import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs



class   lowercase_       (	__snake_case						):



							def __init__(		self ,							lowercase_ ,							lowercase_=None ,							lowercase_=True ,							lowercase_=None ,							**lowercase_							):
													_snake_case		:	Dict							=       parent
													_snake_case		:	int							=       config_class
													_snake_case		:	Union[str, Any]							=       has_text_modality
													_snake_case		:	int							=       kwargs
													_snake_case		:	List[str]							=       common_properties



							def 			UpperCamelCase			(		self							):
													_snake_case		:	int							=       self.config_class(**self.inputs_dict							)
													_snake_case		:	Tuple							=       (
													    ["hidden_size", "num_attention_heads", "num_hidden_layers"]
													    if self.common_properties is None
													    else self.common_properties
													)

													# Add common fields for text models
													if self.has_text_modality:
																			common_properties.extend(["vocab_size"]							)

													# Test that config has the common properties as getters
													for prop in common_properties:
																			self.parent.assertTrue(hasattr(_lowerCAmelCase ,							_lowerCAmelCase							) ,							msg=f"""`{prop}` does not exist"""							)

													# Test that config has the common properties as setter
													for idx, name in enumerate(_lowerCAmelCase							):
																			try:
																									setattr(_lowerCAmelCase ,							_lowerCAmelCase ,							_lowerCAmelCase							)
																									self.parent.assertEqual(
																									    getattr(_lowerCAmelCase ,							_lowerCAmelCase							) ,							_lowerCAmelCase ,							msg=f"""`{name} value {idx} expected, but was {getattr(_lowerCAmelCase ,							_lowerCAmelCase							)}"""							)
																			except NotImplementedError:
																									# Some models might not be able to implement setters for common_properties
																									# In that case, a NotImplementedError is raised
																									pass

																			# Test if config class can be called with Config(prop_name=..)
													for idx, name in enumerate(_lowerCAmelCase							):
																			try:
																									_snake_case		:	str							=       self.config_class(**{name: idx}							)
																									self.parent.assertEqual(
																									    getattr(_lowerCAmelCase ,							_lowerCAmelCase							) ,							_lowerCAmelCase ,							msg=f"""`{name} value {idx} expected, but was {getattr(_lowerCAmelCase ,							_lowerCAmelCase							)}"""							)
																			except NotImplementedError:
																									# Some models might not be able to implement setters for common_properties
																									# In that case, a NotImplementedError is raised
																									pass



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Optional[Any]							=       self.config_class(**self.inputs_dict							)
													_snake_case		:	Optional[int]							=       json.loads(config.to_json_string()							)
													for key, value in self.inputs_dict.items():
																			self.parent.assertEqual(obj[key] ,							_lowerCAmelCase							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Tuple							=       self.config_class(**self.inputs_dict							)

													with tempfile.TemporaryDirectory() as tmpdirname:
																			_snake_case		:	Dict							=       os.path.join(_lowerCAmelCase ,							"config.json"							)
																			config_first.to_json_file(_lowerCAmelCase							)
																			_snake_case		:	Any							=       self.config_class.from_json_file(_lowerCAmelCase							)

													self.parent.assertEqual(config_second.to_dict() ,							config_first.to_dict()							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	str							=       self.config_class(**self.inputs_dict							)

													with tempfile.TemporaryDirectory() as tmpdirname:
																			config_first.save_pretrained(_lowerCAmelCase							)
																			_snake_case		:	Tuple							=       self.config_class.from_pretrained(_lowerCAmelCase							)

													self.parent.assertEqual(config_second.to_dict() ,							config_first.to_dict()							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Any							=       self.config_class(**self.inputs_dict							)

													_snake_case		:	Any							=       "test"
													with tempfile.TemporaryDirectory() as tmpdirname:
																			_snake_case		:	Tuple							=       os.path.join(_lowerCAmelCase ,							_lowerCAmelCase							)
																			config_first.save_pretrained(_lowerCAmelCase							)
																			_snake_case		:	List[Any]							=       self.config_class.from_pretrained(_lowerCAmelCase ,							subfolder=_lowerCAmelCase							)

													self.parent.assertEqual(config_second.to_dict() ,							config_first.to_dict()							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	str							=       self.config_class(**self.inputs_dict ,							num_labels=5							)
													self.parent.assertEqual(len(config.idalabel							) ,							5							)
													self.parent.assertEqual(len(config.labelaid							) ,							5							)

													_snake_case		:	Union[str, Any]							=       3
													self.parent.assertEqual(len(config.idalabel							) ,							3							)
													self.parent.assertEqual(len(config.labelaid							) ,							3							)



							def 			UpperCamelCase			(		self							):
													if self.config_class.is_composition:
																			return
													_snake_case		:	int							=       self.config_class()
													self.parent.assertIsNotNone(_lowerCAmelCase							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Optional[Any]							=       copy.deepcopy(_lowerCAmelCase							)
													_snake_case		:	List[str]							=       self.config_class(**_lowerCAmelCase							)
													_snake_case		:	Optional[int]							=       []
													for key, value in config_common_kwargs.items():
																			if key == "torch_dtype":
																									if not is_torch_available():
																															continue
																									else:
																															import torch

																															if config.torch_dtype != torch.floataa:
																																					wrong_values.append(("torch_dtype", config.torch_dtype, torch.floataa)							)
																			elif getattr(_lowerCAmelCase ,							_lowerCAmelCase							) != value:
																									wrong_values.append((key, getattr(_lowerCAmelCase ,							_lowerCAmelCase							), value)							)

													if len(_lowerCAmelCase							) > 0:
																			_snake_case		:	List[str]							=       "\n".join([f"""- {v[0]}: got {v[1]} instead of {v[2]}""" for v in wrong_values]							)
																			raise ValueError(f"""The following keys were not properly set in the config:\n{errors}"""							)



							def 			UpperCamelCase			(		self							):
													self.create_and_test_config_common_properties()
													self.create_and_test_config_to_json_string()
													self.create_and_test_config_to_json_file()
													self.create_and_test_config_from_and_save_pretrained()
													self.create_and_test_config_from_and_save_pretrained_subfolder()
													self.create_and_test_config_with_num_labels()
													self.check_config_can_be_init_without_params()
													self.check_config_arguments_init()



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


SCREAMING_SNAKE_CASE						:str			=  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						:Dict			=  {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE						:str			=  {
    '''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'''
        ),
    },
}

SCREAMING_SNAKE_CASE						:Tuple			=  {
    '''roberta-base''': 5_12,
    '''roberta-large''': 5_12,
    '''roberta-large-mnli''': 5_12,
    '''distilroberta-base''': 5_12,
    '''roberta-base-openai-detector''': 5_12,
    '''roberta-large-openai-detector''': 5_12,
}


class      __lowerCAmelCase  (			a       ):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE		     =							VOCAB_FILES_NAMES
  _SCREAMING_SNAKE_CASE		     =							PRETRAINED_VOCAB_FILES_MAP
  _SCREAMING_SNAKE_CASE		     =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _SCREAMING_SNAKE_CASE		     =							['input_ids', 'attention_mask']
  _SCREAMING_SNAKE_CASE		     =							RobertaTokenizer



  def __init__(  self							:							Tuple     ,					_lowerCAmelCase							:							Union[str, Any]=None     ,					_lowerCAmelCase							:							Tuple=None     ,					_lowerCAmelCase							:							Any=None     ,					_lowerCAmelCase							:							Optional[Any]="replace"     ,					_lowerCAmelCase							:							str="<s>"     ,					_lowerCAmelCase							:							Tuple="</s>"     ,					_lowerCAmelCase							:							Any="</s>"     ,					_lowerCAmelCase							:							Tuple="<s>"     ,					_lowerCAmelCase							:							Any="<unk>"     ,					_lowerCAmelCase							:							Tuple="<pad>"     ,					_lowerCAmelCase							:							List[str]="<mask>"     ,					_lowerCAmelCase							:							str=False     ,					_lowerCAmelCase							:							Union[str, Any]=True     ,					**_lowerCAmelCase							:							int     ,					) ->			str:




     """simple docstring"""
     super().__init__(
         _lowerCAmelCase     ,					_lowerCAmelCase     ,					tokenizer_file=_lowerCAmelCase     ,					errors=_lowerCAmelCase     ,					bos_token=_lowerCAmelCase     ,					eos_token=_lowerCAmelCase     ,					sep_token=_lowerCAmelCase     ,					cls_token=_lowerCAmelCase     ,					unk_token=_lowerCAmelCase     ,					pad_token=_lowerCAmelCase     ,					mask_token=_lowerCAmelCase     ,					add_prefix_space=_lowerCAmelCase     ,					trim_offsets=_lowerCAmelCase     ,					**_lowerCAmelCase     ,					)

     snake_case_            =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
     if pre_tok_state.get("add_prefix_space"     ,					_lowerCAmelCase	) != add_prefix_space:
        snake_case_            =       getattr(_lowerCAmelCase     ,					pre_tok_state.pop("type"	)	)
        snake_case_            =       add_prefix_space
        snake_case_            =       pre_tok_class(**_lowerCAmelCase	)

     snake_case_            =       add_prefix_space

     snake_case_            =       "post_processor"
     snake_case_            =       getattr(self.backend_tokenizer     ,					_lowerCAmelCase     ,					_lowerCAmelCase	)
     if tokenizer_component_instance:
        snake_case_            =       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:
           snake_case_            =       tuple(state["sep"]	)
        if "cls" in state:
           snake_case_            =       tuple(state["cls"]	)

        snake_case_            =       False

        if state.get("add_prefix_space"     ,					_lowerCAmelCase	) != add_prefix_space:
           snake_case_            =       add_prefix_space
           snake_case_            =       True

        if state.get("trim_offsets"     ,					_lowerCAmelCase	) != trim_offsets:
           snake_case_            =       trim_offsets
           snake_case_            =       True

        if changes_to_apply:
           snake_case_            =       getattr(_lowerCAmelCase     ,					state.pop("type"	)	)
           snake_case_            =       component_class(**_lowerCAmelCase	)
           setattr(self.backend_tokenizer     ,					_lowerCAmelCase     ,					_lowerCAmelCase	)



  @property
  def        lowerCAmelCase__	(  self							:							Dict	) ->			str:




     """simple docstring"""
     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							:							Tuple     ,					_lowerCAmelCase							:							Tuple	) ->			Optional[int]:




     """simple docstring"""
     snake_case_            =       AddedToken(_lowerCAmelCase     ,					lstrip=_lowerCAmelCase     ,					rstrip=_lowerCAmelCase	) if isinstance(_lowerCAmelCase     ,					_lowerCAmelCase	) else value
     snake_case_            =       value



  def        lowerCAmelCase__	(  self							:							Dict     ,					*_lowerCAmelCase							:							Optional[int]     ,					**_lowerCAmelCase							:							Optional[int]	) ->			BatchEncoding:




     """simple docstring"""
     snake_case_            =       kwargs.get("is_split_into_words"     ,					_lowerCAmelCase	)
     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(*_lowerCAmelCase     ,					**_lowerCAmelCase	)



  def        lowerCAmelCase__	(  self							:							Optional[Any]     ,					*_lowerCAmelCase							:							str     ,					**_lowerCAmelCase							:							Any	) ->			BatchEncoding:




     """simple docstring"""
     snake_case_            =       kwargs.get("is_split_into_words"     ,					_lowerCAmelCase	)

     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(*_lowerCAmelCase     ,					**_lowerCAmelCase	)



  def        lowerCAmelCase__	(  self							:							int     ,					_lowerCAmelCase							:							str     ,					_lowerCAmelCase							:							Optional[str] = None	) ->			Tuple[str]:




     """simple docstring"""
     snake_case_            =       self._tokenizer.model.save(_lowerCAmelCase     ,					name=_lowerCAmelCase	)
     return tuple(_lowerCAmelCase	)



  def        lowerCAmelCase__	(  self							:							Any     ,					_lowerCAmelCase							:							int     ,					_lowerCAmelCase							:							List[Any]=None	) ->			Union[str, Any]:




     """simple docstring"""
     snake_case_            =       [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							:							Union[str, Any]     ,					_lowerCAmelCase							:							List[int]     ,					_lowerCAmelCase							:							Optional[List[int]] = None	) ->			List[int]:




     """simple docstring"""
     snake_case_            =       [self.sep_token_id]
     snake_case_            =       [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]




