



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,
)







from manim import *






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    def 			_lowerCAmelCase					(       self		):
        A :       Union[str, Any]          =   Rectangle(height=0.5,		width=0.5		)
        A :       Optional[int]          =   Rectangle(height=0.25,		width=0.25		)
        A :       Optional[Any]          =   Rectangle(height=0.46,		width=0.46		).set_stroke(width=0		)

        A :       List[str]          =   [mem.copy() for i in range(6		)]
        A :       Any          =   [mem.copy() for i in range(6		)]
        A :       int          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       Tuple          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       str          =   VGroup(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       List[Any]          =   Text("""CPU""",		font_size=24		)
        A :       Optional[int]          =   Group(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0.5,		aligned_edge=lowerCamelCase__		)
        cpu.move_to([-2.5, -0.5, 0]		)
        self.add(lowerCamelCase__		)

        A :       List[Any]          =   [mem.copy() for i in range(4		)]
        A :       Optional[Any]          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       Dict          =   Text("""GPU""",		font_size=24		)
        A :       Any          =   Group(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0.5,		aligned_edge=lowerCamelCase__		)
        gpu.move_to([-1, -1, 0]		)
        self.add(lowerCamelCase__		)

        A :       Optional[int]          =   [mem.copy() for i in range(6		)]
        A :       List[str]          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)

        A :       Optional[int]          =   Text("""Model""",		font_size=24		)
        A :       List[Any]          =   Group(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0.5,		aligned_edge=lowerCamelCase__		)
        model.move_to([3, -1.0, 0]		)
        self.add(lowerCamelCase__		)

        A :       Tuple          =   []
        A :       Tuple          =   []
        A :       Any          =   []

        for i, rect in enumerate(lowerCamelCase__		):
            rect.set_stroke(lowerCamelCase__		)

            A :       Any          =   Rectangle(height=0.46 / 4,		width=0.46 / 3		).set_stroke(width=0.0		).set_fill(lowerCamelCase__,		opacity=0.7		)

            if i == 0:
                cpu_target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT		),		buff=0.02,		direction=lowerCamelCase__		)
                cpu_target.set_x(cpu_target.get_x() + 0.1		)
            elif i == 3:
                cpu_target.next_to(model_cpu_arr[0],		direction=lowerCamelCase__,		buff=0.0		)
            else:
                cpu_target.next_to(model_cpu_arr[i - 1],		direction=lowerCamelCase__,		buff=0.0		)
            self.add(lowerCamelCase__		)
            model_cpu_arr.append(lowerCamelCase__		)

        self.add(*lowerCamelCase__,		*lowerCamelCase__,		*lowerCamelCase__		)

        A :       int          =   [mem.copy() for i in range(6		)]
        A :       List[Any]          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)

        A :       str          =   Text("""Loaded Checkpoint""",		font_size=24		)
        A :       List[str]          =   Group(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0.5,		aligned_edge=lowerCamelCase__		)
        checkpoint.move_to([3, 0.5, 0]		)

        self.add(lowerCamelCase__		)

        A :       Optional[int]          =   []
        A :       List[Any]          =   []

        for i, rect in enumerate(lowerCamelCase__		):
            A :       int          =   fill.copy().set_fill(lowerCamelCase__,		opacity=0.7		)
            target.move_to(lowerCamelCase__		)
            ckpt_arr.append(lowerCamelCase__		)

            A :       List[Any]          =   target.copy()
            if i < 5:
                cpu_target.move_to(cpu_left_col_base[i + 1]		)
            else:
                cpu_target.move_to(cpu_right_col_base[i - 5]		)
            ckpt_cpu_arr.append(lowerCamelCase__		)
        self.add(*lowerCamelCase__,		*lowerCamelCase__		)

        A :       str          =   Square(side_length=2.2		)
        key.move_to([-5, 2, 0]		)

        A :       List[Any]          =   MarkupText(
            f'''<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model''',		font_size=18,		)

        key_text.move_to([-5, 2.4, 0]		)

        self.add(lowerCamelCase__,		lowerCamelCase__		)

        A :       Union[str, Any]          =   MarkupText(
            f'''<span fgcolor=\'{BLUE}\'>●</span> Checkpoint''',		font_size=18,		)

        blue_text.next_to(lowerCamelCase__,		DOWN * 2.4,		aligned_edge=key_text.get_left()		)
        self.add(lowerCamelCase__		)

        A :       List[str]          =   MarkupText(
            f'''Based on the passed in configuration, weights are stored in\na variety of np.memmaps on disk or to a particular device.''',		font_size=24,		)
        step_a.move_to([2, 2, 0]		)

        A :       List[str]          =   [meta_mem.copy() for i in range(6		)]
        A :       List[Any]          =   [meta_mem.copy() for i in range(6		)]
        A :       List[Any]          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       List[str]          =   VGroup(*lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       Dict          =   VGroup(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0		)
        A :       Optional[Any]          =   Text("""Disk""",		font_size=24		)
        A :       List[str]          =   Group(lowerCamelCase__,		lowerCamelCase__		).arrange(lowerCamelCase__,		buff=0.5,		aligned_edge=lowerCamelCase__		)
        disk.move_to([-4.0, -1.25, 0]		)
        self.play(Write(lowerCamelCase__,		run_time=3		),		Write(lowerCamelCase__,		run_time=1		),		Create(lowerCamelCase__,		run_time=1		)		)

        A :       str          =   []
        for i, rect in enumerate(lowerCamelCase__		):
            A :       Optional[Any]          =   rect.copy()
            target.generate_target()
            target.target.move_to(disk_left_col_base[i]		).scale(0.5		)
            animations.append(MoveToTarget(lowerCamelCase__,		run_time=1.5		)		)
        self.play(*lowerCamelCase__		)

        self.play(FadeOut(lowerCamelCase__		)		)

        A :       List[str]          =   MarkupText(f'''Then, the checkpoint is removed from memory\nthrough garbage collection.''',		font_size=24		)
        step_a.move_to([2, 2, 0]		)

        self.play(Write(lowerCamelCase__,		run_time=3		)		)

        self.play(
            FadeOut(lowerCamelCase__,		lowerCamelCase__,		*lowerCamelCase__,		*lowerCamelCase__		),		)

        self.wait()


