


"""simple docstring"""





import unittest

import numpy as np

from transformers import is_flax_available
from transformers.testing_utils import require_flax

from ..test_modeling_flax_common import ids_tensor


if is_flax_available():
 import jax
 import jax.numpy as jnp

 from transformers.generation import (
     FlaxForcedBOSTokenLogitsProcessor,
     FlaxForcedEOSTokenLogitsProcessor,
     FlaxLogitsProcessorList,
     FlaxMinLengthLogitsProcessor,
     FlaxTemperatureLogitsWarper,
     FlaxTopKLogitsWarper,
     FlaxTopPLogitsWarper,
 )



@require_flax
class 						snake_case_(				unittest.TestCase	):






     def    lowerCamelCase__   (		self     :    Any    , UpperCamelCase_     :    int    , UpperCamelCase_     :    int ):
           lowerCAmelCase    :		Optional[int]				=      jnp.ones((batch_size, length) ) / length
           return scores






     def    lowerCamelCase__   (		self     :    List[Any] ):
           lowerCAmelCase    :		List[Any]				=      None
           lowerCAmelCase    :		Optional[Any]				=      2_0

           lowerCAmelCase    :		Any				=      self._get_uniform_logits(batch_size=2    , length=UpperCamelCase_ )

           # tweak scores to not be uniform anymore
           lowerCAmelCase    :		Optional[int]				=      scores.at[1, 5].set((1 / length) + 0.1 )  # peak, 1st batch
           lowerCAmelCase    :		Optional[int]				=      scores.at[1, 1_0].set((1 / length) - 0.4 )  # valley, 1st batch

           # compute softmax
           lowerCAmelCase    :		Dict				=      jax.nn.softmax(UpperCamelCase_    , axis=-1 )

           lowerCAmelCase    :		Optional[Any]				=      FlaxTemperatureLogitsWarper(temperature=0.5 )
           lowerCAmelCase    :		List[str]				=      FlaxTemperatureLogitsWarper(temperature=1.3 )

           lowerCAmelCase    :		Optional[Any]				=      jax.nn.softmax(temp_dist_warper_sharper(UpperCamelCase_    , scores.copy()    , cur_len=UpperCamelCase_ )    , axis=-1 )
           lowerCAmelCase    :		Optional[Any]				=      jax.nn.softmax(temp_dist_warper_smoother(UpperCamelCase_    , scores.copy()    , cur_len=UpperCamelCase_ )    , axis=-1 )

           # uniform distribution stays uniform
           self.assertTrue(jnp.allclose(probs[0, :]    , warped_prob_sharp[0, :]    , atol=1E-3 ) )
           self.assertTrue(jnp.allclose(probs[0, :]    , warped_prob_smooth[0, :]    , atol=1E-3 ) )

           # sharp peaks get higher, valleys get lower
           self.assertLess(probs[1, :].max()    , warped_prob_sharp[1, :].max() )
           self.assertGreater(probs[1, :].min()    , warped_prob_sharp[1, :].min() )

           # smooth peaks get lower, valleys get higher
           self.assertGreater(probs[1, :].max()    , warped_prob_smooth[1, :].max() )
           self.assertLess(probs[1, :].min()    , warped_prob_smooth[1, :].min() )






     def    lowerCamelCase__   (		self     :    List[str] ):
           lowerCAmelCase    :		List[str]				=      None
           lowerCAmelCase    :		Optional[int]				=      1_0
           lowerCAmelCase    :		str				=      2

           # create ramp distribution
           lowerCAmelCase    :		Optional[Any]				=      np.broadcast_to(np.arange(UpperCamelCase_ )[None, :]    , (batch_size, vocab_size) ).copy()
           lowerCAmelCase    :		Optional[Any]				=      ramp_logits[1:, : vocab_size // 2] + vocab_size

           lowerCAmelCase    :		Optional[int]				=      FlaxTopKLogitsWarper(3 )

           lowerCAmelCase    :		Dict				=      top_k_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )

           # check that correct tokens are filtered
           self.assertListEqual(jnp.isinf(scores[0] ).tolist()    , 7 * [True] + 3 * [False] )
           self.assertListEqual(jnp.isinf(scores[1] ).tolist()    , 2 * [True] + 3 * [False] + 5 * [True] )

           # check special case
           lowerCAmelCase    :		List[Any]				=      5
           lowerCAmelCase    :		List[Any]				=      FlaxTopKLogitsWarper(top_k=1    , filter_value=0.0    , min_tokens_to_keep=3 )

           lowerCAmelCase    :		Dict				=      np.broadcast_to(np.arange(UpperCamelCase_ )[None, :]    , (batch_size, length) ).copy()
           lowerCAmelCase    :		Optional[int]				=      top_k_warp_safety_check(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )

           # min_tokens overwrites k: 3 tokens are kept => 2 tokens are nullified
           self.assertListEqual((scores == 0.0).sum(axis=-1 ).tolist()    , [2, 2] )






     def    lowerCamelCase__   (		self     :    List[Any] ):
           lowerCAmelCase    :		int				=      None
           lowerCAmelCase    :		Dict				=      1_0
           lowerCAmelCase    :		List[str]				=      2

           # create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
           lowerCAmelCase    :		List[Any]				=      np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.15, 0.3, 0.3, 0.25]] ) )

           lowerCAmelCase    :		List[str]				=      FlaxTopPLogitsWarper(0.8 )
           lowerCAmelCase    :		Optional[Any]				=      np.exp(top_p_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ ) )

           # dist should be filtered to keep min num values so that sum is >= top_p
           # exp (-inf) => 0
           lowerCAmelCase    :		Dict				=      np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]] )
           self.assertTrue(np.allclose(UpperCamelCase_    , UpperCamelCase_    , atol=1E-3 ) )

           # check edge cases with negative and extreme logits
           lowerCAmelCase    :		Optional[Any]				=      np.broadcast_to(np.arange(UpperCamelCase_ )[None, :]    , (batch_size, vocab_size) ).copy() - (
               vocab_size // 2
           )

           # make ramp_logits more extreme
           lowerCAmelCase    :		Optional[int]				=      ramp_logits[1] * 100.0

           # make sure at least 2 tokens are kept
           lowerCAmelCase    :		Dict				=      FlaxTopPLogitsWarper(0.9    , min_tokens_to_keep=2    , filter_value=0.0 )
           lowerCAmelCase    :		str				=      top_p_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )

           # first batch should keep three tokens, second batch would keep only 1, but due to `min_tokens_to_keep=2` keeps 2.
           self.assertListEqual((filtered_dist != 0.0).sum(axis=-1 ).tolist()    , [3, 2] )






     def    lowerCamelCase__   (		self     :    Optional[Any] ):
           lowerCAmelCase    :		Any				=      2_0
           lowerCAmelCase    :		Optional[int]				=      4
           lowerCAmelCase    :		Dict				=      0

           lowerCAmelCase    :		Any				=      FlaxMinLengthLogitsProcessor(min_length=1_0    , eos_token_id=UpperCamelCase_ )

           # check that min length is applied at length 5
           lowerCAmelCase    :		List[Any]				=      ids_tensor((batch_size, 2_0)    , vocab_size=2_0 )
           lowerCAmelCase    :		int				=      5
           lowerCAmelCase    :		Any				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		Dict				=      min_dist_processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist()    , 4 * [-float('''inf''' )] )

           # check that min length is not applied anymore at length 15
           lowerCAmelCase    :		Any				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		Optional[Any]				=      1_5
           lowerCAmelCase    :		str				=      min_dist_processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           self.assertFalse(jnp.isinf(UpperCamelCase_ ).any() )






     def    lowerCamelCase__   (		self     :    List[Any] ):
           lowerCAmelCase    :		str				=      2_0
           lowerCAmelCase    :		Union[str, Any]				=      4
           lowerCAmelCase    :		Optional[Any]				=      0

           lowerCAmelCase    :		int				=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_ )

           # check that all scores are -inf except the bos_token_id score
           lowerCAmelCase    :		Optional[int]				=      ids_tensor((batch_size, 1)    , vocab_size=2_0 )
           lowerCAmelCase    :		Any				=      1
           lowerCAmelCase    :		List[str]				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		Dict				=      logits_processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           self.assertTrue(jnp.isneginf(scores[:, bos_token_id + 1 :] ).all() )
           self.assertListEqual(scores[:, bos_token_id].tolist()    , 4 * [0] )  # score for bos_token_id shold be zero

           # check that bos_token_id is not forced if current length is greater than 1
           lowerCAmelCase    :		str				=      3
           lowerCAmelCase    :		Optional[Any]				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		Union[str, Any]				=      logits_processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           self.assertFalse(jnp.isinf(UpperCamelCase_ ).any() )






     def    lowerCamelCase__   (		self     :    List[Any] ):
           lowerCAmelCase    :		Optional[Any]				=      2_0
           lowerCAmelCase    :		Dict				=      4
           lowerCAmelCase    :		Tuple				=      0
           lowerCAmelCase    :		Any				=      5

           lowerCAmelCase    :		Dict				=      FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_    , eos_token_id=UpperCamelCase_ )

           # check that all scores are -inf except the eos_token_id when max_length is reached
           lowerCAmelCase    :		str				=      ids_tensor((batch_size, 4)    , vocab_size=2_0 )
           lowerCAmelCase    :		int				=      4
           lowerCAmelCase    :		str				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		List[Any]				=      logits_processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           self.assertTrue(jnp.isneginf(scores[:, eos_token_id + 1 :] ).all() )
           self.assertListEqual(scores[:, eos_token_id].tolist()    , 4 * [0] )  # score for eos_token_id should be zero

           # check that eos_token_id is not forced if max_length is not reached
           lowerCAmelCase    :		Tuple				=      3
           lowerCAmelCase    :		Union[str, Any]				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		Dict				=      logits_processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           self.assertFalse(jnp.isinf(UpperCamelCase_ ).any() )






     def    lowerCamelCase__   (		self     :    str ):
           lowerCAmelCase    :		Union[str, Any]				=      4
           lowerCAmelCase    :		Tuple				=      1_0
           lowerCAmelCase    :		Union[str, Any]				=      1_5
           lowerCAmelCase    :		Union[str, Any]				=      2
           lowerCAmelCase    :		int				=      1
           lowerCAmelCase    :		Tuple				=      1_5

           # dummy input_ids and scores
           lowerCAmelCase    :		Union[str, Any]				=      ids_tensor((batch_size, sequence_length)    , UpperCamelCase_ )
           lowerCAmelCase    :		Optional[int]				=      input_ids.copy()

           lowerCAmelCase    :		Tuple				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		List[str]				=      scores.copy()

           # instantiate all dist processors
           lowerCAmelCase    :		Tuple				=      FlaxTemperatureLogitsWarper(temperature=0.5 )
           lowerCAmelCase    :		Optional[Any]				=      FlaxTopKLogitsWarper(3 )
           lowerCAmelCase    :		int				=      FlaxTopPLogitsWarper(0.8 )

           # instantiate all logits processors
           lowerCAmelCase    :		List[Any]				=      FlaxMinLengthLogitsProcessor(min_length=1_0    , eos_token_id=UpperCamelCase_ )
           lowerCAmelCase    :		List[Any]				=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_ )
           lowerCAmelCase    :		Union[str, Any]				=      FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_    , eos_token_id=UpperCamelCase_ )

           lowerCAmelCase    :		List[str]				=      1_0

           # no processor list
           lowerCAmelCase    :		Dict				=      temp_dist_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           lowerCAmelCase    :		Dict				=      top_k_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           lowerCAmelCase    :		Optional[Any]				=      top_p_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           lowerCAmelCase    :		Any				=      min_dist_proc(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           lowerCAmelCase    :		int				=      bos_dist_proc(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
           lowerCAmelCase    :		List[Any]				=      eos_dist_proc(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )

           # with processor list
           lowerCAmelCase    :		Tuple				=      FlaxLogitsProcessorList(
               [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc] )
           lowerCAmelCase    :		Optional[int]				=      processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )

           # scores should be equal
           self.assertTrue(jnp.allclose(UpperCamelCase_    , UpperCamelCase_    , atol=1E-3 ) )

           # input_ids should never be changed
           self.assertListEqual(input_ids.tolist()    , input_ids_comp.tolist() )






     def    lowerCamelCase__   (		self     :    Dict ):
           lowerCAmelCase    :		Dict				=      4
           lowerCAmelCase    :		str				=      1_0
           lowerCAmelCase    :		str				=      1_5
           lowerCAmelCase    :		Union[str, Any]				=      2
           lowerCAmelCase    :		List[Any]				=      1
           lowerCAmelCase    :		List[Any]				=      1_5

           # dummy input_ids and scores
           lowerCAmelCase    :		int				=      ids_tensor((batch_size, sequence_length)    , UpperCamelCase_ )
           lowerCAmelCase    :		Dict				=      input_ids.copy()

           lowerCAmelCase    :		str				=      self._get_uniform_logits(UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		Any				=      scores.copy()

           # instantiate all dist processors
           lowerCAmelCase    :		Optional[Any]				=      FlaxTemperatureLogitsWarper(temperature=0.5 )
           lowerCAmelCase    :		str				=      FlaxTopKLogitsWarper(3 )
           lowerCAmelCase    :		Optional[int]				=      FlaxTopPLogitsWarper(0.8 )

           # instantiate all logits processors
           lowerCAmelCase    :		str				=      FlaxMinLengthLogitsProcessor(min_length=1_0    , eos_token_id=UpperCamelCase_ )
           lowerCAmelCase    :		Tuple				=      FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase_ )
           lowerCAmelCase    :		List[str]				=      FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase_    , eos_token_id=UpperCamelCase_ )

           lowerCAmelCase    :		Optional[Any]				=      1_0

           # no processor list
           def run_no_processor_list(UpperCamelCase_     :    List[Any]    , UpperCamelCase_     :    Dict    , UpperCamelCase_     :    Optional[Any] ):
                 lowerCAmelCase    :		Optional[Any]				=      temp_dist_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 lowerCAmelCase    :		List[Any]				=      top_k_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 lowerCAmelCase    :		Optional[Any]				=      top_p_warp(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 lowerCAmelCase    :		Dict				=      min_dist_proc(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 lowerCAmelCase    :		int				=      bos_dist_proc(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 lowerCAmelCase    :		str				=      eos_dist_proc(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 return scores

           # with processor list
           def run_processor_list(UpperCamelCase_     :    int    , UpperCamelCase_     :    Optional[int]    , UpperCamelCase_     :    Dict ):
                 lowerCAmelCase    :		List[Any]				=      FlaxLogitsProcessorList(
                     [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc] )
                 lowerCAmelCase    :		Optional[int]				=      processor(UpperCamelCase_    , UpperCamelCase_    , cur_len=UpperCamelCase_ )
                 return scores

           lowerCAmelCase    :		Any				=      jax.jit(UpperCamelCase_ )
           lowerCAmelCase    :		int				=      jax.jit(UpperCamelCase_ )

           lowerCAmelCase    :		str				=      jitted_run_no_processor_list(UpperCamelCase_    , UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		int				=      jitted_run_processor_list(UpperCamelCase_    , UpperCamelCase_    , UpperCamelCase_ )

           # scores should be equal
           self.assertTrue(jnp.allclose(UpperCamelCase_    , UpperCamelCase_    , atol=1E-3 ) )

           # input_ids should never be changed
           self.assertListEqual(input_ids.tolist()    , input_ids_comp.tolist() )





'''simple docstring'''
from __future__ import annotations

from random import random
from typing import Generic, TypeVar

lowerCamelCase :      Union[str, Any]					 =     TypeVar("KT")
lowerCamelCase :      Dict					 =     TypeVar("VT")







class 							A__    (       Generic[KT, VT]  ):





  def __init__(		self      :	str							,					_a      :	KT | str = "root"							,					_a      :	VT | None = None )	->    Dict:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =key
       _SCREAMING_SNAKE_CASE							    =value
       _SCREAMING_SNAKE_CASE							    =[]





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





       '''simple docstring'''






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





  @property
  def 						A  (		self      :	int )	->    int:





       '''simple docstring'''






       return len(self.forward )







class 							A__    (       Generic[KT, VT]  ):





  def __init__(		self      :	Optional[Any]							,					_a      :	float = 0.5							,					_a      :	int = 16 )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =Node[KT, VT]()
       _SCREAMING_SNAKE_CASE							    =0
       _SCREAMING_SNAKE_CASE							    =p
       _SCREAMING_SNAKE_CASE							    =max_level





  def __str__(		self      :	Tuple )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =list(self )

       if len(_a ) == 0:
            return f"SkipList(level={self.level})"

       _SCREAMING_SNAKE_CASE							    =max((len(str(_a ) ) for item in items)							,					default=4 )
       _SCREAMING_SNAKE_CASE							    =max(_a							,					4 ) + 4

       _SCREAMING_SNAKE_CASE							    =self.head
       _SCREAMING_SNAKE_CASE							    =[]

       _SCREAMING_SNAKE_CASE							    =node.forward.copy()
       lines.append(f"[{node.key}]".ljust(_a							,					'-' ) + '* ' * len(_a ) )
       lines.append(' ' * label_size + '| ' * len(_a ) )

       while len(node.forward ) != 0:
            _SCREAMING_SNAKE_CASE							    =node.forward[0]

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

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





  def __iter__(		self      :	Dict )	->    Optional[Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =self.head

       while len(node.forward ) != 0:
            yield node.forward[0].key
            _SCREAMING_SNAKE_CASE							    =node.forward[0]





  def 						A  (		self      :	List[Any] )	->    int:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =1
       while random() < self.p and level < self.max_level:
            level += 1

       return level





  def 						A  (		self      :	Any							,					_a      :	Any )	->    tuple[Node[KT, VT] | None, list[Node[KT, VT]]]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =[]

       _SCREAMING_SNAKE_CASE							    =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:
                 _SCREAMING_SNAKE_CASE							    =node.forward[i]
            # Each leftmost node (relative to searched node) will potentially have to
            # be updated.
            update_vector.append(_a )

       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 						A  (		self      :	Union[str, Any]							,					_a      :	KT )	->    int:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE    ,						_SCREAMING_SNAKE_CASE							    =self._locate_node(_a )

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





  def 						A  (		self      :	Optional[Any]							,					_a      :	KT							,					_a      :	VT )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE    ,						_SCREAMING_SNAKE_CASE							    =self._locate_node(_a )
       if node is not None:
            _SCREAMING_SNAKE_CASE							    =value
       else:
            _SCREAMING_SNAKE_CASE							    =self.random_level()

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

            _SCREAMING_SNAKE_CASE							    =Node(_a							,					_a )

            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(_a )
                 else:
                      _SCREAMING_SNAKE_CASE							    =new_node





  def 						A  (		self      :	List[str]							,					_a      :	VT )	->    VT | None:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE    ,						_SCREAMING_SNAKE_CASE							    =self._locate_node(_a )

       if node is not None:
            return node.value

       return None


def        _lowerCAmelCase					(						)      ->			str:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =SkipList()
     skip_list.insert('Key1'							, 3				)
     skip_list.insert('Key2'							, 12				)
     skip_list.insert('Key3'							, 41				)
     skip_list.insert('Key4'							, -19				)

     _SCREAMING_SNAKE_CASE							    =skip_list.head
     _SCREAMING_SNAKE_CASE							    ={}
     while node.level != 0:
          _SCREAMING_SNAKE_CASE							    =node.forward[0]
          _SCREAMING_SNAKE_CASE							    =node.value

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


def        _lowerCAmelCase					(						)      ->			Optional[int]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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				)

     _SCREAMING_SNAKE_CASE							    =skip_list.head
     _SCREAMING_SNAKE_CASE							    ={}
     while node.level != 0:
          _SCREAMING_SNAKE_CASE							    =node.forward[0]
          _SCREAMING_SNAKE_CASE							    =node.value

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


def        _lowerCAmelCase					(						)      ->			Tuple:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =SkipList()
     assert skip_list.find('Some key'				) is None


def        _lowerCAmelCase					(						)      ->			str:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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        _lowerCAmelCase					(						)      ->			List[Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =SkipList()
     skip_list.delete('Some key'				)

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


def        _lowerCAmelCase					(						)      ->			Optional[Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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        _lowerCAmelCase					(						)      ->			List[str]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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        _lowerCAmelCase					(						)      ->			Dict:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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(_UpperCamelCase						:     Dict				):
          yield node.key
          for forward_node in node.forward:
               yield from traverse_keys(_UpperCamelCase				)

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


def        _lowerCAmelCase					(						)      ->			Union[str, Any]:
     """simple docstring"""




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

     _SCREAMING_SNAKE_CASE							    =SkipList()
     for i in range(10				):
          skip_list.insert(_UpperCamelCase							, _UpperCamelCase				)
     assert is_sorted(list(_UpperCamelCase				)				)
     skip_list.delete(5				)
     skip_list.delete(8				)
     skip_list.delete(2				)
     assert is_sorted(list(_UpperCamelCase				)				)
     skip_list.insert(-12							, -12				)
     skip_list.insert(77							, 77				)
     assert is_sorted(list(_UpperCamelCase				)				)


def        _lowerCAmelCase					(						)      ->			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        _lowerCAmelCase					(						)      ->			Dict:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =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(_UpperCamelCase				)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()
