
from __future__ import annotations

from random import random
from typing import Generic, TypeVar

lowerCamelCase__    :		Optional[Any]          =   TypeVar("""KT""")
lowerCamelCase__    :		str          =   TypeVar("""VT""")



class       _snake_case   (	Generic[KT, VT]							):


 def __init__(					self					,  SCREAMING_SNAKE_CASE_ = "root"					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      key
   lowercase__  :   List[Any]    		=      value
   lowercase__  :   list[Node[KT, VT]]    		=      []


 def __repr__(					self):


   '''simple docstring'''




   return f'Node({self.key}: {self.value})'



 @property
 def      lowercase__     (					self):


   '''simple docstring'''




   return len(self.forward)



class       _snake_case   (	Generic[KT, VT]							):


 def __init__(					self					,  SCREAMING_SNAKE_CASE_ = 0.5					,  SCREAMING_SNAKE_CASE_ = 16):


   '''simple docstring'''




   lowercase__  :   Node[KT, VT]    		=      Node[KT, VT]()
   lowercase__  :   List[Any]    		=      0
   lowercase__  :   str    		=      p
   lowercase__  :   Dict    		=      max_level


 def __str__(					self):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      list(self)

   if len(SCREAMING_SNAKE_CASE_) == 0:
     return f'SkipList(level={self.level})'

   lowercase__  :   Any    		=      max((len(str(SCREAMING_SNAKE_CASE_)) for item in items)					,  default=4)
   lowercase__  :   int    		=      max(SCREAMING_SNAKE_CASE_					,  4) + 4

   lowercase__  :   int    		=      self.head
   lowercase__  :   str    		=      []

   lowercase__  :   Union[str, Any]    		=      node.forward.copy()
   lines.append(f'[{node.key}]'.ljust(SCREAMING_SNAKE_CASE_					,  """-""") + """* """ * len(SCREAMING_SNAKE_CASE_))
   lines.append(""" """ * label_size + """| """ * len(SCREAMING_SNAKE_CASE_))

   while len(node.forward) != 0:
     lowercase__  :   Optional[int]    		=      node.forward[0]

     lines.append(
         f'[{node.key}]'.ljust(SCREAMING_SNAKE_CASE_					,  """-""")
         + """ """.join(str(n.key) if n.key == node.key else """|""" for n in forwards))
     lines.append(""" """ * label_size + """| """ * len(SCREAMING_SNAKE_CASE_))
     lowercase__  :   Optional[int]    		=      node.forward

   lines.append("""None""".ljust(SCREAMING_SNAKE_CASE_) + """* """ * len(SCREAMING_SNAKE_CASE_))
   return f'SkipList(level={self.level})\n' + "\n".join(SCREAMING_SNAKE_CASE_)


 def __iter__(					self):


   '''simple docstring'''




   lowercase__  :   Optional[int]    		=      self.head

   while len(node.forward) != 0:
     yield node.forward[0].key
     lowercase__  :   Union[str, Any]    		=      node.forward[0]


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      1
   while random() < self.p and level < self.max_level:
     level += 1

   return level


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      []

   lowercase__  :   Dict    		=      self.head

   for i in reversed(range(self.level)):
     # i < node.level - When node level is lesser than `i` decrement `i`.
     # node.forward[i].key < key - Jumping to node with key value higher
     #                             or equal to searched key would result
     #                             in skipping searched key.
     while i < node.level and node.forward[i].key < key:
       lowercase__  :   List[str]    		=      node.forward[i]
     # Each leftmost node (relative to searched node) will potentially have to
     # be updated.
     update_vector.append(SCREAMING_SNAKE_CASE_)

   update_vector.reverse()  # Note that we were inserting values in reverse order.

   # len(node.forward) != 0 - If current node doesn't contain any further
   #                          references then searched key is not present.
   # node.forward[0].key == key - Next node key should be equal to search key
   #                              if key is present.
   if len(node.forward) != 0 and node.forward[0].key == key:
     return node.forward[0], update_vector
   else:
     return None, update_vector


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Optional[int]    		=      self._locate_node(SCREAMING_SNAKE_CASE_)

   if node is not None:
     for i, update_node in enumerate(SCREAMING_SNAKE_CASE_):
       # Remove or replace all references to removed node.
       if update_node.level > i and update_node.forward[i].key == key:
         if node.level > i:
           lowercase__  :   int    		=      node.forward[i]
         else:
           lowercase__  :   List[Any]    		=      update_node.forward[:i]


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      self._locate_node(SCREAMING_SNAKE_CASE_)
   if node is not None:
     lowercase__  :   str    		=      value
   else:
     lowercase__  :   Union[str, Any]    		=      self.random_level()

     if level > self.level:
       # After level increase we have to add additional nodes to head.
       for _ in range(self.level - 1					,  SCREAMING_SNAKE_CASE_):
         update_vector.append(self.head)
       lowercase__  :   int    		=      level

     lowercase__  :   Optional[int]    		=      Node(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

     for i, update_node in enumerate(update_vector[:level]):
       # Change references to pass through new node.
       if update_node.level > i:
         new_node.forward.append(update_node.forward[i])

       if update_node.level < i + 1:
         update_node.forward.append(SCREAMING_SNAKE_CASE_)
       else:
         lowercase__  :   int    		=      new_node



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   str    		=      self._locate_node(SCREAMING_SNAKE_CASE_)

   if node is not None:
     return node.value

   return None

def 		UpperCamelCase	(      )		->	List[str]:


  '''simple docstring'''






  lowercase__  :   int    		=      SkipList()
  skip_list.insert("""Key1""" , 3   )
  skip_list.insert("""Key2""" , 12   )
  skip_list.insert("""Key3""" , 41   )
  skip_list.insert("""Key4""" , -19   )

  lowercase__  :   List[str]    		=      skip_list.head
  lowercase__  :   Union[str, Any]    		=      {}
  while node.level != 0:
    lowercase__  :   Optional[int]    		=      node.forward[0]
    lowercase__  :   Union[str, Any]    		=      node.value

  assert len(lowercase_   ) == 4
  assert all_values["Key1"] == 3
  assert all_values["Key2"] == 12
  assert all_values["Key3"] == 41
  assert all_values["Key4"] == -19

def 		UpperCamelCase	(      )		->	Optional[Any]:


  '''simple docstring'''






  lowercase__  :   Dict    		=      SkipList()
  skip_list.insert("""Key1""" , 10   )
  skip_list.insert("""Key1""" , 12   )

  skip_list.insert("""Key5""" , 7   )
  skip_list.insert("""Key7""" , 10   )
  skip_list.insert("""Key10""" , 5   )

  skip_list.insert("""Key7""" , 7   )
  skip_list.insert("""Key5""" , 5   )
  skip_list.insert("""Key10""" , 10   )

  lowercase__  :   Optional[int]    		=      skip_list.head
  lowercase__  :   Optional[int]    		=      {}
  while node.level != 0:
    lowercase__  :   int    		=      node.forward[0]
    lowercase__  :   str    		=      node.value

  if len(lowercase_   ) != 4:
    print()
  assert len(lowercase_   ) == 4
  assert all_values["Key1"] == 12
  assert all_values["Key7"] == 7
  assert all_values["Key5"] == 5
  assert all_values["Key10"] == 10

def 		UpperCamelCase	(      )		->	Optional[int]:


  '''simple docstring'''






  lowercase__  :   Optional[Any]    		=      SkipList()
  assert skip_list.find("""Some key"""   ) is None

def 		UpperCamelCase	(      )		->	int:


  '''simple docstring'''






  lowercase__  :   List[Any]    		=      SkipList()

  skip_list.insert("""Key2""" , 20   )
  assert skip_list.find("""Key2"""   ) == 20

  skip_list.insert("""Some Key""" , 10   )
  skip_list.insert("""Key2""" , 8   )
  skip_list.insert("""V""" , 13   )

  assert skip_list.find("""Y"""   ) is None
  assert skip_list.find("""Key2"""   ) == 8
  assert skip_list.find("""Some Key"""   ) == 10
  assert skip_list.find("""V"""   ) == 13

def 		UpperCamelCase	(      )		->	str:


  '''simple docstring'''






  lowercase__  :   int    		=      SkipList()
  skip_list.delete("""Some key"""   )

  assert len(skip_list.head.forward   ) == 0

def 		UpperCamelCase	(      )		->	List[str]:


  '''simple docstring'''






  lowercase__  :   Any    		=      SkipList()

  skip_list.insert("""Key1""" , 12   )
  skip_list.insert("""V""" , 13   )
  skip_list.insert("""X""" , 14   )
  skip_list.insert("""Key2""" , 15   )

  skip_list.delete("""V"""   )
  skip_list.delete("""Key2"""   )

  assert skip_list.find("""V"""   ) is None
  assert skip_list.find("""Key2"""   ) is None

def 		UpperCamelCase	(      )		->	Optional[int]:


  '''simple docstring'''






  lowercase__  :   Optional[Any]    		=      SkipList()

  skip_list.insert("""Key1""" , 12   )
  skip_list.insert("""V""" , 13   )
  skip_list.insert("""X""" , 14   )
  skip_list.insert("""Key2""" , 15   )

  skip_list.delete("""V"""   )
  assert skip_list.find("""V"""   ) is None
  assert skip_list.find("""X"""   ) == 14
  assert skip_list.find("""Key1"""   ) == 12
  assert skip_list.find("""Key2"""   ) == 15

  skip_list.delete("""X"""   )
  assert skip_list.find("""V"""   ) is None
  assert skip_list.find("""X"""   ) is None
  assert skip_list.find("""Key1"""   ) == 12
  assert skip_list.find("""Key2"""   ) == 15

  skip_list.delete("""Key1"""   )
  assert skip_list.find("""V"""   ) is None
  assert skip_list.find("""X"""   ) is None
  assert skip_list.find("""Key1"""   ) is None
  assert skip_list.find("""Key2"""   ) == 15

  skip_list.delete("""Key2"""   )
  assert skip_list.find("""V"""   ) is None
  assert skip_list.find("""X"""   ) is None
  assert skip_list.find("""Key1"""   ) is None
  assert skip_list.find("""Key2"""   ) is None

def 		UpperCamelCase	(      )		->	Dict:


  '''simple docstring'''






  lowercase__  :   Dict    		=      SkipList()

  skip_list.insert("""Key1""" , 12   )
  skip_list.insert("""V""" , 13   )
  skip_list.insert("""X""" , 1_42   )
  skip_list.insert("""Key2""" , 15   )

  skip_list.delete("""X"""   )

  def traverse_keys(lowercase_   ):
    yield node.key
    for forward_node in node.forward:
      yield from traverse_keys(lowercase_   )

  assert len(set(traverse_keys(skip_list.head   )   )   ) == 4

def 		UpperCamelCase	(      )		->	Union[str, Any]:


  '''simple docstring'''






  def is_sorted(lowercase_   ):
    return all(next_item >= item for item, next_item in zip(lowercase_ , lst[1:]   )   )

  lowercase__  :   List[str]    		=      SkipList()
  for i in range(10   ):
    skip_list.insert(lowercase_ , lowercase_   )
  assert is_sorted(list(lowercase_   )   )
  skip_list.delete(5   )
  skip_list.delete(8   )
  skip_list.delete(2   )
  assert is_sorted(list(lowercase_   )   )
  skip_list.insert(-12 , -12   )
  skip_list.insert(77 , 77   )
  assert is_sorted(list(lowercase_   )   )

def 		UpperCamelCase	(      )		->	List[str]:


  '''simple docstring'''






  for _ in range(1_00   ):
    # Repeat test 100 times due to the probabilistic nature of skip list
    # random values == random bugs
    test_insert()
    test_insert_overrides_existing_value()

    test_searching_empty_list_returns_none()
    test_search()

    test_deleting_item_from_empty_list_do_nothing()
    test_deleted_items_are_not_founded_by_find_method()
    test_delete_removes_only_given_key()
    test_delete_doesnt_leave_dead_nodes()

    test_iter_always_yields_sorted_values()

def 		UpperCamelCase	(      )		->	Tuple:


  '''simple docstring'''






  lowercase__  :   Optional[Any]    		=      SkipList()
  skip_list.insert(2 , """2"""   )
  skip_list.insert(4 , """4"""   )
  skip_list.insert(6 , """4"""   )
  skip_list.insert(4 , """5"""   )
  skip_list.insert(8 , """4"""   )
  skip_list.insert(9 , """4"""   )

  skip_list.delete(4   )

  print(lowercase_   )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()








import unittest

from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor


if is_flax_available():
     import os

     # The slow tests are often failing with OOM error on GPU
     # This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
     # but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
     lowerCamelCase__    :		Optional[int]          =   """platform"""
     import jax
     import jax.numpy as jnp
     import numpy as np

     from transformers import FlaxPegasusForConditionalGeneration, FlaxPegasusModel



@require_flax
class       _snake_case   :
 __lowerCAmelCase  :     Optional[int]        =			PegasusConfig
 __lowerCAmelCase  :     str        =			{}
 __lowerCAmelCase  :     int        =			'gelu'


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_=13					,  SCREAMING_SNAKE_CASE_=7					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=False					,  SCREAMING_SNAKE_CASE_=99					,  SCREAMING_SNAKE_CASE_=32					,  SCREAMING_SNAKE_CASE_=5					,  SCREAMING_SNAKE_CASE_=4					,  SCREAMING_SNAKE_CASE_=37					,  SCREAMING_SNAKE_CASE_=0.1					,  SCREAMING_SNAKE_CASE_=0.1					,  SCREAMING_SNAKE_CASE_=20					,  SCREAMING_SNAKE_CASE_=2					,  SCREAMING_SNAKE_CASE_=1					,  SCREAMING_SNAKE_CASE_=0					,  ):


   '''simple docstring'''




   lowercase__  :   Any    		=      parent
   lowercase__  :   int    		=      batch_size
   lowercase__  :   Optional[int]    		=      seq_length
   lowercase__  :   str    		=      is_training
   lowercase__  :   str    		=      use_labels
   lowercase__  :   List[str]    		=      vocab_size
   lowercase__  :   Dict    		=      hidden_size
   lowercase__  :   int    		=      num_hidden_layers
   lowercase__  :   int    		=      num_attention_heads
   lowercase__  :   int    		=      intermediate_size

   lowercase__  :   List[str]    		=      hidden_dropout_prob
   lowercase__  :   List[str]    		=      attention_probs_dropout_prob
   lowercase__  :   Tuple    		=      max_position_embeddings
   lowercase__  :   Dict    		=      eos_token_id
   lowercase__  :   Any    		=      pad_token_id
   lowercase__  :   Any    		=      bos_token_id


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      ids_tensor([self.batch_size, self.seq_length - 1]					,  self.vocab_size).clip(3					,  self.vocab_size)
   lowercase__  :   str    		=      np.expand_dims(np.array([self.eos_token_id] * self.batch_size)					,  1)
   lowercase__  :   Union[str, Any]    		=      np.concatenate([input_ids, eos_tensor]					,  axis=1)

   lowercase__  :   Optional[int]    		=      ids_tensor([self.batch_size, self.seq_length]					,  self.vocab_size)

   lowercase__  :   str    		=      self.config_cls(
       vocab_size=self.vocab_size					,  d_model=self.hidden_size					,  encoder_layers=self.num_hidden_layers					,  decoder_layers=self.num_hidden_layers					,  encoder_attention_heads=self.num_attention_heads					,  decoder_attention_heads=self.num_attention_heads					,  encoder_ffn_dim=self.intermediate_size					,  decoder_ffn_dim=self.intermediate_size					,  dropout=self.hidden_dropout_prob					,  attention_dropout=self.attention_probs_dropout_prob					,  max_position_embeddings=self.max_position_embeddings					,  eos_token_ids=[2]					,  bos_token_id=self.bos_token_id					,  pad_token_id=self.pad_token_id					,  decoder_start_token_id=self.pad_token_id					,  **self.config_updates					,  )
   lowercase__  :   Any    		=      prepare_pegasus_inputs_dict(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   return config, inputs_dict


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      20
   lowercase__  :   str    		=      model_class_name(SCREAMING_SNAKE_CASE_)

   lowercase__  :   str    		=      model.encode(inputs_dict["""input_ids"""])

   lowercase__		,    lowercase__  :   Dict    		=      (
       inputs_dict["""decoder_input_ids"""],
       inputs_dict["""decoder_attention_mask"""],
   )

   lowercase__  :   int    		=      model.init_cache(decoder_input_ids.shape[0]					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   lowercase__  :   Tuple    		=      jnp.ones((decoder_input_ids.shape[0], max_decoder_length)					,  dtype="""i4""")

   lowercase__  :   Union[str, Any]    		=      jnp.broadcast_to(
       jnp.arange(decoder_input_ids.shape[-1] - 1)[None, :]					,  (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)					,  )
   lowercase__  :   str    		=      model.decode(
       decoder_input_ids[:, :-1]					,  SCREAMING_SNAKE_CASE_					,  decoder_attention_mask=SCREAMING_SNAKE_CASE_					,  past_key_values=SCREAMING_SNAKE_CASE_					,  decoder_position_ids=SCREAMING_SNAKE_CASE_					,  )

   lowercase__  :   Any    		=      jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]					,  dtype="""i4""")
   lowercase__  :   List[Any]    		=      model.decode(
       decoder_input_ids[:, -1:]					,  SCREAMING_SNAKE_CASE_					,  decoder_attention_mask=SCREAMING_SNAKE_CASE_					,  past_key_values=outputs_cache.past_key_values					,  decoder_position_ids=SCREAMING_SNAKE_CASE_					,  )

   lowercase__  :   Any    		=      model.decode(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

   lowercase__  :   int    		=      np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])))
   self.parent.assertTrue(diff < 1E-3					,  msg=f'Max diff is {diff}')



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Tuple    		=      20
   lowercase__  :   Tuple    		=      model_class_name(SCREAMING_SNAKE_CASE_)

   lowercase__  :   List[Any]    		=      model.encode(inputs_dict["""input_ids"""])

   lowercase__		,    lowercase__  :   Dict    		=      (
       inputs_dict["""decoder_input_ids"""],
       inputs_dict["""decoder_attention_mask"""],
   )

   lowercase__  :   Optional[int]    		=      jnp.concatenate(
       [
           decoder_attention_mask,
           jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])),
       ]					,  axis=-1					,  )

   lowercase__  :   Tuple    		=      model.init_cache(decoder_input_ids.shape[0]					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   lowercase__  :   List[Any]    		=      jnp.broadcast_to(
       jnp.arange(decoder_input_ids.shape[-1] - 1)[None, :]					,  (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)					,  )

   lowercase__  :   Tuple    		=      model.decode(
       decoder_input_ids[:, :-1]					,  SCREAMING_SNAKE_CASE_					,  decoder_attention_mask=SCREAMING_SNAKE_CASE_					,  past_key_values=SCREAMING_SNAKE_CASE_					,  decoder_position_ids=SCREAMING_SNAKE_CASE_					,  )
   lowercase__  :   Union[str, Any]    		=      jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]					,  dtype="""i4""")
   lowercase__  :   Dict    		=      model.decode(
       decoder_input_ids[:, -1:]					,  SCREAMING_SNAKE_CASE_					,  past_key_values=outputs_cache.past_key_values					,  decoder_attention_mask=SCREAMING_SNAKE_CASE_					,  decoder_position_ids=SCREAMING_SNAKE_CASE_					,  )

   lowercase__  :   Dict    		=      model.decode(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  decoder_attention_mask=SCREAMING_SNAKE_CASE_)

   lowercase__  :   Any    		=      np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])))
   self.parent.assertTrue(diff < 1E-3					,  msg=f'Max diff is {diff}')

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_ , lowercase_=None , lowercase_=None , )		->	List[str]:


  '''simple docstring'''






  if attention_mask is None:
    lowercase__  :   int    		=      np.not_equal(lowercase_ , config.pad_token_id   ).astype(np.inta   )
  if decoder_attention_mask is None:
    lowercase__  :   Dict    		=      np.concatenate(
        [
            np.ones(decoder_input_ids[:, :1].shape , dtype=np.inta   ),
            np.not_equal(decoder_input_ids[:, 1:] , config.pad_token_id   ).astype(np.inta   ),
        ] , axis=-1 , )
  return {
      "input_ids": input_ids,
      "decoder_input_ids": decoder_input_ids,
      "attention_mask": attention_mask,
      "decoder_attention_mask": decoder_attention_mask,
  }



@require_flax
class       _snake_case   (	UpperCAmelCase_  ,						unittest.TestCase							):
 __lowerCAmelCase  :     Tuple        =			(
     (
         FlaxPegasusForConditionalGeneration,
         FlaxPegasusModel,
     )
     if is_flax_available()
     else ()
 )
 __lowerCAmelCase  :     Optional[Any]        =			(FlaxPegasusForConditionalGeneration,) if is_flax_available() else ()
 __lowerCAmelCase  :     List[str]        =			True
 __lowerCAmelCase  :     Optional[Any]        =			False
 __lowerCAmelCase  :     List[str]        =			False
 __lowerCAmelCase  :     List[Any]        =			False


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Any    		=      FlaxPegasusModelTester(self)
   lowercase__  :   int    		=      ConfigTester(self					,  config_class=SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self):


   '''simple docstring'''




   self.config_tester.run_common_tests()


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__		,    lowercase__  :   Optional[Any]    		=      self.model_tester.prepare_config_and_inputs_for_common()
   for model_class in self.all_model_classes:
     self.model_tester.check_use_cache_forward(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__		,    lowercase__  :   Optional[Any]    		=      self.model_tester.prepare_config_and_inputs_for_common()
   for model_class in self.all_model_classes:
     self.model_tester.check_use_cache_forward_with_attn_mask(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__		,    lowercase__  :   int    		=      self.model_tester.prepare_config_and_inputs_for_common()

   for model_class in self.all_model_classes:
     with self.subTest(model_class.__name__):
       lowercase__  :   Optional[int]    		=      self._prepare_for_class(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
       lowercase__  :   Dict    		=      model_class(SCREAMING_SNAKE_CASE_)

       @jax.jit
       def encode_jitted(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_=None					,  **SCREAMING_SNAKE_CASE_):
         return model.encode(input_ids=SCREAMING_SNAKE_CASE_					,  attention_mask=SCREAMING_SNAKE_CASE_)

       with self.subTest("""JIT Enabled"""):
         lowercase__  :   List[Any]    		=      encode_jitted(**SCREAMING_SNAKE_CASE_).to_tuple()

       with self.subTest("""JIT Disabled"""):
         with jax.disable_jit():
           lowercase__  :   Optional[int]    		=      encode_jitted(**SCREAMING_SNAKE_CASE_).to_tuple()

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


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__		,    lowercase__  :   str    		=      self.model_tester.prepare_config_and_inputs_for_common()

   for model_class in self.all_model_classes:
     with self.subTest(model_class.__name__):
       lowercase__  :   Dict    		=      model_class(SCREAMING_SNAKE_CASE_)
       lowercase__  :   Any    		=      model.encode(inputs_dict["""input_ids"""]					,  inputs_dict["""attention_mask"""])

       lowercase__  :   Any    		=      {
           """decoder_input_ids""": inputs_dict["""decoder_input_ids"""],
           """decoder_attention_mask""": inputs_dict["""decoder_attention_mask"""],
           """encoder_outputs""": encoder_outputs,
       }

       @jax.jit
       def decode_jitted(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):
         return model.decode(
             decoder_input_ids=SCREAMING_SNAKE_CASE_					,  decoder_attention_mask=SCREAMING_SNAKE_CASE_					,  encoder_outputs=SCREAMING_SNAKE_CASE_					,  )

       with self.subTest("""JIT Enabled"""):
         lowercase__  :   List[str]    		=      decode_jitted(**SCREAMING_SNAKE_CASE_).to_tuple()

       with self.subTest("""JIT Disabled"""):
         with jax.disable_jit():
           lowercase__  :   Tuple    		=      decode_jitted(**SCREAMING_SNAKE_CASE_).to_tuple()

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


 @slow
 def      lowercase__     (					self):


   '''simple docstring'''




   for model_class_name in self.all_model_classes:
     lowercase__  :   Any    		=      model_class_name.from_pretrained("""google/pegasus-large"""					,  from_pt=SCREAMING_SNAKE_CASE_)
     lowercase__  :   Any    		=      np.ones((1, 1))
     lowercase__  :   Optional[int]    		=      model(SCREAMING_SNAKE_CASE_)
     self.assertIsNotNone(SCREAMING_SNAKE_CASE_)



 @slow
 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   int    		=      FlaxPegasusForConditionalGeneration.from_pretrained("""google/pegasus-xsum""")
   lowercase__  :   Optional[int]    		=      PegasusTokenizer.from_pretrained("""google/pegasus-xsum""")

   lowercase__  :   Union[str, Any]    		=      [
       """ PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.""",
       """ The London trio are up for best UK act and best album, as well as getting two nominations in the best song category.\"We got told like this morning 'Oh I think you're nominated'\", said Dappy.\"And I was like 'Oh yeah, which one?' And now we've got nominated for four awards. I mean, wow!\"Bandmate Fazer added: \"We thought it's best of us to come down and mingle with everyone and say hello to the cameras. And now we find we've got four nominations.\"The band have two shots at the best song prize, getting the nod for their Tynchy Stryder collaboration Number One, and single Strong Again.Their album Uncle B will also go up against records by the likes of Beyonce and Kanye West.N-Dubz picked up the best newcomer Mobo in 2007, but female member Tulisa said they wouldn't be too disappointed if they didn't win this time around.\"At the end of the day we're grateful to be where we are in our careers.\"If it don't happen then it don't happen - live to fight another day and keep on making albums and hits for the fans.\"Dappy also revealed they could be performing live several times on the night.The group will be doing Number One and also a possible rendition of the War Child single, I Got Soul.The charity song is a  re-working of The Killers' All These Things That I've Done and is set to feature artists like Chipmunk, Ironik and Pixie Lott.This year's Mobos will be held outside of London for the first time, in Glasgow on 30 September.N-Dubz said they were looking forward to performing for their Scottish fans and boasted about their recent shows north of the border.\"We just done Edinburgh the other day,\" said Dappy.\"We smashed up an N-Dubz show over there. We done Aberdeen about three or four months ago - we smashed up that show over there! Everywhere we go we smash it up!\" """,
   ]

   lowercase__  :   Union[str, Any]    		=      [
       """California's largest electricity provider has turned off power to hundreds of thousands of customers.""",
       """Pop group N-Dubz have revealed they were surprised to get four nominations for this year's Mobo Awards.""",
   ]

   lowercase__  :   Dict    		=      tokenizer(SCREAMING_SNAKE_CASE_					,  return_tensors="""np"""					,  truncation=SCREAMING_SNAKE_CASE_					,  max_length=5_12					,  padding=SCREAMING_SNAKE_CASE_)
   lowercase__  :   Dict    		=      model.generate(**SCREAMING_SNAKE_CASE_					,  num_beams=2).sequences
   lowercase__  :   Dict    		=      tokenizer.batch_decode(SCREAMING_SNAKE_CASE_					,  skip_special_tokens=SCREAMING_SNAKE_CASE_)
   assert tgt_text == decoded






