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<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Echo&quot;,&quot;local&quot;:&quot;echo&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Inferencia&quot;,&quot;local&quot;:&quot;inference&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2},{&quot;title&quot;:&quot;EchoModularPipeline&quot;,&quot;local&quot;:&quot;diffusers.EchoModularPipeline&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2},{&quot;title&quot;:&quot;EchoBlocks&quot;,&quot;local&quot;:&quot;diffusers.EchoBlocks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}"/>
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		<!--rbrdnd--><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Echo&quot;,&quot;local&quot;:&quot;echo&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Inference&quot;,&quot;local&quot;:&quot;inference&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2},{&quot;title&quot;:&quot;EchoModularPipeline&quot;,&quot;local&quot;:&quot;diffusers.EchoModularPipeline&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2},{&quot;title&quot;:&quot;EchoBlocks&quot;,&quot;local&quot;:&quot;diffusers.EchoBlocks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}"/><!---->
		<link href="/docs/diffusers/v0.43.0/en/_app/immutable/assets/0.tn0RQdqM.css" rel="modulepreload"> <!--[--><!--[0--><!--[--><!--[0--><!--[--><p></p> <!--[0--><h1 class="relative group"><a id="echo" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#echo"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Echo<!----></span></h1><!--]--><!----> <p><a href="https://github.com/jd-opensource/JoyAI-Echo" rel="nofollow">Echo</a> es un modelo de generación de video de larga duración. Admite un primer frame limpio opcional, ranuras de memoria de imagen/áudio ordenadas y un muestreador estocástico de pocos pasos de Destilación de Coincidencia de Distribuciones (DMD).
La pipeline genera video y audio sincronizados.</p> <p>Echo se implementa como un <a href="/docs/diffusers/v0.43.0/es/api/modular_diffusers/pipeline#diffusers.ModularPipeline">ModularPipeline</a>, por lo que sus bloques de codificación de texto, condicionamiento de memoria, desruido estocástico DMD y decodificación pueden ejecutarse como un flujo de trabajo completo o componerse de forma independiente.</p> <!--[1--><h2 class="relative group"><a id="inference" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#inference"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->Inferencia<!----></span></h2><!--]--><!----> <p>Cargue directamente el checkpoint oficial <a href="https://huggingface.co/jdopensource/JoyAI-Echo" rel="nofollow">jdopensource/JoyAI-Echo</a>.
Utiliza el codificador de texto y el tokenizador de <a href="https://huggingface.co/google/gemma-3-12b-it" rel="nofollow">google/gemma-3-12b-it</a>.
El repositorio de Gemma está restringido, por lo que debe aceptar su licencia y autenticarse con Hugging Face antes de cargar el pipeline.</p> <p>El modelo publicado utiliza 241 fotogramas en su ejemplo de video largo. Las coordenadas de RoPE del video se mantienen en la tasa de entrenamiento de 24 fps, independientemente de la tasa del contenedor de salida.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600  " title="code excerpt" type="button"><svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg><!----> <div class=" absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0 "><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent;"></div> Copiado</div><!----></button><!----></div> <pre class="language-py "><!----><span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">import</span> torchaudio
<span class="hljs-keyword">from</span> PIL <span class="hljs-keyword">import</span> Image

<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> ComponentsManager, ModularPipeline
<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> encode_video

manager = ComponentsManager()
pipe = ModularPipeline.from_pretrained(<span class="hljs-string">&quot;jdopensource/JoyAI-Echo&quot;</span>, components_manager=manager)
pipe.load_components(dtype={<span class="hljs-string">&quot;default&quot;</span>: torch.bfloat16, <span class="hljs-string">&quot;audio_vae&quot;</span>: torch.float32})
manager.enable_auto_cpu_offload(device=<span class="hljs-string">&quot;cuda&quot;</span>)
pipe.vae.enable_tiling()

first_frame = Image.<span class="hljs-built_in">open</span>(<span class="hljs-string">&quot;first_frame.png&quot;</span>).convert(<span class="hljs-string">&quot;RGB&quot;</span>)
memory_images = [Image.<span class="hljs-built_in">open</span>(path).convert(<span class="hljs-string">&quot;RGB&quot;</span>) <span class="hljs-keyword">for</span> path <span class="hljs-keyword">in</span> [<span class="hljs-string">&quot;memory_0.png&quot;</span>, <span class="hljs-string">&quot;memory_1.png&quot;</span>]]
memory_audio_with_rates = [torchaudio.load(path) <span class="hljs-keyword">for</span> path <span class="hljs-keyword">in</span> [<span class="hljs-string">&quot;memory_0.wav&quot;</span>, <span class="hljs-string">&quot;memory_1.wav&quot;</span>]]
memory_audio = [waveform <span class="hljs-keyword">for</span> waveform, _ <span class="hljs-keyword">in</span> memory_audio_with_rates]
memory_audio_rates = [sample_rate <span class="hljs-keyword">for</span> _, sample_rate <span class="hljs-keyword">in</span> memory_audio_with_rates]

output = pipe(
    prompt=<span class="hljs-string">&quot;A cinematic dialogue scene in a quiet cafe.&quot;</span>,
    image=first_frame,
    memory_images=memory_images,
    memory_audio_waveforms=memory_audio,
    memory_audio_sample_rates=memory_audio_rates,
    width=<span class="hljs-number">1280</span>,
    height=<span class="hljs-number">736</span>,
    num_frames=<span class="hljs-number">241</span>,
    frame_rate=<span class="hljs-number">25.0</span>,
    model_frame_rate=<span class="hljs-number">24.0</span>,
    generator=torch.Generator(device=<span class="hljs-string">&quot;cuda&quot;</span>).manual_seed(<span class="hljs-number">42</span>),
    output_type=<span class="hljs-string">&quot;np&quot;</span>,
    output=[<span class="hljs-string">&quot;videos&quot;</span>, <span class="hljs-string">&quot;audio&quot;</span>],
)

encode_video(
    output[<span class="hljs-string">&quot;videos&quot;</span>][<span class="hljs-number">0</span>],
    fps=<span class="hljs-number">25</span>,
    audio=output[<span class="hljs-string">&quot;audio&quot;</span>][<span class="hljs-number">0</span>].<span class="hljs-built_in">float</span>().cpu(),
    audio_sample_rate=pipe.vocoder.config.output_sampling_rate,
    output_path=<span class="hljs-string">&quot;echo.mp4&quot;</span>,
)<!----></pre></div><!----> <p>El programa de sigma DMD predeterminado es el programa de ocho pasos publicado. Predice <code>x0</code> en cada paso y vuelve a añadir ruido con ruido gaussiano nuevo en el siguiente sigma, por lo que un <code>torch.Generator</code> con semilla controla tanto el ruido inicial como todo el ruido intermedio.</p> <p>La codificación de audio en memoria cruda requiere <code>torchaudio</code>. Para mantener la paridad de referencia, mantenga <code>audio_vae</code> en FP32, como se muestra arriba.
Los flujos de trabajo modulares pueden almacenar en caché los tensores normalizados y desempaquetados del codificador VAE. Los latentes de video tienen forma <code>(batch, channels, frames, height, width)</code> y los latentes de audio tienen forma <code>(batch, channels, time, mel_bins)</code>.
El bloque principal <code>denoise</code> empaqueta esos tensores, expande las condiciones para <code>num_videos_per_prompt</code> y desempaqueta
las salidas desruidadas de vuelta a la misma forma VAE. Pase también los <code>latents</code> y <code>audio_latents</code> iniciales en esa forma desempaquetada.
Los decodificadores toman tensores VAE normalizados y los desnormalizan inmediatamente antes de
decodificar. <code>output=["latents", "audio_latents"]</code> devuelve tensores VAE normalizados. Con <code>output_type="latent"</code> y <code>output=["videos", "audio"]</code>, obtiene los tensores VAE desnormalizados sin decodificar.</p> <!--[1--><h2 class="relative group"><a id="diffusers.EchoModularPipeline" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#diffusers.EchoModularPipeline"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->EchoModularPipeline<!----></span></h2><!--]--><!----> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><div><span class="group flex space-x-1.5 items-center text-gray-800 bg-gradient-to-r rounded-tr-lg -mt-4 -ml-4 pt-3 px-2.5" id="diffusers.EchoModularPipeline"><!----><h3 class="!m-0"><span class="flex-1 break-all md:text-lg bg-gradient-to-r px-2.5 py-1.5 rounded-xl from-indigo-50/70 to-white dark:from-gray-900 dark:to-gray-950 dark:text-indigo-300 text-indigo-700"><svg class="mr-1.5 text-indigo-500 inline-block -mt-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width=".8em" height=".8em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z" opacity=".25" fill="currentColor"></path><path class="uim-tertiary" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z" opacity=".5" fill="currentColor"></path><path class="uim-primary" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z" fill="currentColor"></path></svg><span class="font-light">clase</span> <span class="font-medium">diffusers.</span><span class="font-semibold">EchoModularPipeline</span></span></h3><!----> <a id="diffusers.EchoModularPipeline" class="header-link invisible with-hover:group-hover:visible pr-2" href="#diffusers.EchoModularPipeline"><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></a> <!--[0--><a class="!ml-auto !text-gray-400 !no-underline text-sm flex items-center" href="https://github.com/huggingface/diffusers/blob/v0.43.0/src/diffusers/modular_pipelines/echo/modular_pipeline.py#L27" target="_blank"><span>&lt;</span> <span class="hidden md:block mx-0.5 hover:!underline">source</span> <span>></span></a><!--]--></span> <!--[0--><p class="font-mono text-xs md:text-sm !leading-relaxed !my-6"><span>(</span> <!--[--><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">blocks<span class="opacity-60">: diffusers.modular_pipelines.modular_pipeline.ModularPipelineBlocks | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">pretrained_model_name_or_path<span class="opacity-60">: str | os.PathLike | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">components_manager<span class="opacity-60">: diffusers.modular_pipelines.components_manager.ComponentsManager | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">collection<span class="opacity-60">: str | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">workflow<span class="opacity-60">: str | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">modular_config_dict<span class="opacity-60">: dict[str, typing.Any] | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">config_dict<span class="opacity-60">: dict[str, typing.Any] | None = None</span></span></span><span class="comma cursor-default"><span class="rounded hover:bg-black hover:text-white dark:hover:bg-white dark:hover:text-black">**kwargs<span class="opacity-60"></span></span></span><!--]--> <span>)</span> <!--[-1--><!--]--></p><!--]--> <div class="!mb-10 relative docstring-details "><!--[-1--><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--></div></div><!----> <p>Un ModularPipeline para el punto de control DMD de video largo de Echo.</p></div> <!--[1--><h2 class="relative group"><a id="diffusers.EchoBlocks" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#diffusers.EchoBlocks"><span><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></span></a> <span><!---->EchoBlocks<!----></span></h2><!--]--><!----> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><div><span class="group flex space-x-1.5 items-center text-gray-800 bg-gradient-to-r rounded-tr-lg -mt-4 -ml-4 pt-3 px-2.5" id="diffusers.EchoBlocks"><!----><h3 class="!m-0"><span class="flex-1 break-all md:text-lg bg-gradient-to-r px-2.5 py-1.5 rounded-xl from-indigo-50/70 to-white dark:from-gray-900 dark:to-gray-950 dark:text-indigo-300 text-indigo-700"><svg class="mr-1.5 text-indigo-500 inline-block -mt-0.5" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width=".8em" height=".8em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path class="uim-quaternary" d="M20.23 7.24L12 12L3.77 7.24a1.98 1.98 0 0 1 .7-.71L11 2.76c.62-.35 1.38-.35 2 0l6.53 3.77c.29.173.531.418.7.71z" opacity=".25" fill="currentColor"></path><path class="uim-tertiary" d="M12 12v9.5a2.09 2.09 0 0 1-.91-.21L4.5 17.48a2.003 2.003 0 0 1-1-1.73v-7.5a2.06 2.06 0 0 1 .27-1.01L12 12z" opacity=".5" fill="currentColor"></path><path class="uim-primary" d="M20.5 8.25v7.5a2.003 2.003 0 0 1-1 1.73l-6.62 3.82c-.275.13-.576.198-.88.2V12l8.23-4.76c.175.308.268.656.27 1.01z" fill="currentColor"></path></svg><span class="font-light">clase</span> <span class="font-medium">diffusers.</span><span class="font-semibold">EchoBlocks</span></span></h3><!----> <a id="diffusers.EchoBlocks" class="header-link invisible with-hover:group-hover:visible pr-2" href="#diffusers.EchoBlocks"><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg><!----></a> <!--[0--><a class="!ml-auto !text-gray-400 !no-underline text-sm flex items-center" href="https://github.com/huggingface/diffusers/blob/v0.43.0/src/diffusers/modular_pipelines/echo/modular_blocks_echo.py#L220" target="_blank"><span>&lt;</span> <span class="hidden md:block mx-0.5 hover:!underline">source</span> <span>></span></a><!--]--></span> <!--[0--><p class="font-mono text-xs md:text-sm !leading-relaxed !my-6"><span>(</span> <!--[--><!--]--> <span>)</span> <!--[-1--><!--]--></p><!--]--> <div class="!mb-10 relative docstring-details "><!--[-1--><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--></div></div><!----> <p>Generación de video a partir de referencia con Echo, condicionamiento limpio del primer fotograma, ranuras de memoria de imagen/áudio ordenadas y
denoising estocástico DMD.</p> <p>Componentes:
text_encoder (<code>PreTrainedModel</code>) tokenizer (<code>PreTrainedTokenizerBase</code>) connectors (<code>LTX2TextConnectors</code>) vae
(<code>AutoencoderKLLTX2Video</code>) audio_vae (<code>AutoencoderKLLTX2Audio</code>) transformer (<code>LTX2VideoTransformer3DModel</code>)
video_processor (<code>VideoProcessor</code>) vocoder (<code>LTX2Vocoder</code>)</p> <p>Entradas:
prompt (<code>str</code>):
El prompt o prompts para guiar la generación de imágenes.
max_sequence_length (<code>int</code>, <em>opcional</em>, valor predeterminado 1024):
Longitud máxima de secuencia para la codificación del prompt.
image (<code>Image | Tensor</code>, <em>opcional</em>):
Opcional primer fotograma utilizado como condición de referencia limpia.
memory_images (<code>list</code>, <em>opcional</em>):
Imágenes de referencia ordenadas, una por cada ranura de memoria de Echo.
memory_audio_waveforms (<code>list</code>, <em>opcional</em>):
Formas de onda de memoria ordenadas como tensores <code>(channels, samples)</code>. Las entradas más largas de 9,62 segundos se recortan a
su ventana de mayor respuesta. Use <code>None</code> para una ranura silenciosa.
memory_audio_sample_rates (<code>int | list</code>, <em>opcional</em>):
Tasa de muestreo compartida por todas las formas de onda de memoria, o una tasa por ranura.
height (<code>int</code>, <em>opcional</em>, valor predeterminado 512):
La altura en píxeles de la imagen generada.
width (<code>int</code>, <em>opcional</em>, valor predeterminado 704):
El ancho en píxeles de la imagen generada.
model_frame_rate (<code>float</code>, <em>opcional</em>, valor predeterminado 24.0):
Tasa de fotogramas en tiempo de entrenamiento utilizada para las coordenadas RoPE de video de Echo.
memory_position_offset (<code>float</code>, <em>opcional</em>, valor predeterminado 500.0):
Centro temporal asignado a la primera ranura de memoria.
memory_position_slot_stride (<code>float</code>, <em>opcional</em>, valor predeterminado 50.0):
Distancia temporal entre los centros de ranuras de memoria consecutivas.
num_videos_per_prompt (<code>int</code>, <em>opcional</em>, valor predeterminado 1):
Número de videos por prompt.
num_frames (<code>int</code>, <em>opcional</em>, valor predeterminado 241):
Número de fotogramas de píxeles generados; debe ser <code>1 + k * vae_temporal_compression_ratio</code>.
frame_rate (<code>float</code>, <em>opcional</em>, valor predeterminado 25.0):
Tasa de fotogramas del video generado.
latents (<code>Tensor</code>, <em>opcional</em>):
Ruido de video inicial opcional en forma de VAE (B, C, F, H, W).
audio_latents (<code>Tensor</code>, <em>opcional</em>):
Ruido de audio inicial opcional en forma de VAE (B, C, L, M).
generator (<code>Generator</code>, <em>opcional</em>):
Generador de Torch para una generación determinista.
sigmas (<code>list | tuple</code>):
Programa de sigma de DMD, incluido el cero terminal.
attention_kwargs (<code>dict</code>, <em>opcional</em>):
Kwargs adicionales para los procesadores de atención.
output_type (<code>str</code>, <em>opcional</em>, valor predeterminado pil):
Formato de salida: ‘pil’, ‘np’, ‘pt’.
decode_timestep (<code>None</code>, <em>opcional</em>, valor predeterminado 0.0):
Paso temporal utilizado para decodificar los latentes finales.
decode_noise_scale (<code>None</code>, <em>opcional</em>):
Factor de interpolación de ruido aplicado en el paso temporal de decodificación.</p> <p>Salidas:
videos (<code>list</code>):
Los videos generados.
audio (<code>Tensor</code>):
La forma de onda de audio generada.</p></div> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/diffusers/blob/main/docs/source/en/api/pipelines/echo.md" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg><!----> <span><span class="underline">Update</span> on GitHub</span></a><!----> <p></p><!--]--><!----><!--]--><!--]--><!--]--> <!--[-1--><!--]--><!--]-->
			
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