






from collections import defaultdict


def        _a  (     UpperCamelCase_					:				List[Any]    ,   UpperCamelCase_					:				List[str]   ) ->   bool:
						"""simple docstring"""







						lowerCAmelCase__       =						first_str.lower().strip()
						lowerCAmelCase__       =						second_str.lower().strip()

						# Remove whitespace
						lowerCAmelCase__       =						first_str.replace(" "    ,   ""   )
						lowerCAmelCase__       =						second_str.replace(" "    ,   ""   )

						# Strings of different lengths are not anagrams
						if len(UpperCamelCase_   ) != len(UpperCamelCase_   ):
												return False

						# Default values for count should be 0
						lowerCAmelCase__       =						defaultdict(UpperCamelCase_   )

						# For each character in input strings,
						# increment count in the corresponding
						for i in range(len(UpperCamelCase_   )   ):
												count[first_str[i]] += 1
												count[second_str[i]] -= 1

						return all(_count == 0 for _count in count.values()   )


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	a_							=    input("""Enter the first string """).strip()
	a_							=    input("""Enter the second string """).strip()

	a_							=    check_anagrams(input_a, input_b)
	print(F"{input_a} and {input_b} are {'' if status else 'not '}anagrams.")














from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_							=    {'''configuration_ibert''': ['''IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''IBertConfig''', '''IBertOnnxConfig''']}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a_							=    [
	    '''IBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''IBertForMaskedLM''',
	    '''IBertForMultipleChoice''',
	    '''IBertForQuestionAnswering''',
	    '''IBertForSequenceClassification''',
	    '''IBertForTokenClassification''',
	    '''IBertModel''',
	    '''IBertPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_ibert import (
		    IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    IBertForMaskedLM,
		    IBertForMultipleChoice,
		    IBertForQuestionAnswering,
		    IBertForSequenceClassification,
		    IBertForTokenClassification,
		    IBertModel,
		    IBertPreTrainedModel,
		)

else:
	import sys

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






