





'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase_					:    Tuple      	=			{
    'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
    'tokenization_canine': ['CanineTokenizer'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    Tuple      	=			[
					    'CANINE_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'CanineForMultipleChoice',
					    'CanineForQuestionAnswering',
					    'CanineForSequenceClassification',
					    'CanineForTokenClassification',
					    'CanineLayer',
					    'CanineModel',
					    'CaninePreTrainedModel',
					    'load_tf_weights_in_canine',
					]


if TYPE_CHECKING:
					from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
					from .tokenization_canine import CanineTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_canine import (
										    CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
										    CanineForMultipleChoice,
										    CanineForQuestionAnswering,
										    CanineForSequenceClassification,
										    CanineForTokenClassification,
										    CanineLayer,
										    CanineModel,
										    CaninePreTrainedModel,
										    load_tf_weights_in_canine,
										)


else:
					import sys

					lowerCAmelCase_					:    Dict      	=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

'''simple docstring'''

import re

from filelock import FileLock


try:
 import nltk

 _A			:      int					      =				True
except (ImportError, ModuleNotFoundError):
 _A			:      Optional[Any]					      =				False

if NLTK_AVAILABLE:
 with FileLock('''.lock''') as lock:
  nltk.download('''punkt''', quiet=True)







def      UpperCamelCase_						(					snake_case_       :       str      )					->     str:






 '''simple docstring'''

 re.sub("""<n>"""						,		""""""						,		snake_case_      )  # remove pegasus newline char
 assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
 return "\n".join(nltk.sent_tokenize(snake_case_      )      )






