

from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap



def    _lowercase			(	a__						:			Dict					)							->					str:





	"""simple docstring"""


	return getitem, k



def    _lowercase			(	a__						:			int							,  a__						:			Dict					)							->					Any:





	"""simple docstring"""


	return setitem, k, v



def    _lowercase			(	a__						:			Tuple					)							->					str:





	"""simple docstring"""


	return delitem, k



def    _lowercase			(	a__						:			int							,  a__						:			Optional[int]							,  *a__						:			Optional[Any]					)							->					List[Any]:





	"""simple docstring"""


	try:
		return fun(A__							,  *A__					), None
	except Exception as e:
		return None, e


__lowerCAmelCase			     =       (
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
)

__lowerCAmelCase			     =       [
    _set("""key_a""", """val_a"""),
    _set("""key_a""", """val_b"""),
]

__lowerCAmelCase			     =       [
    _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			     =       [
    _get("""key_a"""),
    _del("""key_a"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
    _del("""key_a"""),
    _get("""key_a"""),
]

__lowerCAmelCase			     =       [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

__lowerCAmelCase			     =       [
    *[_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    _lowercase			(	a__						:			Optional[int]					)							->					Dict:





	"""simple docstring"""


	_UpperCamelCase			=   HashMap(initial_block_size=4					)
	_UpperCamelCase			=   {}
	for _, (fun, *args) in enumerate(A__					):
		_UpperCamelCase			=   _run_operation(A__							,  A__							,  *A__					)
		_UpperCamelCase			=   _run_operation(A__							,  A__							,  *A__					)
		assert my_res == py_res
		assert str(A__					) == str(A__					)
		assert set(A__					) == set(A__					)
		assert len(A__					) == len(A__					)
		assert set(my.items()					) == set(py.items()					)




def    _lowercase			(	)							->					List[Any]:





	"""simple docstring"""


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

	_UpperCamelCase			=   {name for name in dir({}					) if is_public(A__					)}
	_UpperCamelCase			=   {name for name in dir(HashMap()					) if is_public(A__					)}

	assert dict_public_names > hash_public_names








from . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
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    bert_japanese,
    bertweet,
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    decision_transformer,
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    deit,
    deprecated,
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    dialogpt,
    dinat,
    distilbert,
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    dpr,
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    efficientformer,
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    electra,
    encodec,
    encoder_decoder,
    ernie,
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    esm,
    falcon,
    flaubert,
    flava,
    fnet,
    focalnet,
    fsmt,
    funnel,
    git,
    glpn,
    gpta,
    gpt_bigcode,
    gpt_neo,
    gpt_neox,
    gpt_neox_japanese,
    gpt_swa,
    gptj,
    gptsan_japanese,
    graphormer,
    groupvit,
    herbert,
    hubert,
    ibert,
    imagegpt,
    informer,
    instructblip,
    jukebox,
    layoutlm,
    layoutlmva,
    layoutlmva,
    layoutxlm,
    led,
    levit,
    lilt,
    llama,
    longformer,
    longta,
    luke,
    lxmert,
    mam_aaa,
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    mbart,
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    opt,
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    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
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    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
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    ta,
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    timm_backbone,
    transfo_xl,
    trocr,
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    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
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    vision_encoder_decoder,
    vision_text_dual_encoder,
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    vit,
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    wavaveca,
    wavaveca_conformer,
    wavaveca_phoneme,
    wavaveca_with_lm,
    wavlm,
    whisper,
    x_clip,
    xglm,
    xlm,
    xlm_prophetnet,
    xlm_roberta,
    xlm_roberta_xl,
    xlnet,
    xmod,
    yolos,
    yoso,
)





