





"""simple docstring"""




import unittest

import numpy as np

from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
    expand_dims,
    flatten_dict,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    reshape,
    squeeze,
    transpose,
)


if is_flax_available():
      import jax.numpy as jnp

if is_tf_available():
      import tensorflow as tf

if is_torch_available():
      import torch
class     SCREAMING_SNAKE_CASE       (unittest.TestCase				):


   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       List[str]:





     """simple docstring"""







     lowercase__           =  {
         'task_specific_params': {
             'summarization': {'length_penalty': 1.0, 'max_length': 128, 'min_length': 12, 'num_beams': 4},
             'summarization_cnn': {'length_penalty': 2.0, 'max_length': 142, 'min_length': 56, 'num_beams': 4},
             'summarization_xsum': {'length_penalty': 1.0, 'max_length': 62, 'min_length': 11, 'num_beams': 6},
         }
     }
     lowercase__           =  {
         'task_specific_params.summarization.length_penalty': 1.0,
         'task_specific_params.summarization.max_length': 128,
         'task_specific_params.summarization.min_length': 12,
         'task_specific_params.summarization.num_beams': 4,
         'task_specific_params.summarization_cnn.length_penalty': 2.0,
         'task_specific_params.summarization_cnn.max_length': 142,
         'task_specific_params.summarization_cnn.min_length': 56,
         'task_specific_params.summarization_cnn.num_beams': 4,
         'task_specific_params.summarization_xsum.length_penalty': 1.0,
         'task_specific_params.summarization_xsum.max_length': 62,
         'task_specific_params.summarization_xsum.min_length': 11,
         'task_specific_params.summarization_xsum.num_beams': 6,
     }

     self.assertEqual(flatten_dict(a	)      ,					a	)


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





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     self.assertTrue(np.allclose(transpose(a	)      ,					x.transpose()	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     self.assertTrue(np.allclose(transpose(a      ,					axes=(1, 2, 0)	)      ,					x.transpose((1, 2, 0)	)	)	)


   @require_torch
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Tuple	)->       Dict:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(transpose(a	)      ,					transpose(a	).numpy()	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(transpose(a      ,					axes=(1, 2, 0)	)      ,					transpose(a      ,					axes=(1, 2, 0)	).numpy()	)	)


   @require_tf
   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]	)->       Tuple:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(transpose(a	)      ,					transpose(a	).numpy()	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(transpose(a      ,					axes=(1, 2, 0)	)      ,					transpose(a      ,					axes=(1, 2, 0)	).numpy()	)	)


   @require_flax
   def 	SCREAMING_SNAKE_CASE_							(   self      :    str	)->       Dict:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(transpose(a	)      ,					np.asarray(transpose(a	)	)	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(transpose(a      ,					axes=(1, 2, 0)	)      ,					np.asarray(transpose(a      ,					axes=(1, 2, 0)	)	)	)	)


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





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     self.assertTrue(np.allclose(reshape(a      ,					(4, 3)	)      ,					np.reshape(a      ,					(4, 3)	)	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     self.assertTrue(np.allclose(reshape(a      ,					(12, 5)	)      ,					np.reshape(a      ,					(12, 5)	)	)	)


   @require_torch
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Union[str, Any]	)->       Any:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(reshape(a      ,					(4, 3)	)      ,					reshape(a      ,					(4, 3)	).numpy()	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(reshape(a      ,					(12, 5)	)      ,					reshape(a      ,					(12, 5)	).numpy()	)	)


   @require_tf
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any	)->       Optional[Any]:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(reshape(a      ,					(4, 3)	)      ,					reshape(a      ,					(4, 3)	).numpy()	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(reshape(a      ,					(12, 5)	)      ,					reshape(a      ,					(12, 5)	).numpy()	)	)


   @require_flax
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Union[str, Any]	)->       List[str]:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(reshape(a      ,					(4, 3)	)      ,					np.asarray(reshape(a      ,					(4, 3)	)	)	)	)

     lowercase__           =  np.random.randn(3      ,					4      ,					5	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(reshape(a      ,					(12, 5)	)      ,					np.asarray(reshape(a      ,					(12, 5)	)	)	)	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any	)->       Optional[Any]:





     """simple docstring"""







     lowercase__           =  np.random.randn(1      ,					3      ,					4	)
     self.assertTrue(np.allclose(squeeze(a	)      ,					np.squeeze(a	)	)	)

     lowercase__           =  np.random.randn(1      ,					4      ,					1      ,					5	)
     self.assertTrue(np.allclose(squeeze(a      ,					axis=2	)      ,					np.squeeze(a      ,					axis=2	)	)	)


   @require_torch
   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]	)->       Dict:





     """simple docstring"""







     lowercase__           =  np.random.randn(1      ,					3      ,					4	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(squeeze(a	)      ,					squeeze(a	).numpy()	)	)

     lowercase__           =  np.random.randn(1      ,					4      ,					1      ,					5	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(squeeze(a      ,					axis=2	)      ,					squeeze(a      ,					axis=2	).numpy()	)	)


   @require_tf
   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]	)->       int:





     """simple docstring"""







     lowercase__           =  np.random.randn(1      ,					3      ,					4	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(squeeze(a	)      ,					squeeze(a	).numpy()	)	)

     lowercase__           =  np.random.randn(1      ,					4      ,					1      ,					5	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(squeeze(a      ,					axis=2	)      ,					squeeze(a      ,					axis=2	).numpy()	)	)


   @require_flax
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]	)->       Tuple:





     """simple docstring"""







     lowercase__           =  np.random.randn(1      ,					3      ,					4	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(squeeze(a	)      ,					np.asarray(squeeze(a	)	)	)	)

     lowercase__           =  np.random.randn(1      ,					4      ,					1      ,					5	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(squeeze(a      ,					axis=2	)      ,					np.asarray(squeeze(a      ,					axis=2	)	)	)	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Union[str, Any]	)->       Optional[int]:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     self.assertTrue(np.allclose(expand_dims(a      ,					axis=1	)      ,					np.expand_dims(a      ,					axis=1	)	)	)


   @require_torch
   def 	SCREAMING_SNAKE_CASE_							(   self      :    str	)->       str:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  torch.tensor(a	)
     self.assertTrue(np.allclose(expand_dims(a      ,					axis=1	)      ,					expand_dims(a      ,					axis=1	).numpy()	)	)


   @require_tf
   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[Any]	)->       int:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  tf.constant(a	)
     self.assertTrue(np.allclose(expand_dims(a      ,					axis=1	)      ,					expand_dims(a      ,					axis=1	).numpy()	)	)


   @require_flax
   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]	)->       List[str]:





     """simple docstring"""







     lowercase__           =  np.random.randn(3      ,					4	)
     lowercase__           =  jnp.array(a	)
     self.assertTrue(np.allclose(expand_dims(a      ,					axis=1	)      ,					np.asarray(expand_dims(a      ,					axis=1	)	)	)	)









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

lowercase_          =		TypeVar("""KEY""")
lowercase_          =		TypeVar("""VAL""")
@dataclass(frozen=UpperCAmelCase      ,     slots=UpperCAmelCase				)
class     SCREAMING_SNAKE_CASE       (Generic[KEY, VAL]				):
   _UpperCamelCase   :		KEY
   _UpperCamelCase   :		VAL






class     SCREAMING_SNAKE_CASE       (_Item				):


   def __init__(   self      :    Optional[int]	)->       None:





     """simple docstring"""







     super().__init__(a      ,					a	)


   def __bool__(   self      :    str	)->       bool:





     """simple docstring"""







     return False






lowercase_          =		_DeletedItem()
class     SCREAMING_SNAKE_CASE       (MutableMapping[KEY, VAL]				):


   def __init__(   self      :    Tuple      ,					a      :    int = 8      ,					a      :    float = 0.75	)->       None:





     """simple docstring"""







     lowercase__           =  initial_block_size
     lowercase__           =  [None] * initial_block_size
     assert 0.0 < capacity_factor < 1.0
     lowercase__           =  capacity_factor
     lowercase__           =  0


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    KEY	)->       int:





     """simple docstring"""







     return hash(a	) % len(self._buckets	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]      ,					a      :    int	)->       int:





     """simple docstring"""







     return (ind + 1) % len(self._buckets	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    int      ,					a      :    KEY      ,					a      :    VAL	)->       bool:





     """simple docstring"""







     lowercase__           =  self._buckets[ind]
     if not stored:
       lowercase__           =  _Item(a      ,					a	)
       self._len += 1
       return True
     elif stored.key == key:
       lowercase__           =  _Item(a      ,					a	)
       return True
     else:
       return False


   def 	SCREAMING_SNAKE_CASE_							(   self      :    str	)->       bool:





     """simple docstring"""







     lowercase__           =  len(self._buckets	) * self._capacity_factor
     return len(self	) >= int(a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Tuple	)->       bool:





     """simple docstring"""







     if len(self._buckets	) <= self._initial_block_size:
       return False
     lowercase__           =  len(self._buckets	) * self._capacity_factor / 2
     return len(self	) < limit


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]      ,					a      :    int	)->       None:





     """simple docstring"""







     lowercase__           =  self._buckets
     lowercase__           =  [None] * new_size
     lowercase__           =  0
     for item in old_buckets:
       if item:
         self._add_item(item.key      ,					item.val	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       None:





     """simple docstring"""







     self._resize(len(self._buckets	) * 2	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       None:





     """simple docstring"""







     self._resize(len(self._buckets	) // 2	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    KEY	)->       Iterator[int]:





     """simple docstring"""







     lowercase__           =  self._get_bucket_index(a	)
     for _ in range(len(self._buckets	)	):
       yield ind
       lowercase__           =  self._get_next_ind(a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Tuple      ,					a      :    KEY      ,					a      :    VAL	)->       None:





     """simple docstring"""







     for ind in self._iterate_buckets(a	):
       if self._try_set(a      ,					a      ,					a	):
         break


   def __setitem__(   self      :    List[Any]      ,					a      :    KEY      ,					a      :    VAL	)->       None:





     """simple docstring"""







     if self._is_full():
       self._size_up()

     self._add_item(a      ,					a	)


   def __delitem__(   self      :    str      ,					a      :    KEY	)->       None:





     """simple docstring"""







     for ind in self._iterate_buckets(a	):
       lowercase__           =  self._buckets[ind]
       if item is None:
         raise KeyError(a	)
       if item is _deleted:
         continue
       if item.key == key:
         lowercase__           =  _deleted
         self._len -= 1
         break
     if self._is_sparse():
       self._size_down()


   def __getitem__(   self      :    List[str]      ,					a      :    KEY	)->       VAL:





     """simple docstring"""







     for ind in self._iterate_buckets(a	):
       lowercase__           =  self._buckets[ind]
       if item is None:
         break
       if item is _deleted:
         continue
       if item.key == key:
         return item.val
     raise KeyError(a	)


   def __len__(   self      :    Tuple	)->       int:





     """simple docstring"""







     return self._len


   def __iter__(   self      :    int	)->       Iterator[KEY]:





     """simple docstring"""







     yield from (item.key for item in self._buckets if item)


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





     """simple docstring"""







     lowercase__           =  ' ,'.join(
         f"""{item.key}: {item.val}""" for item in self._buckets if item	)
     return f"""HashMap({val_string})"""


