code: 
  
  
  """simple docstring"""
  
  
  
  
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  					from .tokenization_xglm import XGLMTokenizer
  else:
  					__magic_name__	:   Union[str, Any]          =							None
  
  
  __magic_name__	:   int          =							logging.get_logger(__name__)
  
  __magic_name__	:   str          =							{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}
  
  __magic_name__	:   Optional[int]          =							{
      'vocab_file': {
          'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
      },
      'tokenizer_file': {
          'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json',
      },
  }
  
  __magic_name__	:   Optional[int]          =							{
      'facebook/xglm-564M': 2_0_4_8,
  }
  
  
  
  
  class  __snake_case      (lowerCamelCase     ):
  							__a				   =					VOCAB_FILES_NAMES
  							__a				   =					PRETRAINED_VOCAB_FILES_MAP
  							__a				   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  							__a				   =					['''input_ids''', '''attention_mask''']
  							__a				   =					XGLMTokenizer
  
  
  
  
  							def __init__(    self:						List[str]    ,       A_:						Optional[Any]=None    ,       A_:						Optional[int]=None    ,       A_:						Optional[int]="<s>"    ,       A_:						Optional[Any]="</s>"    ,       A_:						Optional[int]="</s>"    ,       A_:						List[str]="<s>"    ,       A_:						List[Any]="<unk>"    ,       A_:						int="<pad>"    ,       **A_:						Dict    ,       ):
  										# Compatibility with the original tokenizer
  										__lowerCamelCase        =			7
  										__lowerCamelCase        =			[f'<madeupword{i}>' for i in range(self.num_madeup_words      )]
  
  										__lowerCamelCase        =			kwargs.get("""additional_special_tokens"""    ,       []      )
  										kwargs["additional_special_tokens"] += [
  										    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
  										]
  
  										super().__init__(
  										    A_    ,       tokenizer_file=A_    ,       bos_token=A_    ,       eos_token=A_    ,       sep_token=A_    ,       cls_token=A_    ,       unk_token=A_    ,       pad_token=A_    ,       **A_    ,       )
  
  										__lowerCamelCase        =			vocab_file
  										__lowerCamelCase        =			False if not self.vocab_file else True
  
  
  
  
  							def      __a      (    self:						Dict    ,       A_:						List[int]    ,       A_:						Optional[List[int]] = None      ):
  
  										if token_ids_a is None:
  													return [self.sep_token_id] + token_ids_a
  										__lowerCamelCase        =			[self.sep_token_id]
  										return sep + token_ids_a + sep + sep + token_ids_a
  
  
  
  
  							def      __a      (    self:						Tuple    ,       A_:						List[int]    ,       A_:						Optional[List[int]] = None      ):
  										__lowerCamelCase        =			[self.sep_token_id]
  
  										if token_ids_a is None:
  													return len(sep + token_ids_a      ) * [0]
  										return len(sep + token_ids_a + sep + sep + token_ids_a      ) * [0]
  
  
  
  
  							def      __a      (    self:						Union[str, Any]    ,       A_:						str    ,       A_:						Optional[str] = None      ):
  										if not self.can_save_slow_tokenizer:
  													raise ValueError(
  													    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
  													    """tokenizer."""      )
  
  										if not os.path.isdir(A_      ):
  													logger.error(f'Vocabulary path ({save_directory}) should be a directory.'      )
  													return
  										__lowerCamelCase        =			os.path.join(
  										    A_    ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )
  
  										if os.path.abspath(self.vocab_file      ) != os.path.abspath(A_      ):
  													copyfile(self.vocab_file    ,       A_      )
  
  										return (out_vocab_file,)
  
  
  
  
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  import unittest
  
  from transformers import load_tool
  from transformers.tools.agent_types import AGENT_TYPE_MAPPING
  
  from .test_tools_common import ToolTesterMixin, output_types
  
  
  
  
  class  __snake_case      (unittest.TestCase ,		lowerCamelCase     ):
  
  
  
  
  							def      __a      (    self:						Optional[Any]      ):
  										__lowerCamelCase        =			load_tool("""translation"""      )
  										self.tool.setup()
  										__lowerCamelCase        =			load_tool("""translation"""    ,       remote=A_      )
  
  
  
  
  							def      __a      (    self:						int      ):
  										__lowerCamelCase        =			self.tool("""Hey, what's up?"""    ,       src_lang="""English"""    ,       tgt_lang="""French"""      )
  										self.assertEqual(A_    ,       """- Hé, comment ça va?"""      )
  
  
  
  
  							def      __a      (    self:						int      ):
  										__lowerCamelCase        =			self.remote_tool("""Hey, what's up?"""    ,       src_lang="""English"""    ,       tgt_lang="""French"""      )
  										self.assertEqual(A_    ,       """- Hé, comment ça va?"""      )
  
  
  
  
  							def      __a      (    self:						Union[str, Any]      ):
  										__lowerCamelCase        =			self.tool(text="""Hey, what's up?"""    ,       src_lang="""English"""    ,       tgt_lang="""French"""      )
  										self.assertEqual(A_    ,       """- Hé, comment ça va?"""      )
  
  
  
  
  							def      __a      (    self:						Any      ):
  										__lowerCamelCase        =			self.remote_tool(text="""Hey, what's up?"""    ,       src_lang="""English"""    ,       tgt_lang="""French"""      )
  										self.assertEqual(A_    ,       """- Hé, comment ça va?"""      )
  
  
  
  
  							def      __a      (    self:						List[Any]      ):
  										__lowerCamelCase        =			["""Hey, what's up?""", """English""", """Spanish"""]
  										__lowerCamelCase        =			self.tool(*A_      )
  
  										# There is a single output
  										if len(self.tool.outputs      ) == 1:
  													__lowerCamelCase        =			[outputs]
  
  										self.assertListEqual(output_types(A_      )    ,       self.tool.outputs      )
  
  
  
  
  							def      __a      (    self:						Union[str, Any]      ):
  										__lowerCamelCase        =			["""Hey, what's up?""", """English""", """Spanish"""]
  										__lowerCamelCase        =			self.tool(*A_      )
  
  										if not isinstance(A_    ,       A_      ):
  													__lowerCamelCase        =			[outputs]
  
  										self.assertEqual(len(A_      )    ,       len(self.tool.outputs      )      )
  
  										for output, output_type in zip(A_    ,       self.tool.outputs      ):
  													__lowerCamelCase        =			AGENT_TYPE_MAPPING[output_type]
  													self.assertTrue(isinstance(A_    ,       A_      )      )
  
  
  
  
  							def      __a      (    self:						Dict      ):
  										__lowerCamelCase        =			["""Hey, what's up?""", """English""", """Spanish"""]
  
  										__lowerCamelCase        =			[]
  
  										for _input, input_type in zip(A_    ,       self.tool.inputs      ):
  													if isinstance(A_    ,       A_      ):
  																_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input      ) for _input_type in input_type]      )
  													else:
  																_inputs.append(AGENT_TYPE_MAPPING[input_type](_input      )      )
  
          # Should not raise an error
  										__lowerCamelCase        =			self.tool(*A_      )
  
  										if not isinstance(A_    ,       A_      ):
  													__lowerCamelCase        =			[outputs]
  
  										self.assertEqual(len(A_      )    ,       len(self.tool.outputs      )      )
  
  
  
  
  