





'''simple docstring'''


from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap
def 							UpperCAmelCase_  (						__lowerCamelCase : Optional[Any]			):
   return getitem, k
def 							UpperCAmelCase_  (						__lowerCamelCase : int     ,__lowerCamelCase : List[str]			):
   return setitem, k, v
def 							UpperCAmelCase_  (						__lowerCamelCase : List[Any]			):
   return delitem, k
def 							UpperCAmelCase_  (						__lowerCamelCase : Any     ,__lowerCamelCase : Optional[int]     ,*__lowerCamelCase : Tuple			):
   try:
      return fun(__lowerCamelCase     ,*__lowerCamelCase			), None
   except Exception as e:
      return None, e


lowerCAmelCase :					Optional[Any] 							=(
    _set('''key_a''', '''val_a'''),
    _set('''key_b''', '''val_b'''),
)

lowerCAmelCase :					Optional[int] 							=[
    _set('''key_a''', '''val_a'''),
    _set('''key_a''', '''val_b'''),
]

lowerCAmelCase :					Dict 							=[
    _set('''key_a''', '''val_a'''),
    _set('''key_b''', '''val_b'''),
    _del('''key_a'''),
    _del('''key_b'''),
    _set('''key_a''', '''val_a'''),
    _del('''key_a'''),
]

lowerCAmelCase :					Any 							=[
    _get('''key_a'''),
    _del('''key_a'''),
    _set('''key_a''', '''val_a'''),
    _del('''key_a'''),
    _del('''key_a'''),
    _get('''key_a'''),
]

lowerCAmelCase :					List[str] 							=[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

lowerCAmelCase :					List[Any] 							=[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set('''key_a''', '''val_b'''),
]
@pytest.mark.parametrize(
    "operations"     ,(
        pytest.param(_add_items     ,id="add items"			),
        pytest.param(_overwrite_items     ,id="overwrite items"			),
        pytest.param(_delete_items     ,id="delete items"			),
        pytest.param(_access_absent_items     ,id="access absent items"			),
        pytest.param(_add_with_resize_up     ,id="add with resize up"			),
        pytest.param(_add_with_resize_down     ,id="add with resize down"			),
    )     ,)
def 							UpperCAmelCase_  (						__lowerCamelCase : Union[str, Any]			):
   lowercase_      :List[Any]         =			HashMap(initial_block_size=4			)
   lowercase_      :List[str]         =			{}
   for _, (fun, *args) in enumerate(__lowerCamelCase			):
      lowercase_      ,							lowercase_      :List[Any]         =			_run_operation(__lowerCamelCase     ,__lowerCamelCase     ,*__lowerCamelCase			)
      lowercase_      ,							lowercase_      :str         =			_run_operation(__lowerCamelCase     ,__lowerCamelCase     ,*__lowerCamelCase			)
      assert my_res == py_res
      assert str(__lowerCamelCase			) == str(__lowerCamelCase			)
      assert set(__lowerCamelCase			) == set(__lowerCamelCase			)
      assert len(__lowerCamelCase			) == len(__lowerCamelCase			)
      assert set(my.items()			) == set(py.items()			)


def 							UpperCAmelCase_  (						):
   def is_public(__lowerCamelCase : str			) -> bool:
      return not name.startswith("_"			)

   lowercase_      :Union[str, Any]         =			{name for name in dir({}			) if is_public(__lowerCamelCase			)}
   lowercase_      :Union[str, Any]         =			{name for name in dir(HashMap()			) if is_public(__lowerCamelCase			)}

   assert dict_public_names > hash_public_names









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase :					Optional[int] 							={'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					Optional[Any] 							=[
     '''WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''WavLMForAudioFrameClassification''',
     '''WavLMForCTC''',
     '''WavLMForSequenceClassification''',
     '''WavLMForXVector''',
     '''WavLMModel''',
     '''WavLMPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_wavlm import (
      WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      WavLMForAudioFrameClassification,
      WavLMForCTC,
      WavLMForSequenceClassification,
      WavLMForXVector,
      WavLMModel,
      WavLMPreTrainedModel,
  )

else:
 import sys

 lowerCAmelCase :					Union[str, Any] 							=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


