
'''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_mvp import MvpTokenizer


UpperCamelCase_   	=	logging.get_logger(__name__)


UpperCamelCase_   	=	{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all MVP models at https://huggingface.co/models?filter=mvp
UpperCamelCase_   	=	{
    "vocab_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json",
    },
    "added_tokens.json": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json",
    },
    "merges_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json",
    },
}

UpperCamelCase_   	=	{
    "RUCAIBox/mvp": 1_0_2_4,
}

class       a		(   UpperCAmelCase_					):
							lowercase_		:						Optional[int]   							=  VOCAB_FILES_NAMES
							lowercase_		:						List[str]   							=  PRETRAINED_VOCAB_FILES_MAP
							lowercase_		:						Dict   							=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_		:						Union[str, Any]   							=  ["input_ids", "attention_mask"]
							lowercase_		:						List[str]   							=  MvpTokenizer







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







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

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

								__lowerCAmelCase         =							add_prefix_space

								# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
								__lowerCAmelCase         =							"post_processor"
								__lowerCAmelCase         =							getattr(self.backend_tokenizer      ,				_snake_case      ,				_snake_case )
								if tokenizer_component_instance:
									__lowerCAmelCase         =							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         =							tuple(state["sep"] )
									if "cls" in state:
										__lowerCAmelCase         =							tuple(state["cls"] )

									__lowerCAmelCase         =							False

									if state.get("add_prefix_space"      ,				_snake_case ) != add_prefix_space:
										__lowerCAmelCase         =							add_prefix_space
										__lowerCAmelCase         =							True

									if state.get("trim_offsets"      ,				_snake_case ) != trim_offsets:
										__lowerCAmelCase         =							trim_offsets
										__lowerCAmelCase         =							True

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







							@property
							def       UpperCAmelCase__					(						self  :  Union[str, Any] ):
								"""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       UpperCAmelCase__					(						self  :  str      ,				snake_case__  :  Union[str, Any] ):
								"""simple docstring"""







								__lowerCAmelCase         =							AddedToken(_snake_case      ,				lstrip=_snake_case      ,				rstrip=_snake_case ) if isinstance(_snake_case      ,				_snake_case ) else value
								__lowerCAmelCase         =							value







							def       UpperCAmelCase__					(						self  :  Optional[Any]      ,				*snake_case__  :  Union[str, Any]      ,				**snake_case__  :  Any ):
								"""simple docstring"""







								__lowerCAmelCase         =							kwargs.get("is_split_into_words"      ,				_snake_case )

								if is_split_into_words and not self.add_prefix_space:
									raise ValueError(
									    F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
									    "to use it with pretokenized inputs." )

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







							def       UpperCAmelCase__					(						self  :  Optional[int]      ,				*snake_case__  :  Union[str, Any]      ,				**snake_case__  :  Dict ):
								"""simple docstring"""







								__lowerCAmelCase         =							kwargs.get("is_split_into_words"      ,				_snake_case )

								if is_split_into_words and not self.add_prefix_space:
									raise ValueError(
									    F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
									    "to use it with pretokenized inputs." )

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







							def       UpperCAmelCase__					(						self  :  Tuple      ,				snake_case__  :  str      ,				snake_case__  :  Optional[str] = None ):
								"""simple docstring"""







								__lowerCAmelCase         =							self._tokenizer.model.save(_snake_case      ,				name=_snake_case )
								return tuple(_snake_case )







							def       UpperCAmelCase__					(						self  :  Dict      ,				snake_case__  :  List[str]      ,				snake_case__  :  Optional[int]=None ):
								"""simple docstring"""







								__lowerCAmelCase         =							[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       UpperCAmelCase__					(						self  :  List[str]      ,				snake_case__  :  List[int]      ,				snake_case__  :  Optional[List[int]] = None ):
								"""simple docstring"""







								__lowerCAmelCase         =							[self.sep_token_id]
								__lowerCAmelCase         =							[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 os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


UpperCamelCase_   	=	pytest.mark.integration






@pytest.mark.parametrize("path"			,							["paws", "csv"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	inspect_dataset(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@pytest.mark.filterwarnings("ignore:inspect_metric is deprecated:FutureWarning"  )
@pytest.mark.filterwarnings("ignore:metric_module_factory is deprecated:FutureWarning"  )
@pytest.mark.parametrize("path"			,							["accuracy"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     List[Any]			,							UpperCamelCase:     Any  ):






	"""simple docstring"""


	inspect_metric(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@pytest.mark.parametrize(
    "path, config_name, expected_splits"			,							[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[Any]			,							UpperCamelCase:     int			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )
	assert info.config_name == config_name
	assert list(info.splits.keys()  ) == expected_splits






@pytest.mark.parametrize(
    "path, config_name, expected_exception"			,							[
        ("paws", None, ValueError),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     Any			,							UpperCamelCase:     List[str]  ):






	"""simple docstring"""


	with pytest.raises(UpperCamelCase  ):
		get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )






@pytest.mark.parametrize(
    "path, expected"			,							[
        ("squad", "plain_text"),
        ("acronym_identification", "default"),
        ("lhoestq/squad", "plain_text"),
        ("lhoestq/test", "default"),
        ("lhoestq/demo1", "lhoestq--demo1"),
        ("dalle-mini/wit", "dalle-mini--wit"),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     List[str]			,							UpperCamelCase:     Optional[int]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_names(UpperCamelCase  )
	assert expected in config_names






@pytest.mark.parametrize(
    "path, expected_configs, expected_splits_in_first_config"			,							[
        ("squad", ["plain_text"], ["train", "validation"]),
        ("dalle-mini/wit", ["dalle-mini--wit"], ["train"]),
        ("paws", ["labeled_final", "labeled_swap", "unlabeled_final"], ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     str			,							UpperCamelCase:     Tuple			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert list(infos.keys()  ) == expected_configs
	__lowerCAmelCase         =							expected_configs[0]
	assert expected_config in infos
	__lowerCAmelCase         =							infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()  ) == expected_splits_in_first_config






@pytest.mark.parametrize(
    "path, expected_config, expected_splits"			,							[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     int			,							UpperCamelCase:     Optional[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert expected_config in infos
	__lowerCAmelCase         =							infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()  ) == expected_splits







@pytest.mark.parametrize(
    "path, config_name, expected_exception"			,							[
        ("paws", None, ValueError),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     List[str]			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	with pytest.raises(UpperCamelCase  ):
		get_dataset_split_names(UpperCamelCase			,							config_name=UpperCamelCase  )






