




'''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


a  :				List[str]									=  logging.get_logger(__name__)


a  :				str									=  {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all MVP models at https://huggingface.co/models?filter=mvp
a  :				Union[str, Any]									=  {
    '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',
    },
}

a  :				int									=  {
    'RUCAIBox/mvp': 1024,
}






class 						a				(   _lowerCamelCase     ):
				snake_case_      =		VOCAB_FILES_NAMES
				snake_case_      =		PRETRAINED_VOCAB_FILES_MAP
				snake_case_      =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				snake_case_      =		["input_ids", "attention_mask"]
				snake_case_      =		MvpTokenizer


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

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

									snake_case_									=				add_prefix_space

									# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
									snake_case_									=				'''post_processor'''
									snake_case_									=				getattr(self.backend_tokenizer       ,				lowercase_       ,				lowercase_					)
									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'''       ,				lowercase_					) != add_prefix_space:
																			snake_case_									=				add_prefix_space
																			snake_case_									=				True

														if state.get('''trim_offsets'''       ,				lowercase_					) != trim_offsets:
																			snake_case_									=				trim_offsets
																			snake_case_									=				True

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


				@property
				def   A_ (		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   A_ (		self    :					Optional[Any]       ,				lowercase_    :					Any					):
									snake_case_									=				AddedToken(lowercase_       ,				lstrip=lowercase_       ,				rstrip=lowercase_					) if isinstance(lowercase_       ,				lowercase_					) else value
									snake_case_									=				value


				def   A_ (		self    :					Any       ,				*lowercase_    :					Optional[int]       ,				**lowercase_    :					str					):
									snake_case_									=				kwargs.get('''is_split_into_words'''       ,				lowercase_					)

									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(*lowercase_       ,				**lowercase_					)


				def   A_ (		self    :					str       ,				*lowercase_    :					int       ,				**lowercase_    :					Dict					):
									snake_case_									=				kwargs.get('''is_split_into_words'''       ,				lowercase_					)

									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(*lowercase_       ,				**lowercase_					)


				def   A_ (		self    :					Optional[int]       ,				lowercase_    :					str       ,				lowercase_    :					Optional[str] = None					):
									snake_case_									=				self._tokenizer.model.save(lowercase_       ,				name=lowercase_					)
									return tuple(lowercase_					)


				def   A_ (		self    :					Optional[int]       ,				lowercase_    :					int       ,				lowercase_    :					Optional[Any]=None					):
									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   A_ (		self    :					str       ,				lowercase_    :					List[int]       ,				lowercase_    :					Optional[List[int]] = None					):
									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]







'''simple docstring'''

# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
a  :				int									=  abspath(join(dirname(__file__), 'src'))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)


def 		__magic_name__    (	__UpperCAmelCase	)		->					Optional[int]:

					'''simple docstring'''

					config.addinivalue_line(
					    '''markers''',      '''is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested'''	)
					config.addinivalue_line(
					    '''markers''',      '''is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested'''	)
					config.addinivalue_line('''markers''',      '''is_pipeline_test: mark test to run only when pipelines are tested'''	)
					config.addinivalue_line('''markers''',      '''is_staging_test: mark test to run only in the staging environment'''	)
					config.addinivalue_line('''markers''',      '''accelerate_tests: mark test that require accelerate'''	)
					config.addinivalue_line('''markers''',      '''tool_tests: mark the tool tests that are run on their specific schedule'''	)


def 		__magic_name__    (	__UpperCAmelCase	)		->					int:

					'''simple docstring'''

					from transformers.testing_utils import pytest_addoption_shared

					pytest_addoption_shared(__UpperCAmelCase	)


def 		__magic_name__    (	__UpperCAmelCase	)		->					Union[str, Any]:

					'''simple docstring'''

					from transformers.testing_utils import pytest_terminal_summary_main

					snake_case_									=				terminalreporter.config.getoption('''--make-reports'''	)
					if make_reports:
										pytest_terminal_summary_main(__UpperCAmelCase,      id=__UpperCAmelCase	)


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					Optional[int]:

					'''simple docstring'''

					if exitstatus == 5:
										snake_case_									=				0


# Doctest custom flag to ignore output.
a  :				Union[str, Any]									=  doctest.register_optionflag('IGNORE_RESULT')

a  :				Optional[int]									=  doctest.OutputChecker






class 						a				(   _lowerCamelCase     ):


				def   A_ (		self    :					List[Any]       ,				lowercase_    :					int       ,				lowercase_    :					Tuple       ,				lowercase_    :					Optional[int]					):
									if IGNORE_RESULT & optionflags:
														return True
									return OutputChecker.check_output(self       ,				lowercase_       ,				lowercase_       ,				lowercase_					)







a  :				List[Any]									=  CustomOutputChecker
a  :				Optional[int]									=  HfDoctestModule

a  :				Tuple									=  HfDocTestParser

