




'''simple docstring'''





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

							'''simple docstring'''






							snake_case_						=      set()

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


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

							'''simple docstring'''






							snake_case_						=      [False] * 2_6
							for char in input_str:
														if char.islower():
																					snake_case_						=      True
														elif char.isupper():
																					snake_case_						=      True
							return all(snake_case     )


def      UpperCamelCase_(	snake_case							:       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      UpperCamelCase_(	):

							'''simple docstring'''






							from timeit import timeit

							snake_case_						=      "from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"
							print(timeit("is_pangram()"							,				setup=snake_case     )     )
							print(timeit("is_pangram_faster()"							,				setup=snake_case     )     )
							print(timeit("is_pangram_fastest()"							,				setup=snake_case     )     )
							# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
							# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()









'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a          =		{
    "configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __a          =		[
           "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TimesformerModel",
           "TimesformerForVideoClassification",
           "TimesformerPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_timesformer import (
                  TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TimesformerForVideoClassification,
                  TimesformerModel,
                  TimesformerPreTrainedModel,
              )

else:
       import sys

       __a          =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
