



"""simple docstring"""






import math

import tensorflow as tf
from packaging import version






def   snake_case__     (	__lowerCamelCase       :					List[str]			):
			"""simple docstring"""
			lowerCamelCase__	:	List[Any]				=tf.convert_to_tensor(__lowerCamelCase			)
			lowerCamelCase__	:	Optional[Any]				=0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0			)							,	x.dtype			)			))

			return x * cdf






def   snake_case__     (	__lowerCamelCase       :					Dict			):
			"""simple docstring"""
			lowerCamelCase__	:	Dict				=tf.convert_to_tensor(__lowerCamelCase			)
			lowerCamelCase__	:	Optional[Any]				=tf.cast(math.pi							,	x.dtype			)
			lowerCamelCase__	:	int				=tf.cast(0.04_47_15							,	x.dtype			)
			lowerCamelCase__	:	Optional[int]				=0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi			) * (x + coeff * tf.pow(__lowerCamelCase							,	3			))			))

			return x * cdf






def   snake_case__     (	__lowerCamelCase       :					Optional[Any]			):
			"""simple docstring"""
			lowerCamelCase__	:	str				=tf.convert_to_tensor(__lowerCamelCase			)

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






def   snake_case__     (	__lowerCamelCase       :					List[Any]			):
			"""simple docstring"""
			lowerCamelCase__	:	Union[str, Any]				=tf.convert_to_tensor(__lowerCamelCase			)
			lowerCamelCase__	:	Optional[int]				=tf.cast(0.04_47_15							,	x.dtype			)
			lowerCamelCase__	:	int				=tf.cast(0.79_78_84_56_08							,	x.dtype			)

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






def   snake_case__     (	__lowerCamelCase       :					Dict			):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[Any]				=tf.convert_to_tensor(__lowerCamelCase			)
			lowerCamelCase__	:	Any				=tf.cast(1.7_02							,	x.dtype			)
			return x * tf.math.sigmoid(coeff * x			)






def   snake_case__     (	__lowerCamelCase       :					str			):
			"""simple docstring"""
			return tf.clip_by_value(_gelu(__lowerCamelCase			)							,	-10							,	10			)






def   snake_case__     (	__lowerCamelCase       :					List[str]							,	__lowerCamelCase       :					Union[str, Any]=-1			):
			"""simple docstring"""
			lowerCamelCase__	:	List[Any]				=tf.split(__lowerCamelCase							,	2							,	axis=__lowerCamelCase			)
			return a * tf.math.sigmoid(__lowerCamelCase			)


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






		def   snake_case__     (	__lowerCamelCase       :					str			):
					"""simple docstring"""
					return tf.keras.activations.gelu(__lowerCamelCase							,	approximate=__lowerCamelCase			)

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

		_lowercase				:				Any     =		approximate_gelu_wrap
else:
		_lowercase				:				Tuple     =		_gelu
		_lowercase				:				Tuple     =		_gelu_new


_lowercase				:				Optional[int]     =		{
    "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   snake_case__     (	__lowerCamelCase       :					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()			)}'''			)









"""simple docstring"""






def   snake_case__     (	__lowerCamelCase       :					list[list[int]]							,	__lowerCamelCase       :					int							,	__lowerCamelCase       :					int							,	__lowerCamelCase       :					list[int]			):
			"""simple docstring"""

			# 1. Validate that path exists between current and next vertices
			if graph[path[curr_ind - 1]][next_ver] == 0:
						return False

			# 2. Validate that next vertex is not already in path
			return not any(vertex == next_ver for vertex in path			)






def   snake_case__     (	__lowerCamelCase       :					list[list[int]]							,	__lowerCamelCase       :					list[int]							,	__lowerCamelCase       :					int			):
			"""simple docstring"""

			# Base Case
			if curr_ind == len(__lowerCamelCase			):
						# return whether path exists between current and starting vertices
						return graph[path[curr_ind - 1]][path[0]] == 1

			# Recursive Step
			for next_ver in range(0							,	len(__lowerCamelCase			)			):
						if valid_connection(__lowerCamelCase							,	__lowerCamelCase							,	__lowerCamelCase							,	__lowerCamelCase			):
									# Insert current vertex  into path as next transition
									lowerCamelCase__	:	Tuple				=next_ver
									# Validate created path
									if util_hamilton_cycle(__lowerCamelCase							,	__lowerCamelCase							,	curr_ind + 1			):
												return True
									# Backtrack
									lowerCamelCase__	:	int				=-1
			return False






def   snake_case__     (	__lowerCamelCase       :					list[list[int]]							,	__lowerCamelCase       :					int = 0			):
			"""simple docstring"""
			lowerCamelCase__	:	Tuple				=[-1] * (len(__lowerCamelCase			) + 1)
			# initialize start and end of path with starting index
			lowerCamelCase__	:	Union[str, Any]				=start_index
			# evaluate and if we find answer return path either return empty array
			return path if util_hamilton_cycle(__lowerCamelCase							,	__lowerCamelCase							,	1			) else []




