


'''simple docstring'''





from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

__lowerCamelCase												=						TypeVar('''KEY''')
__lowerCamelCase												=						TypeVar('''VAL''')




@dataclass(frozen=_snake_case						, slots=_snake_case						)
class 				UpperCAmelCase			(			Generic[KEY, VAL]						):
 UpperCAmelCase				=					42
 UpperCAmelCase				=					42




class 				UpperCAmelCase			(			_Item						):


 def __init__(      self							:	Optional[Any] ):
    super().__init__(__lowerCamelCase			,       __lowerCamelCase )





 def __bool__(      self							:	str ):
    return False

__lowerCamelCase												=						_DeletedItem()




class 				UpperCAmelCase			(			MutableMapping[KEY, VAL]						):


 def __init__(      self							:	Union[str, Any]			,       __lowerCamelCase							:	int = 8			,       __lowerCamelCase							:	float = 0.75 ):
    UpperCAmelCase__	:Tuple      =      initial_block_size
    UpperCAmelCase__	:list[_Item | None]      =      [None] * initial_block_size
    assert 0.0 < capacity_factor < 1.0
    UpperCAmelCase__	:int      =      capacity_factor
    UpperCAmelCase__	:List[str]      =      0


 def        __SCREAMING_SNAKE_CASE					(      self							:	str			,       __lowerCamelCase							:	KEY ):
    return hash(__lowerCamelCase ) % len(self._buckets )


 def        __SCREAMING_SNAKE_CASE					(      self							:	Tuple			,       __lowerCamelCase							:	int ):
    return (ind + 1) % len(self._buckets )


 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[Any]			,       __lowerCamelCase							:	int			,       __lowerCamelCase							:	KEY			,       __lowerCamelCase							:	VAL ):
    UpperCAmelCase__	:Union[str, Any]      =      self._buckets[ind]
    if not stored:
       UpperCAmelCase__	:str      =      _Item(__lowerCamelCase			,       __lowerCamelCase )
       self._len += 1
       return True
    elif stored.key == key:
       UpperCAmelCase__	:Dict      =      _Item(__lowerCamelCase			,       __lowerCamelCase )
       return True
    else:
       return False


 def        __SCREAMING_SNAKE_CASE					(      self							:	List[str] ):
    UpperCAmelCase__	:int      =      len(self._buckets ) * self._capacity_factor
    return len(self ) >= int(__lowerCamelCase )


 def        __SCREAMING_SNAKE_CASE					(      self							:	Dict ):
    if len(self._buckets ) <= self._initial_block_size:
       return False
    UpperCAmelCase__	:List[str]      =      len(self._buckets ) * self._capacity_factor / 2
    return len(self ) < limit


 def        __SCREAMING_SNAKE_CASE					(      self							:	Union[str, Any]			,       __lowerCamelCase							:	int ):
    UpperCAmelCase__	:Optional[Any]      =      self._buckets
    UpperCAmelCase__	:List[Any]      =      [None] * new_size
    UpperCAmelCase__	:Optional[Any]      =      0
    for item in old_buckets:
       if item:
          self._add_item(item.key			,       item.val )


 def        __SCREAMING_SNAKE_CASE					(      self							:	int ):
    self._resize(len(self._buckets ) * 2 )


 def        __SCREAMING_SNAKE_CASE					(      self							:	int ):
    self._resize(len(self._buckets ) // 2 )


 def        __SCREAMING_SNAKE_CASE					(      self							:	Union[str, Any]			,       __lowerCamelCase							:	KEY ):
    UpperCAmelCase__	:List[Any]      =      self._get_bucket_index(__lowerCamelCase )
    for _ in range(len(self._buckets ) ):
       yield ind
       UpperCAmelCase__	:Union[str, Any]      =      self._get_next_ind(__lowerCamelCase )


 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[int]			,       __lowerCamelCase							:	KEY			,       __lowerCamelCase							:	VAL ):
    for ind in self._iterate_buckets(__lowerCamelCase ):
       if self._try_set(__lowerCamelCase			,       __lowerCamelCase			,       __lowerCamelCase ):
          break


 def __setitem__(      self							:	Union[str, Any]			,       __lowerCamelCase							:	KEY			,       __lowerCamelCase							:	VAL ):
    if self._is_full():
       self._size_up()

    self._add_item(__lowerCamelCase			,       __lowerCamelCase )


 def __delitem__(      self							:	List[Any]			,       __lowerCamelCase							:	KEY ):
    for ind in self._iterate_buckets(__lowerCamelCase ):
       UpperCAmelCase__	:Tuple      =      self._buckets[ind]
       if item is None:
          raise KeyError(__lowerCamelCase )
       if item is _deleted:
          continue
       if item.key == key:
          UpperCAmelCase__	:Tuple      =      _deleted
          self._len -= 1
          break
    if self._is_sparse():
       self._size_down()


 def __getitem__(      self							:	str			,       __lowerCamelCase							:	KEY ):
    for ind in self._iterate_buckets(__lowerCamelCase ):
       UpperCAmelCase__	:str      =      self._buckets[ind]
       if item is None:
          break
       if item is _deleted:
          continue
       if item.key == key:
          return item.val
    raise KeyError(__lowerCamelCase )


 def __len__(      self							:	List[Any] ):
    return self._len


 def __iter__(      self							:	Any ):
    yield from (item.key for item in self._buckets if item)





 def __repr__(      self							:	int ):
    UpperCAmelCase__	:Optional[int]      =      ''' ,'''.join(
        f'''{item.key}: {item.val}''' for item in self._buckets if item )
    return f'''HashMap({val_string})'''







'''simple docstring'''





from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
    import numpy as np
    import tensorflow as tf

    from transformers import TFCamembertModel




@require_tf
@require_sentencepiece
@require_tokenizers
class 				UpperCAmelCase			(			unittest.TestCase						):


 @slow
 def        __SCREAMING_SNAKE_CASE					(      self							:	List[str] ):
    UpperCAmelCase__	:List[str]      =      TFCamembertModel.from_pretrained('''jplu/tf-camembert-base''' )

    UpperCAmelCase__	:Optional[Any]      =      tf.convert_to_tensor(
        [[5, 1_2_1, 1_1, 6_6_0, 1_6, 7_3_0, 2_5_5_4_3, 1_1_0, 8_3, 6]]			,       dtype=tf.intaa			,       )  # J'aime le camembert !"

    UpperCAmelCase__	:Any      =      model(__lowerCamelCase )['''last_hidden_state''']
    UpperCAmelCase__	:Dict      =      tf.TensorShape((1, 1_0, 7_6_8) )
    self.assertEqual(output.shape			,       __lowerCamelCase )
    # compare the actual values for a slice.
    UpperCAmelCase__	:Any      =      tf.convert_to_tensor(
        [[[-0.02_54, 0.02_35, 0.10_27], [0.06_06, -0.18_11, -0.04_18], [-0.15_61, -0.11_27, 0.26_87]]]			,       dtype=tf.floataa			,       )
    # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
    # camembert.eval()
    # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

    self.assertTrue(np.allclose(output[:, :3, :3].numpy()			,       expected_slice.numpy()			,       atol=1e-4 ) )



