
"""simple docstring"""







import functools
from typing import Any
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase	):

	# Validation
	if not isinstance(_UpperCamelCase ,						_UpperCamelCase	) or len(_UpperCamelCase	) == 0:
		raise ValueError('the string should be not empty string'	)

	if not isinstance(_UpperCamelCase ,						_UpperCamelCase	) or not all(
	    isinstance(_UpperCamelCase ,						_UpperCamelCase	) and len(_UpperCamelCase	) > 0 for item in words	):
		raise ValueError('the words should be a list of non-empty strings'	)

	# Build trie
	__lowerCAmelCase    :		dict[str, Any]		    =   {}
	__lowerCAmelCase    :		int		    =   'WORD_KEEPER'

	for word in words:
		__lowerCAmelCase    :		Tuple		    =   trie
		for c in word:
			if c not in trie_node:
				__lowerCAmelCase    :		Union[str, Any]		    =   {}

			__lowerCAmelCase    :		int		    =   trie_node[c]

		__lowerCAmelCase    :		List[Any]		    =   True

	__lowerCAmelCase    :		Any		    =   len(_UpperCamelCase	)

	# Dynamic programming method
	@functools.cache
	def is_breakable(_UpperCamelCase	) -> bool:
		if index == len_string:
			return True

		__lowerCAmelCase    :		List[Any]		    =   trie
		for i in range(_UpperCamelCase ,						_UpperCamelCase	):
			__lowerCAmelCase    :		int		    =   trie_node.get(string[i] ,						_UpperCamelCase	)

			if trie_node is None:
				return False

			if trie_node.get(_UpperCamelCase ,						_UpperCamelCase	) and is_breakable(i + 1	):
				return True

		return False

	return is_breakable(0	)


if __name__ == "__main__":
							import doctest

							doctest.testmod()

"""simple docstring"""







from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def 					__lowerCAmelCase       ():
	__lowerCAmelCase    :		Tuple		    =   HfArgumentParser(_UpperCamelCase	)
	__lowerCAmelCase    :		Optional[Any]		    =   parser.parse_args_into_dataclasses()[0]
	__lowerCAmelCase    :		int		    =   TensorFlowBenchmark(args=_UpperCamelCase	)
	try:
		__lowerCAmelCase    :		Dict		    =   parser.parse_args_into_dataclasses()[0]
	except ValueError as e:
		__lowerCAmelCase    :		List[Any]		    =   'Arg --no_{0} is no longer used, please use --no-{0} instead.'
		__lowerCAmelCase    :		Union[str, Any]		    =   ' '.join(str(_UpperCamelCase	).split(' '	)[:-1]	)
		__lowerCAmelCase    :		List[str]		    =   ''
		__lowerCAmelCase    :		Any		    =   eval(str(_UpperCamelCase	).split(' '	)[-1]	)
		__lowerCAmelCase    :		Dict		    =   []
		for arg in depreciated_args:
			# arg[2:] removes '--'
			if arg[2:] in TensorFlowBenchmark.deprecated_args:
				# arg[5:] removes '--no_'
				full_error_msg += arg_error_msg.format(arg[5:]	)
			else:
				wrong_args.append(_UpperCamelCase	)
		if len(_UpperCamelCase	) > 0:
			__lowerCAmelCase    :		Any		    =   full_error_msg + begin_error_msg + str(_UpperCamelCase	)
		raise ValueError(_UpperCamelCase	)
	benchmark.run()


if __name__ == "__main__":
							main()