


'''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   __snake_case			(  unittest.TestCase):







    """simple docstring"""



    def __init__(  self       :    Optional[Any]       ,		lowerCamelCase       :    Optional[int]       ,		lowerCamelCase       :    Union[str, Any]=2       ,		lowerCamelCase       :    Dict=56       ,		lowerCamelCase       :    Optional[Any]=True       ,		lowerCamelCase       :    str=True       ,		lowerCamelCase       :    Optional[int]=True       ,		lowerCamelCase       :    Dict=True       ,		lowerCamelCase       :    Dict=99       ,		lowerCamelCase       :    str=32       ,		lowerCamelCase       :    str=2       ,		lowerCamelCase       :    Any=2       ,		lowerCamelCase       :    List[Any]=7       ,		lowerCamelCase       :    Optional[int]="gelu_new"       ,		lowerCamelCase       :    Optional[Any]=0.1       ,		lowerCamelCase       :    List[Any]=0.1       ,		lowerCamelCase       :    Optional[int]=5_12       ,		lowerCamelCase       :    Optional[Any]=16       ,		lowerCamelCase       :    List[str]=2       ,		lowerCamelCase       :    int=0.02       ,		lowerCamelCase       :    Any=4       ,		lowerCamelCase       :    List[Any]="block_sparse"       ,		lowerCamelCase       :    Any=True       ,		lowerCamelCase       :    Tuple=False       ,		lowerCamelCase       :    List[str]=2       ,		lowerCamelCase       :    Tuple=3       ,		)  ->    Any:
      lowerCAmelCase_     : List[Any]     =  parent
      lowerCAmelCase_     : Dict     =  batch_size
      lowerCAmelCase_     : Any     =  seq_length
      lowerCAmelCase_     : str     =  is_training
      lowerCAmelCase_     : List[str]     =  use_attention_mask
      lowerCAmelCase_     : List[Any]     =  use_token_type_ids
      lowerCAmelCase_     : List[str]     =  use_labels
      lowerCAmelCase_     : Optional[Any]     =  vocab_size
      lowerCAmelCase_     : Tuple     =  hidden_size
      lowerCAmelCase_     : Any     =  num_hidden_layers
      lowerCAmelCase_     : Optional[int]     =  num_attention_heads
      lowerCAmelCase_     : Union[str, Any]     =  intermediate_size
      lowerCAmelCase_     : List[str]     =  hidden_act
      lowerCAmelCase_     : str     =  hidden_dropout_prob
      lowerCAmelCase_     : str     =  attention_probs_dropout_prob
      lowerCAmelCase_     : Union[str, Any]     =  max_position_embeddings
      lowerCAmelCase_     : Optional[Any]     =  type_vocab_size
      lowerCAmelCase_     : Union[str, Any]     =  type_sequence_label_size
      lowerCAmelCase_     : List[str]     =  initializer_range
      lowerCAmelCase_     : List[str]     =  num_choices

      lowerCAmelCase_     : Optional[Any]     =  rescale_embeddings
      lowerCAmelCase_     : Any     =  attention_type
      lowerCAmelCase_     : int     =  use_bias
      lowerCAmelCase_     : Optional[int]     =  block_size
      lowerCAmelCase_     : Union[str, Any]     =  num_random_blocks

    def __lowercase  (  self       :    Any						)  ->    Optional[int]:
      lowerCAmelCase_     : int     =  ids_tensor([self.batch_size, self.seq_length]       ,		self.vocab_size						)

      lowerCAmelCase_     : Union[str, Any]     =  None
      if self.use_attention_mask:
        lowerCAmelCase_     : Union[str, Any]     =  random_attention_mask([self.batch_size, self.seq_length]						)

      lowerCAmelCase_     : Optional[int]     =  None
      if self.use_token_type_ids:
        lowerCAmelCase_     : List[Any]     =  ids_tensor([self.batch_size, self.seq_length]       ,		self.type_vocab_size						)

      lowerCAmelCase_     : List[Any]     =  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 __lowercase  (  self       :    str						)  ->    Tuple:
      lowerCAmelCase_     : Any     =  self.prepare_config_and_inputs()
      lowerCAmelCase_,				lowerCAmelCase_,				lowerCAmelCase_,				lowerCAmelCase_     : int     =  config_and_inputs
      lowerCAmelCase_     : Tuple     =  {
          """input_ids""": input_ids,
          """token_type_ids""": token_type_ids,
          """attention_mask""": attention_mask,
      }
      return config, inputs_dict







@require_flax
class   __snake_case			(  _SCREAMING_SNAKE_CASE      ,unittest.TestCase):







    """simple docstring"""



    lowercase  					=   (
        (
            FlaxBigBirdForCausalLM,
            FlaxBigBirdModel,
            FlaxBigBirdForPreTraining,
            FlaxBigBirdForMaskedLM,
            FlaxBigBirdForMultipleChoice,
            FlaxBigBirdForQuestionAnswering,
            FlaxBigBirdForSequenceClassification,
            FlaxBigBirdForTokenClassification,
        )
        if is_flax_available()
        else ()
    )

    lowercase  					=   False
    lowercase  					=   False

    def __lowercase  (  self       :    str						)  ->    List[Any]:
      lowerCAmelCase_     : List[str]     =  FlaxBigBirdModelTester(self						)

    @slow
    # copied from `test_modeling_flax_common` because it takes much longer than other models
    def __lowercase  (  self       :    str						)  ->    Union[str, Any]:
      super().test_from_pretrained_save_pretrained()

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

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

    @slow
    # copied from `test_modeling_flax_common` because it takes much longer than other models
    def __lowercase  (  self       :    Tuple						)  ->    Tuple:
      super().test_hidden_states_output()

    @slow
    def __lowercase  (  self       :    Any						)  ->    Any:
      for model_class_name in self.all_model_classes:
        lowerCAmelCase_     : Dict     =  model_class_name.from_pretrained("""google/bigbird-roberta-base"""						)
        self.assertIsNotNone(lowerCamelCase						)

    def __lowercase  (  self       :    Tuple						)  ->    int:
      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 __lowercase  (  self       :    Union[str, Any]						)  ->    Tuple:
      lowerCAmelCase_,				lowerCAmelCase_     : Optional[Any]     =  self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
        with self.subTest(model_class.__name__						):
          lowerCAmelCase_     : Dict     =  self._prepare_for_class(lowerCamelCase       ,		lowerCamelCase						)
          lowerCAmelCase_     : List[str]     =  model_class(lowerCamelCase						)

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

          with self.subTest("""JIT Enabled"""						):
            lowerCAmelCase_     : Dict     =  model_jitted(**lowerCamelCase						).to_tuple()

          with self.subTest("""JIT Disabled"""						):
            with jax.disable_jit():
              lowerCAmelCase_     : str     =  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 __lowercase  (  self       :    List[str]       ,		lowerCamelCase       :    Dict       ,		lowerCamelCase       :    Optional[int]       ,		lowerCamelCase       :    List[Any]       ,		lowerCamelCase       :    Dict=1E-5       ,		lowerCamelCase       :    Tuple="outputs"       ,		lowerCamelCase       :    Optional[Any]=None						)  ->    List[str]:
      # `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'''






from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__A   :    Tuple											= 10







def 							UpperCamelCase_     (       A__   :  int				,       A__   :  int				,       A__   :  list[int]				,       A__   :  int   ):
  '''simple docstring'''





  for i in range(A__				,       A__   ):
    if array[i] == target:
      return i
  return -1







def 							UpperCamelCase_     (       A__   :  list[int]				,       A__   :  int   ):
  '''simple docstring'''





  lowerCAmelCase_     : Optional[int]     =  0
  lowerCAmelCase_     : Union[str, Any]     =  len(A__   )
  while left <= right:
    if right - left < precision:
      return lin_search(A__				,       A__				,       A__				,       A__   )

    lowerCAmelCase_     : Dict     =  (left + right) // 3 + 1
    lowerCAmelCase_     : List[Any]     =  2 * (left + right) // 3 + 1

    if array[one_third] == target:
      return one_third
    elif array[two_third] == target:
      return two_third

    elif target < array[one_third]:
      lowerCAmelCase_     : List[str]     =  one_third - 1
    elif array[two_third] < target:
      lowerCAmelCase_     : Tuple     =  two_third + 1

    else:
      lowerCAmelCase_     : Tuple     =  one_third + 1
      lowerCAmelCase_     : Any     =  two_third - 1
  else:
    return -1







def 							UpperCamelCase_     (       A__   :  int				,       A__   :  int				,       A__   :  list[int]				,       A__   :  int   ):
  '''simple docstring'''





  if left < right:
    if right - left < precision:
      return lin_search(A__				,       A__				,       A__				,       A__   )
    lowerCAmelCase_     : Dict     =  (left + right) // 3 + 1
    lowerCAmelCase_     : Dict     =  2 * (left + right) // 3 + 1

    if array[one_third] == target:
      return one_third
    elif array[two_third] == target:
      return two_third

    elif target < array[one_third]:
      return rec_ternary_search(A__				,       one_third - 1				,       A__				,       A__   )
    elif array[two_third] < target:
      return rec_ternary_search(two_third + 1				,       A__				,       A__				,       A__   )
    else:
      return rec_ternary_search(one_third + 1				,       two_third - 1				,       A__				,       A__   )
  else:
    return -1


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  __A   :    List[Any]											= input("Enter numbers separated by comma:\n").strip()
  __A   :    Union[str, Any]											= [int(item.strip()) for item in user_input.split(",")]
  assert collection == sorted(collection), F"List must be ordered.\n{collection}."
  __A   :    List[Any]											= int(input("Enter the number to be found in the list:\n").strip())
  __A   :    str											= ite_ternary_search(collection, target)
  __A   :    Dict											= rec_ternary_search(0, len(collection) - 1, collection, target)
  if resulta != -1:
    print(F'''Iterative search: {target} found at positions: {resulta}''')
    print(F'''Recursive search: {target} found at positions: {resulta}''')
  else:
    print("Not found")



