






'''simple docstring'''







import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


_A	:			List[Any]         =logging.get_logger(__name__)

_A	:			List[str]         ={'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_A	:			Optional[Any]         ={
    '''vocab_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/vocab.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/vocab.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/vocab.json''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/merges.txt''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/merges.txt''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/merges.txt''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/tokenizer.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/tokenizer.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json''',
        '''roberta-base-openai-detector''': (
            '''https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'''
        ),
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'''
        ),
    },
}

_A	:			Optional[Any]         ={
    '''roberta-base''': 512,
    '''roberta-large''': 512,
    '''roberta-large-mnli''': 512,
    '''distilroberta-base''': 512,
    '''roberta-base-openai-detector''': 512,
    '''roberta-large-openai-detector''': 512,
}

class _lowercase	(				_lowercase		):
							a				      =       VOCAB_FILES_NAMES
							a				      =       PRETRAINED_VOCAB_FILES_MAP
							a				      =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							a				      =       ["""input_ids""", """attention_mask"""]
							a				      =       RobertaTokenizer




							def __init__(							self:				List[str]			,							UpperCamelCase__:				Union[str, Any]=None			,							UpperCamelCase__:				Dict=None			,							UpperCamelCase__:				int=None			,							UpperCamelCase__:				List[Any]="replace"			,							UpperCamelCase__:				List[Any]="<s>"			,							UpperCamelCase__:				Optional[Any]="</s>"			,							UpperCamelCase__:				str="</s>"			,							UpperCamelCase__:				List[Any]="<s>"			,							UpperCamelCase__:				Union[str, Any]="<unk>"			,							UpperCamelCase__:				Dict="<pad>"			,							UpperCamelCase__:				Any="<mask>"			,							UpperCamelCase__:				str=False			,							UpperCamelCase__:				List[Any]=True			,							**UpperCamelCase__:				int			,							):
														super().__init__(
														    UpperCamelCase__			,							UpperCamelCase__			,							tokenizer_file=UpperCamelCase__			,							errors=UpperCamelCase__			,							bos_token=UpperCamelCase__			,							eos_token=UpperCamelCase__			,							sep_token=UpperCamelCase__			,							cls_token=UpperCamelCase__			,							unk_token=UpperCamelCase__			,							pad_token=UpperCamelCase__			,							mask_token=UpperCamelCase__			,							add_prefix_space=UpperCamelCase__			,							trim_offsets=UpperCamelCase__			,							**UpperCamelCase__			,							)

														lowerCamelCase__					:	Optional[Any]         =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
														if pre_tok_state.get("""add_prefix_space"""			,							UpperCamelCase__     ) != add_prefix_space:
																					lowerCamelCase__					:	int         =       getattr(UpperCamelCase__			,							pre_tok_state.pop("""type"""     )     )
																					lowerCamelCase__					:	Dict         =       add_prefix_space
																					lowerCamelCase__					:	Union[str, Any]         =       pre_tok_class(**UpperCamelCase__     )

														lowerCamelCase__					:	Any         =       add_prefix_space

														lowerCamelCase__					:	List[Any]         =       """post_processor"""
														lowerCamelCase__					:	Optional[Any]         =       getattr(self.backend_tokenizer			,							UpperCamelCase__			,							UpperCamelCase__     )
														if tokenizer_component_instance:
																					lowerCamelCase__					:	int         =       json.loads(tokenizer_component_instance.__getstate__()     )

																					# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																					if "sep" in state:
																												lowerCamelCase__					:	Optional[Any]         =       tuple(state["""sep"""]     )
																					if "cls" in state:
																												lowerCamelCase__					:	List[Any]         =       tuple(state["""cls"""]     )

																					lowerCamelCase__					:	int         =       False

																					if state.get("""add_prefix_space"""			,							UpperCamelCase__     ) != add_prefix_space:
																												lowerCamelCase__					:	Optional[Any]         =       add_prefix_space
																												lowerCamelCase__					:	Any         =       True

																					if state.get("""trim_offsets"""			,							UpperCamelCase__     ) != trim_offsets:
																												lowerCamelCase__					:	Optional[Any]         =       trim_offsets
																												lowerCamelCase__					:	Tuple         =       True

																					if changes_to_apply:
																												lowerCamelCase__					:	Optional[int]         =       getattr(UpperCamelCase__			,							state.pop("""type"""     )     )
																												lowerCamelCase__					:	Any         =       component_class(**UpperCamelCase__     )
																												setattr(self.backend_tokenizer			,							UpperCamelCase__			,							UpperCamelCase__     )




							@property
							def 		lowerCamelCase_				(							self:				Union[str, Any]     ):
														if self._mask_token is None:
																					if self.verbose:
																												logger.error("""Using mask_token, but it is not set yet."""     )
																					return None
														return str(self._mask_token     )




							@mask_token.setter
							def 		lowerCamelCase_				(							self:				str			,							UpperCamelCase__:				int     ):
														lowerCamelCase__					:	int         =       AddedToken(UpperCamelCase__			,							lstrip=UpperCamelCase__			,							rstrip=UpperCamelCase__     ) if isinstance(UpperCamelCase__			,							UpperCamelCase__     ) else value
														lowerCamelCase__					:	str         =       value




							def 		lowerCamelCase_				(							self:				Any			,							*UpperCamelCase__:				Optional[int]			,							**UpperCamelCase__:				Optional[int]     ):
														lowerCamelCase__					:	List[str]         =       kwargs.get("""is_split_into_words"""			,							UpperCamelCase__     )
														assert self.add_prefix_space or not is_split_into_words, (
														    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
														    "to use it with pretokenized inputs."
														)

														return super()._batch_encode_plus(*UpperCamelCase__			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Any			,							*UpperCamelCase__:				Any			,							**UpperCamelCase__:				Optional[Any]     ):
														lowerCamelCase__					:	int         =       kwargs.get("""is_split_into_words"""			,							UpperCamelCase__     )

														assert self.add_prefix_space or not is_split_into_words, (
														    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
														    "to use it with pretokenized inputs."
														)

														return super()._encode_plus(*UpperCamelCase__			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				str			,							UpperCamelCase__:				str			,							UpperCamelCase__:				Optional[str] = None     ):
														lowerCamelCase__					:	Any         =       self._tokenizer.model.save(UpperCamelCase__			,							name=UpperCamelCase__     )
														return tuple(UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Dict			,							UpperCamelCase__:				Any			,							UpperCamelCase__:				int=None     ):
														lowerCamelCase__					:	Tuple         =       [self.bos_token_id] + token_ids_a + [self.eos_token_id]
														if token_ids_a is None:
																					return output

														return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




							def 		lowerCamelCase_				(							self:				Optional[Any]			,							UpperCamelCase__:				List[int]			,							UpperCamelCase__:				Optional[List[int]] = None     ):
														lowerCamelCase__					:	Optional[int]         =       [self.sep_token_id]
														lowerCamelCase__					:	Optional[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]



import json
import sys





def     _a					(						lowerCamelCase,	lowerCamelCase							):
 with open(lowerCamelCase,	encoding="""utf-8"""							) as f:
  lowerCamelCase		:	List[Any]							=      json.load(lowerCamelCase							)

 lowerCamelCase		:	Optional[Any]							=      ["""<details>""", """<summary>Show updated benchmarks!</summary>""", """ """]

 for benchmark_name in sorted(lowerCamelCase							):
  lowerCamelCase		:	List[Any]							=      results[benchmark_name]

  lowerCamelCase		:	Union[str, Any]							=      benchmark_name.split("""/"""							)[-1]
  output_md.append(F'''### Benchmark: {benchmark_file_name}'''							)

  lowerCamelCase		:	Any							=      """| metric |"""
  lowerCamelCase		:	str							=      """|--------|"""
  lowerCamelCase		:	List[Any]							=      """| new / old (diff) |"""
  for metric_name in sorted(lowerCamelCase							):
   lowerCamelCase		:	List[Any]							=      benchmark_res[metric_name]
   lowerCamelCase		:	Tuple							=      metric_vals["""new"""]
   lowerCamelCase		:	int							=      metric_vals.get("""old""",	lowerCamelCase							)
   lowerCamelCase		:	Dict							=      metric_vals.get("""diff""",	lowerCamelCase							)

   lowerCamelCase		:	Dict							=      F''' {new_val:f}''' if isinstance(lowerCamelCase,	(int, float)							) else """None"""

   if old_val is not None:
    val_str += F''' / {old_val:f}''' if isinstance(lowerCamelCase,	(int, float)							) else "None"
   if dif_val is not None:
    val_str += F''' ({dif_val:f})''' if isinstance(lowerCamelCase,	(int, float)							) else "None"

   title += " " + metric_name + " |"
   lines += "---|"
   value += val_str + " |"

  output_md += [title, lines, value, " "]

 output_md.append("""</details>"""							)

 with open(lowerCamelCase,	"""w""",	encoding="""utf-8"""							) as f:
  f.writelines("""\n""".join(lowerCamelCase							)							)


if __name__ == "__main__":
      _lowerCamelCase					   =sys.argv[1]
      _lowerCamelCase					   =sys.argv[2]

      format_json_to_md(input_json_file, output_md_file)




