





"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a						: str     	=			{
    '''configuration_deberta''': ['''DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DebertaConfig''', '''DebertaOnnxConfig'''],
    '''tokenization_deberta''': ['''DebertaTokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a						: Tuple     	=			['''DebertaTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a						: Optional[int]     	=			[
		    '''DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''DebertaForMaskedLM''',
		    '''DebertaForQuestionAnswering''',
		    '''DebertaForSequenceClassification''',
		    '''DebertaForTokenClassification''',
		    '''DebertaModel''',
		    '''DebertaPreTrainedModel''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a						: Dict     	=			[
		    '''TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFDebertaForMaskedLM''',
		    '''TFDebertaForQuestionAnswering''',
		    '''TFDebertaForSequenceClassification''',
		    '''TFDebertaForTokenClassification''',
		    '''TFDebertaModel''',
		    '''TFDebertaPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_deberta import DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaConfig, DebertaOnnxConfig
		from .tokenization_deberta import DebertaTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_deberta_fast import DebertaTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_deberta import (
				    DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DebertaForMaskedLM,
				    DebertaForQuestionAnswering,
				    DebertaForSequenceClassification,
				    DebertaForTokenClassification,
				    DebertaModel,
				    DebertaPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_deberta import (
				    TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFDebertaForMaskedLM,
				    TFDebertaForQuestionAnswering,
				    TFDebertaForSequenceClassification,
				    TFDebertaForTokenClassification,
				    TFDebertaModel,
				    TFDebertaPreTrainedModel,
				)


else:
		import sys

		a						: int     	=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



'''simple docstring'''




def 				snake_case__							(			_A:					str )    ->	list[int]:

		'''simple docstring'''


		lowerCAmelCase   					=  [0 for i in range(len(_A ) )]

		# initialize interval's left pointer and right pointer
		lowerCAmelCase					,     lowerCAmelCase   					=  0, 0

		for i in range(1      ,   len(_A ) ):
				# case when current index is inside the interval
				if i <= right_pointer:
						lowerCAmelCase   					=  min(right_pointer - i + 1      ,   z_result[i - left_pointer] )
						lowerCAmelCase   					=  min_edge

				while go_next(_A      ,   _A      ,   _A ):
						z_result[i] += 1

				# if new index's result gives us more right interval,
				# we've to update left_pointer and right_pointer
				if i + z_result[i] - 1 > right_pointer:
						lowerCAmelCase					,     lowerCAmelCase   					=  i, i + z_result[i] - 1

		return z_result






def 				snake_case__							(			_A:					int      ,   _A:					list[int]      ,   _A:					str )    ->	bool:

		'''simple docstring'''


		return i + z_result[i] < len(_A ) and s[z_result[i]] == s[i + z_result[i]]






def 				snake_case__							(			_A:					str      ,   _A:					str )    ->	int:

		'''simple docstring'''


		lowerCAmelCase   					=  0
		# concatenate 'pattern' and 'input_str' and call z_function
		# with concatenated string
		lowerCAmelCase   					=  z_function(pattern + input_str )

		for val in z_result:
				# if value is greater then length of the pattern string
				# that means this index is starting position of substring
				# which is equal to pattern string
				if val >= len(_A ):
						answer += 1

		return answer


if __name__ == "__main__":
						import doctest

						doctest.testmod()




