



'''simple docstring'''
import functools
from typing import Any






def A__   (					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
						_UpperCamelCase :		dict[str, Any]			    =       {}
						_UpperCamelCase :		int			    =       'WORD_KEEPER'

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

																		_UpperCamelCase :		int			    =       trie_node[c]

												_UpperCamelCase :		Tuple			    =       True

						_UpperCamelCase :		Dict			    =       len(UpperCAmelCase_							)

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

												_UpperCamelCase :		int			    =       trie
												for i in range(UpperCAmelCase_  ,  UpperCAmelCase_							):
																		_UpperCamelCase :		List[Any]			    =       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'''
import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
					import torch






@require_torch
@require_optimum
@slow
class 							lowercase__     (							unittest.TestCase       ):





	def      UpperCamelCase_  (			self :    str			):







							'''simple docstring'''
							_UpperCamelCase :		Any			    =       'hf-internal-testing/tiny-random-t5'
							_UpperCamelCase :		str			    =       AutoTokenizer.from_pretrained(lowerCamelCase__			)
							_UpperCamelCase :		int			    =       AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase__			)

							_UpperCamelCase :		List[str]			    =       tokenizer('This is me'			,return_tensors='pt'			)

							_UpperCamelCase :		str			    =       model.to_bettertransformer()

							self.assertTrue(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()			)			)

							_UpperCamelCase :		Optional[Any]			    =       model.generate(**lowerCamelCase__			)

							_UpperCamelCase :		Union[str, Any]			    =       model.reverse_bettertransformer()

							self.assertFalse(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()			)			)

							with tempfile.TemporaryDirectory() as tmpdirname:
													model.save_pretrained(lowerCamelCase__			)

													_UpperCamelCase :		List[Any]			    =       AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase__			)

													self.assertFalse(
													    any('BetterTransformer' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()			)			)

													_UpperCamelCase :		Optional[Any]			    =       model_reloaded.generate(**lowerCamelCase__			)
													self.assertTrue(torch.allclose(lowerCamelCase__			,lowerCamelCase__			)			)





	def      UpperCamelCase_  (			self :    Any			):







							'''simple docstring'''
							_UpperCamelCase :		List[Any]			    =       'hf-internal-testing/tiny-random-t5'
							_UpperCamelCase :		List[Any]			    =       AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase__			)

							_UpperCamelCase :		List[str]			    =       model.to_bettertransformer()

							with tempfile.TemporaryDirectory() as tmpdirname:
													with self.assertRaises(lowerCamelCase__			):
																			model.save_pretrained(lowerCamelCase__			)

													_UpperCamelCase :		str			    =       model.reverse_bettertransformer()
													model.save_pretrained(lowerCamelCase__			)


