



from typing import TYPE_CHECKING

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


__magic_name__       =     {
    '''configuration_realm''': ['''REALM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RealmConfig'''],
    '''tokenization_realm''': ['''RealmTokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__       =     ['''RealmTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__       =     [
		    '''REALM_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''RealmEmbedder''',
		    '''RealmForOpenQA''',
		    '''RealmKnowledgeAugEncoder''',
		    '''RealmPreTrainedModel''',
		    '''RealmReader''',
		    '''RealmScorer''',
		    '''load_tf_weights_in_realm''',
		]
		__magic_name__       =     ['''RealmRetriever''']


if TYPE_CHECKING:
		from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
		from .tokenization_realm import RealmTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_realm import RealmTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_realm import (
				    REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RealmEmbedder,
				    RealmForOpenQA,
				    RealmKnowledgeAugEncoder,
				    RealmPreTrainedModel,
				    RealmReader,
				    RealmScorer,
				    load_tf_weights_in_realm,
				)
				from .retrieval_realm import RealmRetriever


else:
		import sys

		__magic_name__       =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					for index, item in enumerate(_UpperCAmelCase				):
										if item == target:
															return index
					return -1





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					if not (0 <= high < len(_UpperCAmelCase				) and 0 <= low < len(_UpperCAmelCase				)):
										raise Exception('Invalid upper or lower bound!'				)
					if high < low:
										return -1
					if sequence[low] == target:
										return low
					if sequence[high] == target:
										return high
					return rec_linear_search(_UpperCAmelCase       ,			low + 1       ,			high - 1       ,			_UpperCAmelCase				)


if __name__ == "__main__":
		__magic_name__       =     input('''Enter numbers separated by comma:\n''').strip()
		__magic_name__       =     [int(item.strip()) for item in user_input.split(''',''')]

		__magic_name__       =     int(input('''Enter a single number to be found in the list:\n''').strip())
		__magic_name__       =     linear_search(sequence, target)
		if result != -1:
				print(F"""linear_search({sequence}, {target}) = {result}""")
		else:
				print(F"""{target} was not found in {sequence}""")






