




"""simple docstring"""


import functools
from typing import Any


def 					UpperCAmelCase__       (snake_case__							:					str		,   snake_case__							:					list[str]    ):
  """simple docstring"""

  if not isinstance(snake_case__		,   snake_case__    ) or len(snake_case__    ) == 0:
    raise ValueError("""the string should be not empty string"""    )

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

  # Build trie
  _snake_case							:		dict[str, Any]								=  {}
  _snake_case							:		str								=  """WORD_KEEPER"""

  for word in words:
    _snake_case							:		int								=  trie
    for c in word:
      if c not in trie_node:
        _snake_case							:		str								=  {}

      _snake_case							:		int								=  trie_node[c]

    _snake_case							:		str								=  True

  _snake_case							:		Optional[int]								=  len(snake_case__    )

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

    _snake_case							:		Any								=  trie
    for i in range(snake_case__		,   snake_case__    ):
      _snake_case							:		int								=  trie_node.get(string[i]		,   snake_case__    )

      if trie_node is None:
        return False

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

    return False

  return is_breakable(0    )


if __name__ == "__main__":
     import doctest

     doctest.testmod()




import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
			import jax.numpy as jnp

			from transformers import FlaxXLMRobertaModel




@require_sentencepiece
@require_tokenizers
@require_flax
class    SCREAMING_SNAKE_CASE__     (	unittest.TestCase					):





	'''simple docstring'''



	@slow
	def  A							(  self	:    int	):


				'''simple docstring'''


				_snake_case		=			FlaxXLMRobertaModel.from_pretrained('xlm-roberta-base'	)
				_snake_case		=			AutoTokenizer.from_pretrained('xlm-roberta-base'	)
				_snake_case		=			'The dog is cute and lives in the garden house'
				_snake_case		=			jnp.array([tokenizer.encode(lowercase	)]	)

				_snake_case		=			(1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
				_snake_case		=			jnp.array(
				    [[-0.0101, 0.1218, -0.0803, 0.0801, 0.1327, 0.0776, -0.1215, 0.2383, 0.3338, 0.3106, 0.0300, 0.0252]]	)

				_snake_case		=			model(lowercase	)['last_hidden_state']
				self.assertEqual(output.shape			,  lowercase	)
				# compare the actual values for a slice of last dim
				self.assertTrue(jnp.allclose(output[:, :, -1]			,  lowercase			,  atol=1E-3	)	)