
from collections.abc import Generator
from math import sin



def 						lowercase_      (       A__		)							->							bytes:
    """simple docstring"""

    if len(A__		) != 32:
        raise ValueError("Input must be of length 32"		)

    snake_case								= b""
    for i in [3, 2, 1, 0]:
        little_endian += string_aa[8 * i : 8 * i + 8]
    return little_endian



def 						lowercase_      (       A__		)							->							bytes:
    """simple docstring"""

    if i < 0:
        raise ValueError("Input must be non-negative"		)

    snake_case								= format(A__			,		"08x"		)[-8:]
    snake_case								= b""
    for i in [3, 2, 1, 0]:
        little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode("utf-8"		)
    return little_endian_hex



def 						lowercase_      (       A__		)							->							bytes:
    """simple docstring"""

    snake_case								= b""
    for char in message:
        bit_string += format(A__			,		"08b"		).encode("utf-8"		)
    snake_case								= format(len(A__		)			,		"064b"		).encode("utf-8"		)

    # Pad bit_string to a multiple of 512 chars
    bit_string += b"1"
    while len(A__		) % 512 != 448:
        bit_string += b"0"
    bit_string += to_little_endian(start_len[32:]		) + to_little_endian(start_len[:32]		)

    return bit_string



def 						lowercase_      (       A__		)							->							Generator[list[int], None, None]:
    """simple docstring"""

    if len(A__		) % 512 != 0:
        raise ValueError("Input must have length that's a multiple of 512"		)

    for pos in range(0			,		len(A__		)			,		512		):
        snake_case								= bit_string[pos : pos + 512]
        snake_case								= []
        for i in range(0			,		512			,		32		):
            block_words.append(int(to_little_endian(block[i : i + 32]		)			,		2		)		)
        yield block_words



def 						lowercase_      (       A__		)							->							int:
    """simple docstring"""

    if i < 0:
        raise ValueError("Input must be non-negative"		)

    snake_case								= format(A__			,		"032b"		)
    snake_case								= ""
    for c in i_str:
        new_str += "1" if c == "0" else "0"
    return int(A__			,		2		)



def 						lowercase_      (       A__			,		A__		)							->							int:
    """simple docstring"""

    return (a + b) % 2**32



def 						lowercase_      (       A__			,		A__		)							->							int:
    """simple docstring"""

    if i < 0:
        raise ValueError("Input must be non-negative"		)
    if shift < 0:
        raise ValueError("Shift must be non-negative"		)
    return ((i << shift) ^ (i >> (32 - shift))) % 2**32



def 						lowercase_      (       A__		)							->							bytes:
    """simple docstring"""

    snake_case								= preprocess(A__		)

    snake_case								= [int(2**32 * abs(sin(i + 1		)		)		) for i in range(64		)]

    # Starting states
    snake_case								= 0x6_7_4_5_2_3_0_1
    snake_case								= 0xE_F_C_D_A_B_8_9
    snake_case								= 0x9_8_B_A_D_C_F_E
    snake_case								= 0x1_0_3_2_5_4_7_6

    snake_case								= [
        7,
        12,
        17,
        22,
        7,
        12,
        17,
        22,
        7,
        12,
        17,
        22,
        7,
        12,
        17,
        22,
        5,
        9,
        14,
        20,
        5,
        9,
        14,
        20,
        5,
        9,
        14,
        20,
        5,
        9,
        14,
        20,
        4,
        11,
        16,
        23,
        4,
        11,
        16,
        23,
        4,
        11,
        16,
        23,
        4,
        11,
        16,
        23,
        6,
        10,
        15,
        21,
        6,
        10,
        15,
        21,
        6,
        10,
        15,
        21,
        6,
        10,
        15,
        21,
    ]

    # Process bit string in chunks, each with 16 32-char words
    for block_words in get_block_words(A__		):
        snake_case								= aa
        snake_case								= ba
        snake_case								= ca
        snake_case								= da

        # Hash current chunk
        for i in range(64		):
            if i <= 15:
                # f = (b & c) | (not_32(b) & d)     # Alternate definition for f
                snake_case								= d ^ (b & (c ^ d))
                snake_case								= i
            elif i <= 31:
                # f = (d & b) | (not_32(d) & c)     # Alternate definition for f
                snake_case								= c ^ (d & (b ^ c))
                snake_case								= (5 * i + 1) % 16
            elif i <= 47:
                snake_case								= b ^ c ^ d
                snake_case								= (3 * i + 5) % 16
            else:
                snake_case								= c ^ (b | not_aa(A__		))
                snake_case								= (7 * i) % 16
            snake_case								= (f + a + added_consts[i] + block_words[g]) % 2**32
            snake_case								= d
            snake_case								= c
            snake_case								= b
            snake_case								= sum_aa(A__			,		left_rotate_aa(A__			,		shift_amounts[i]		)		)

        # Add hashed chunk to running total
        snake_case								= sum_aa(A__			,		A__		)
        snake_case								= sum_aa(A__			,		A__		)
        snake_case								= sum_aa(A__			,		A__		)
        snake_case								= sum_aa(A__			,		A__		)

    snake_case								= reformat_hex(A__		) + reformat_hex(A__		) + reformat_hex(A__		) + reformat_hex(A__		)
    return digest


if __name__ == "__main__":
   import doctest

   doctest.testmod()



from . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
    bert,
    bert_generation,
    bert_japanese,
    bertweet,
    big_bird,
    bigbird_pegasus,
    biogpt,
    bit,
    blenderbot,
    blenderbot_small,
    blip,
    blip_a,
    bloom,
    bridgetower,
    byta,
    camembert,
    canine,
    chinese_clip,
    clap,
    clip,
    clipseg,
    codegen,
    conditional_detr,
    convbert,
    convnext,
    convnextva,
    cpm,
    cpmant,
    ctrl,
    cvt,
    dataavec,
    deberta,
    deberta_va,
    decision_transformer,
    deformable_detr,
    deit,
    deprecated,
    deta,
    detr,
    dialogpt,
    dinat,
    distilbert,
    dit,
    donut,
    dpr,
    dpt,
    efficientformer,
    efficientnet,
    electra,
    encodec,
    encoder_decoder,
    ernie,
    ernie_m,
    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,
    marian,
    markuplm,
    maskaformer,
    maskformer,
    mbart,
    mbartaa,
    mega,
    megatron_bert,
    megatron_gpta,
    mgp_str,
    mluke,
    mobilebert,
    mobilenet_va,
    mobilenet_va,
    mobilevit,
    mobilevitva,
    mpnet,
    mra,
    mta,
    musicgen,
    mvp,
    nat,
    nezha,
    nllb,
    nllb_moe,
    nystromformer,
    oneformer,
    open_llama,
    openai,
    opt,
    owlvit,
    pegasus,
    pegasus_x,
    perceiver,
    phobert,
    pixastruct,
    plbart,
    poolformer,
    prophetnet,
    qdqbert,
    rag,
    realm,
    reformer,
    regnet,
    rembert,
    resnet,
    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
    sew_d,
    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
    swinasr,
    swinva,
    switch_transformers,
    ta,
    table_transformer,
    tapas,
    time_series_transformer,
    timesformer,
    timm_backbone,
    transfo_xl,
    trocr,
    tvlt,
    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
    vilt,
    vision_encoder_decoder,
    vision_text_dual_encoder,
    visual_bert,
    vit,
    vit_hybrid,
    vit_mae,
    vit_msn,
    vivit,
    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,
)

