


import math

import tensorflow as tf
from packaging import version






def 			UpperCamelCase (     __magic_name__					:							int					)       ->  Union[str, Any]:
		"""simple docstring"""




		lowercase__					      =		tf.convert_to_tensor(__magic_name__					)
		lowercase__					      =		0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0					)   ,   x.dtype					)					))

		return x * cdf






def 			UpperCamelCase (     __magic_name__					:							int					)       ->  str:
		"""simple docstring"""




		lowercase__					      =		tf.convert_to_tensor(__magic_name__					)
		lowercase__					      =		tf.cast(math.pi   ,   x.dtype					)
		lowercase__					      =		tf.cast(0.0_4_4_7_1_5   ,   x.dtype					)
		lowercase__					      =		0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi					) * (x + coeff * tf.pow(__magic_name__   ,   3					))					))

		return x * cdf






def 			UpperCamelCase (     __magic_name__					:							int					)       ->  str:
		"""simple docstring"""




		lowercase__					      =		tf.convert_to_tensor(__magic_name__					)

		return x * tf.tanh(tf.math.softplus(__magic_name__					)					)






def 			UpperCamelCase (     __magic_name__					:							int					)       ->  List[Any]:
		"""simple docstring"""




		lowercase__					      =		tf.convert_to_tensor(__magic_name__					)
		lowercase__					      =		tf.cast(0.0_4_4_7_1_5   ,   x.dtype					)
		lowercase__					      =		tf.cast(0.7_9_7_8_8_4_5_6_0_8   ,   x.dtype					)

		return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)					))






def 			UpperCamelCase (     __magic_name__					:							int					)       ->  Dict:
		"""simple docstring"""




		lowercase__					      =		tf.convert_to_tensor(__magic_name__					)
		lowercase__					      =		tf.cast(1.7_0_2   ,   x.dtype					)
		return x * tf.math.sigmoid(coeff * x					)






def 			UpperCamelCase (     __magic_name__					:							Any					)       ->  List[Any]:
		"""simple docstring"""




		return tf.clip_by_value(_gelu(__magic_name__					)   ,   -10   ,   10					)






def 			UpperCamelCase (     __magic_name__					:							List[str]   ,   __magic_name__					:							Any=-1					)       ->  Union[str, Any]:
		"""simple docstring"""




		lowercase__      ,     lowercase__					      =		tf.split(__magic_name__   ,   2   ,   axis=__magic_name__					)
		return a * tf.math.sigmoid(__magic_name__					)


if version.parse(tf.version.VERSION) >= version.parse('2.4'):






	def 			UpperCamelCase (     __magic_name__					:							Optional[int]					)       ->  Optional[Any]:
			"""simple docstring"""




			return tf.keras.activations.gelu(__magic_name__   ,   approximate=__magic_name__					)

	A	:		Optional[Any]    =       tf.keras.activations.gelu







	A	:		Tuple    =       approximate_gelu_wrap
else:
	A	:		List[Any]    =       _gelu
	A	:		int    =       _gelu_new


A	:		Optional[Any]    =       {
    'gelu': gelu,
    'gelu_10': gelu_aa,
    'gelu_fast': gelu_fast,
    'gelu_new': gelu_new,
    'glu': glu,
    'mish': mish,
    'quick_gelu': quick_gelu,
    'relu': tf.keras.activations.relu,
    'sigmoid': tf.keras.activations.sigmoid,
    'silu': tf.keras.activations.swish,
    'swish': tf.keras.activations.swish,
    'tanh': tf.keras.activations.tanh,
}







def 			UpperCamelCase (     __magic_name__					:							Any					)       ->  Optional[Any]:
		"""simple docstring"""




		if activation_string in ACTaFN:
				return ACTaFN[activation_string]
		else:
				raise KeyError(f'''function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()					)}'''					)





def 			UpperCamelCase (     __magic_name__					:							str   ,   __magic_name__					:							str					)       ->  list:
		"""simple docstring"""




		lowercase__					      =		len(__magic_name__					)
		lowercase__					      =		[]
		for i in range(len(__magic_name__					) - pat_len + 1					):
				lowercase__					      =		True
				for j in range(__magic_name__					):
						if s[i + j] != pattern[j]:
								lowercase__					      =		False
								break
				if match_found:
						position.append(__magic_name__					)
		return position


if __name__ == "__main__":
	assert naive_pattern_search('ABCDEFG', 'DE') == [3]
	print(naive_pattern_search('ABAAABCDBBABCDDEBCABC', 'ABC'))

