'''simple docstring'''

import unittest

from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
       import jax

       from transformers.models.big_bird.modeling_flax_big_bird import (
           FlaxBigBirdForCausalLM,
           FlaxBigBirdForMaskedLM,
           FlaxBigBirdForMultipleChoice,
           FlaxBigBirdForPreTraining,
           FlaxBigBirdForQuestionAnswering,
           FlaxBigBirdForSequenceClassification,
           FlaxBigBirdForTokenClassification,
           FlaxBigBirdModel,
       )





class 							lowercase						(						unittest.TestCase ):


   def __init__(   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	List[str]   ,		__lowerCAmelCase				:	Any=2   ,		__lowerCAmelCase				:	Dict=56   ,		__lowerCAmelCase				:	Dict=True   ,		__lowerCAmelCase				:	int=True   ,		__lowerCAmelCase				:	Dict=True   ,		__lowerCAmelCase				:	Optional[int]=True   ,		__lowerCAmelCase				:	int=99   ,		__lowerCAmelCase				:	Dict=32   ,		__lowerCAmelCase				:	int=2   ,		__lowerCAmelCase				:	Union[str, Any]=2   ,		__lowerCAmelCase				:	Any=7   ,		__lowerCAmelCase				:	Optional[Any]="gelu_new"   ,		__lowerCAmelCase				:	List[str]=0.1   ,		__lowerCAmelCase				:	Optional[Any]=0.1   ,		__lowerCAmelCase				:	Optional[int]=512   ,		__lowerCAmelCase				:	Union[str, Any]=16   ,		__lowerCAmelCase				:	int=2   ,		__lowerCAmelCase				:	Optional[int]=0.02   ,		__lowerCAmelCase				:	List[str]=4   ,		__lowerCAmelCase				:	Union[str, Any]="block_sparse"   ,		__lowerCAmelCase				:	Union[str, Any]=True   ,		__lowerCAmelCase				:	int=False   ,		__lowerCAmelCase				:	Dict=2   ,		__lowerCAmelCase				:	List[str]=3   ,		)      ->					Union[str, Any]:
         lowercase_     =      parent
         lowercase_     =      batch_size
         lowercase_     =      seq_length
         lowercase_     =      is_training
         lowercase_     =      use_attention_mask
         lowercase_     =      use_token_type_ids
         lowercase_     =      use_labels
         lowercase_     =      vocab_size
         lowercase_     =      hidden_size
         lowercase_     =      num_hidden_layers
         lowercase_     =      num_attention_heads
         lowercase_     =      intermediate_size
         lowercase_     =      hidden_act
         lowercase_     =      hidden_dropout_prob
         lowercase_     =      attention_probs_dropout_prob
         lowercase_     =      max_position_embeddings
         lowercase_     =      type_vocab_size
         lowercase_     =      type_sequence_label_size
         lowercase_     =      initializer_range
         lowercase_     =      num_choices

         lowercase_     =      rescale_embeddings
         lowercase_     =      attention_type
         lowercase_     =      use_bias
         lowercase_     =      block_size
         lowercase_     =      num_random_blocks


   def __UpperCAmelCase       (   self				:	List[Any])      ->					Dict:
         lowercase_     =      ids_tensor([self.batch_size, self.seq_length]   ,		self.vocab_size)

         lowercase_     =      None
         if self.use_attention_mask:
               lowercase_     =      random_attention_mask([self.batch_size, self.seq_length])

         lowercase_     =      None
         if self.use_token_type_ids:
               lowercase_     =      ids_tensor([self.batch_size, self.seq_length]   ,		self.type_vocab_size)

         lowercase_     =      BigBirdConfig(
             vocab_size=self.vocab_size   ,		hidden_size=self.hidden_size   ,		num_hidden_layers=self.num_hidden_layers   ,		num_attention_heads=self.num_attention_heads   ,		intermediate_size=self.intermediate_size   ,		hidden_act=self.hidden_act   ,		hidden_dropout_prob=self.hidden_dropout_prob   ,		attention_probs_dropout_prob=self.attention_probs_dropout_prob   ,		max_position_embeddings=self.max_position_embeddings   ,		type_vocab_size=self.type_vocab_size   ,		is_decoder=__lowerCAmelCase   ,		initializer_range=self.initializer_range   ,		attention_type=self.attention_type   ,		block_size=self.block_size   ,		num_random_blocks=self.num_random_blocks   ,		use_bias=self.use_bias   ,		rescale_embeddings=self.rescale_embeddings   ,		)

         return config, input_ids, token_type_ids, attention_mask


   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					Tuple:
         lowercase_     =      self.prepare_config_and_inputs()
         lowercase_ ,							lowercase_ ,							lowercase_ ,							lowercase_     =      config_and_inputs
         lowercase_     =      {
             "input_ids": input_ids,
             "token_type_ids": token_type_ids,
             "attention_mask": attention_mask,
         }
         return config, inputs_dict





@require_flax
class 							lowercase						(						__lowerCamelCase ,				unittest.TestCase ):
   lowerCamelCase_    					=(
       (
           FlaxBigBirdForCausalLM,
           FlaxBigBirdModel,
           FlaxBigBirdForPreTraining,
           FlaxBigBirdForMaskedLM,
           FlaxBigBirdForMultipleChoice,
           FlaxBigBirdForQuestionAnswering,
           FlaxBigBirdForSequenceClassification,
           FlaxBigBirdForTokenClassification,
       )
       if is_flax_available()
       else ()
   )

   lowerCamelCase_    					=False
   lowerCamelCase_    					=False


   def __UpperCAmelCase       (   self				:	Any)      ->					Tuple:
         lowercase_     =      FlaxBigBirdModelTester(self)


   @slow
   # copied from `test_modeling_flax_common` because it takes much longer than other models
   def __UpperCAmelCase       (   self				:	Optional[int])      ->					int:
         super().test_from_pretrained_save_pretrained()


   @slow
   # copied from `test_modeling_flax_common` because it takes much longer than other models
   def __UpperCAmelCase       (   self				:	Optional[int])      ->					Dict:
         super().test_from_pretrained_with_no_automatic_init()


   @slow
   # copied from `test_modeling_flax_common` because it takes much longer than other models
   def __UpperCAmelCase       (   self				:	List[str])      ->					int:
         super().test_no_automatic_init()


   @slow
   # copied from `test_modeling_flax_common` because it takes much longer than other models
   def __UpperCAmelCase       (   self				:	List[str])      ->					str:
         super().test_hidden_states_output()


   @slow
   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					Tuple:
         for model_class_name in self.all_model_classes:
               lowercase_     =      model_class_name.from_pretrained("google/bigbird-roberta-base")
               self.assertIsNotNone(__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Any)      ->					List[Any]:
         if self.test_attn_probs:
               super().test_attention_outputs()


   @slow
   # copied from `test_modeling_flax_common` because it takes much longer than other models
   def __UpperCAmelCase       (   self				:	Tuple)      ->					Dict:
         lowercase_ ,							lowercase_     =      self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
               with self.subTest(model_class.__name__):
                     lowercase_     =      self._prepare_for_class(__lowerCAmelCase   ,		__lowerCAmelCase)
                     lowercase_     =      model_class(__lowerCAmelCase)

                     @jax.jit
                     def model_jitted(__lowerCAmelCase				:	Optional[Any]   ,		__lowerCAmelCase				:	Union[str, Any]=None   ,		**__lowerCAmelCase				:	Any):
                           return model(input_ids=__lowerCAmelCase   ,		attention_mask=__lowerCAmelCase   ,		**__lowerCAmelCase)

                     with self.subTest("JIT Enabled"):
                           lowercase_     =      model_jitted(**__lowerCAmelCase).to_tuple()

                     with self.subTest("JIT Disabled"):
                           with jax.disable_jit():
                                 lowercase_     =      model_jitted(**__lowerCAmelCase).to_tuple()

                     self.assertEqual(len(__lowerCAmelCase)   ,		len(__lowerCAmelCase))
                     for jitted_output, output in zip(__lowerCAmelCase   ,		__lowerCAmelCase):
                           self.assertEqual(jitted_output.shape   ,		output.shape)


   def __UpperCAmelCase       (   self				:	Dict   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	Tuple   ,		__lowerCAmelCase				:	Tuple   ,		__lowerCAmelCase				:	Tuple=1e-5   ,		__lowerCAmelCase				:	Tuple="outputs"   ,		__lowerCAmelCase				:	Tuple=None)      ->					Dict:
         # `bigbird_block_sparse_attention` in `FlaxBigBird` returns `attention_probs = None`, while in PyTorch version,
         # an effort was done to return `attention_probs` (yet to be verified).
         if name.startswith("outputs.attentions"):
               return
         else:
               super().check_pt_flax_outputs(__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase   ,		__lowerCAmelCase)







'''simple docstring'''

import functools
from typing import Any


def __a (	__lowerCamelCase			:						str ,		__lowerCamelCase			:						list[str]				)	->							bool:
      '''simple docstring'''


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

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

      # Build trie
      lowercase_     =      {}
      lowercase_     =      "WORD_KEEPER"

      for word in words:
            lowercase_     =      trie
            for c in word:
                  if c not in trie_node:
                        lowercase_     =      {}

                  lowercase_     =      trie_node[c]

            lowercase_     =      True

      lowercase_     =      len(__lowerCamelCase				)

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

            lowercase_     =      trie
            for i in range(__lowerCamelCase ,		__lowerCamelCase				):
                  lowercase_     =      trie_node.get(string[i] ,		__lowerCamelCase				)

                  if trie_node is None:
                        return False

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

            return False

      return is_breakable(0				)


if __name__ == "__main__":
       import doctest

       doctest.testmod()






