




def 		lowercase__   (		__A:	str = "The quick brown fox jumps over the lazy dog"							,):





					'''simple docstring'''






					__magic_name__							:	List[str]    							=							set()

					# Replace all the whitespace in our sentence
					__magic_name__							:	Dict    							=							input_str.replace(''' '''							,''''''				)
					for alpha in input_str:
										if "a" <= alpha.lower() <= "z":
															frequency.add(alpha.lower()				)
					return len(__A				) == 2_6







def 		lowercase__   (		__A:	str = "The quick brown fox jumps over the lazy dog"							,):





					'''simple docstring'''






					__magic_name__							:	Dict    							=							[False] * 2_6
					for char in input_str:
										if char.islower():
															__magic_name__							:	Dict    							=							True
										elif char.isupper():
															__magic_name__							:	Tuple    							=							True
					return all(__A				)







def 		lowercase__   (		__A:	str = "The quick brown fox jumps over the lazy dog"							,):





					'''simple docstring'''






					return len({char for char in input_str.lower() if char.isalpha()}				) == 2_6







def 		lowercase__   (		):





					'''simple docstring'''






					from timeit import timeit

					__magic_name__							:	List[Any]    							=							'''from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'''
					print(timeit('''is_pangram()'''							,setup=__A				)				)
					print(timeit('''is_pangram_faster()'''							,setup=__A				)				)
					print(timeit('''is_pangram_fastest()'''							,setup=__A				)				)
					# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
					# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	benchmark()









from typing import TYPE_CHECKING

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


__lowerCamelCase   :						int				=			{'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowerCamelCase   :						int				=			[
	    '''SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''SwinForImageClassification''',
	    '''SwinForMaskedImageModeling''',
	    '''SwinModel''',
	    '''SwinPreTrainedModel''',
	    '''SwinBackbone''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowerCamelCase   :						Optional[int]				=			[
	    '''TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFSwinForImageClassification''',
	    '''TFSwinForMaskedImageModeling''',
	    '''TFSwinModel''',
	    '''TFSwinPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_swin import (
		    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SwinBackbone,
		    SwinForImageClassification,
		    SwinForMaskedImageModeling,
		    SwinModel,
		    SwinPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_swin import (
		    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFSwinForImageClassification,
		    TFSwinForMaskedImageModeling,
		    TFSwinModel,
		    TFSwinPreTrainedModel,
		)

else:
	import sys

	__lowerCamelCase   :						Union[str, Any]				=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



