,      lowercase_			:					Optional[Any] = None	)						->     List[int]:
      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      UpperCAmelCase	:     str						 =			[self.cls_token_id]
      UpperCAmelCase	:     Optional[Any]						 =			[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					Dict					,      lowercase_			:					List[Any] = None					,      lowercase_			:					int = False	)						->     List[int]:
      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=_a					,      token_ids_a=_a					,      already_has_special_tokens=_a	)

      if token_ids_a is None:
       return [1] + ([0] * len(_a	)) + [1]
      return [1] + ([0] * len(_a	)) + [1, 1] + ([0] * len(_a	)) + [1]


     def        UpperCAmelCase_	(		self			:					List[str]					,      lowercase_			:					List[Any]					,      lowercase_			:					List[str] = None	)						->     List[int]:
      UpperCAmelCase	:     Tuple						 =			[self.sep_token_id]
      UpperCAmelCase	:     Dict						 =			[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        UpperCAmelCase_	(		self			:					Optional[Any]					,      lowercase_			:					Dict					,      lowercase_			:					Any=False					,      **lowercase_			:					Optional[Any]	)						->     Tuple:
      UpperCAmelCase	:     Optional[Any]						 =			kwargs.pop('add_prefix_space'					,      self.add_prefix_space	)
      if (is_split_into_words or add_prefix_space) and (len(_a	) > 0 and not text[0].isspace()):
       UpperCAmelCase	:     Optional[Any]						 =			' ' + text
      return (text, kwargs)







'''simple docstring'''

import inspect
import os
import unittest

import torch

import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment




class 	A_			(    unittest.TestCase							):






     '''simple docstring'''



     def        UpperCAmelCase_	(		self			:					str	)						->     Tuple:
      UpperCAmelCase	:     Any						 =			inspect.getfile(accelerate.test_utils	)
      UpperCAmelCase	:     Dict						 =			os.path.sep.join(mod_file.split(os.path.sep	)[:-1] + ['scripts', 'test_script.py']	)
      UpperCAmelCase	:     Dict						 =			os.path.sep.join(
          mod_file.split(os.path.sep	)[:-1] + ['scripts', 'test_distributed_data_loop.py']	)
      UpperCAmelCase	:     List[Any]						 =			os.path.sep.join(mod_file.split(os.path.sep	)[:-1] + ['scripts', 'test_ops.py']	)


     @require_multi_gpu
     def        UpperCAmelCase_	(		self			:					Optional[Any]	)						->     Optional[int]:
      print(f"""Found {torch.cuda.device_count()} devices."""	)
      UpperCAmelCase	:     Dict						 =			['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
      with patch_environment(omp_num_threads=1	):
       execute_subprocess_async(lowercase_					,      env=os.environ.copy()	)


     @require_multi_gpu
     def        UpperCAmelCase_	(		self			:					Union[str, Any]	)						->     List[Any]:
      print(f"""Found {torch.cuda.device_count()} devices."""	)
      UpperCAmelCase	:     int						 =			['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", self.operation_file_path]
      print(f"""Command: {cmd}"""	)
      with patch_environment(omp_num_threads=1	):
       execute_subprocess_async(lowercase_					,      env=os.environ.copy()	)


     @require_multi_gpu
     def        UpperCAmelCase_	(		self			:					str	)						->     List[Any]:
      UpperCAmelCase	:     Optional[int]						 =			['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__	)]
      with patch_environment(omp_num_threads=1	):
       execute_subprocess_async(lowercase_					,      env=os.environ.copy()	)




     @require_multi_gpu
     def        UpperCAmelCase_	(		self			:					List[str]	)						->     Optional[Any]:
      print(f"""Found {torch.cuda.device_count()} devices, using 2 devices only"""	)
      UpperCAmelCase	:     Dict						 =			['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", self.data_loop_file_path]
      with patch_environment(omp_num_threads=1					,      cuda_visible_devices='0,1'	):
       execute_subprocess_async(lowercase_					,      env=os.environ.copy()	)


if __name__ == "__main__":
 lowercase__         =      Accelerator()
 lowercase__         =      (accelerator.state.process_index + 2, 10)
 lowercase__         =      torch.randint(0, 10, shape).to(accelerator.device)

 lowercase__         =      ""

 lowercase__         =      accelerator.pad_across_processes(tensor)
 if tensora.shape[0] != accelerator.state.num_processes + 1:
  error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
 if not torch.equal(tensora[: accelerator.state.process_index + 2], tensor):
  error_msg += "Tensors have different values."
 if not torch.all(tensora[accelerator.state.process_index + 2 :] == 0):
  error_msg += "Padding was not done with the right value (0)."

 lowercase__         =      accelerator.pad_across_processes(tensor, pad_first=True)
 if tensora.shape[0] != accelerator.state.num_processes + 1:
  error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
 lowercase__         =      accelerator.state.num_processes - accelerator.state.process_index - 1
 if not torch.equal(tensora[index:], tensor):
  error_msg += "Tensors have different values."
 if not torch.all(tensora[:index] == 0):
  error_msg += "Padding was not done with the right value (0)."

 # Raise error at the end to make sure we don't stop at the first failure.
 if len(error_msg) > 0:
  raise ValueError(error_msg)




