


"""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,)








"""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      )      )




