diffusers/pr_13182/en/_app/immutable/nodes/67.76331f11.js

import{s as ne,n as ae,o as re}from"../chunks/scheduler.53228c21.js";import{S as se,i as ie,e as d,s as a,c as b,h as de,a as c,d as t,b as r,f as W,g as x,j as A,k as G,l as M,m as n,n as w,t as L,o as $,p as y}from"../chunks/index.100fac89.js";import{C as ce}from"../chunks/CopyLLMTxtMenu.5dcd659f.js";import{D as oe}from"../chunks/Docstring.8867d421.js";import{C as le}from"../chunks/CodeBlock.d30a6509.js";import{H as te,E as me}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.3fe6de9f.js";function fe(S){let i,N,k,q,m,E,f,R,u,Q='A Diffusion Transformer model for 3D data from <a href="https://huggingface.co/Lightricks/LTX-2" rel="nofollow">LTX</a> was introduced by Lightricks.',I,_,B="The model can be loaded with the following code snippet.",C,p,P,h,J,s,g,Y,V,K='A Transformer model for video-like data used in <a href="https://huggingface.co/Lightricks/LTX-Video" rel="nofollow">LTX</a>.',O,l,T,F,X,ee="Forward pass for LTX-2.0 audiovisual video transformer.",U,v,Z,z,j;return m=new ce({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),f=new te({props:{title:"LTX2VideoTransformer3DModel",local:"ltx2videotransformer3dmodel",headingTag:"h1"}}),p=new le({props:{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMExUWDJWaWRlb1RyYW5zZm9ybWVyM0RNb2RlbCUwQSUwQXRyYW5zZm9ybWVyJTIwJTNEJTIwTFRYMlZpZGVvVHJhbnNmb3JtZXIzRE1vZGVsLmZyb21fcHJldHJhaW5lZCglMjJMaWdodHJpY2tzJTJGTFRYLTIlMjIlMkMlMjBzdWJmb2xkZXIlM0QlMjJ0cmFuc2Zvcm1lciUyMiUyQyUyMHRvcmNoX2R0eXBlJTNEdG9yY2guYmZsb2F0MTYpLnRvKCUyMmN1ZGElMjIp",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> LTX2VideoTransformer3DModel

transformer = LTX2VideoTransformer3DModel.from_pretrained(<span class="hljs-string">&quot;Lightricks/LTX-2&quot;</span>, subfolder=<span class="hljs-string">&quot;transformer&quot;</span>, torch_dtype=torch.bfloat16).to(<span class="hljs-string">&quot;cuda&quot;</span>)`,wrap:!1}}),h=new te({props:{title:"LTX2VideoTransformer3DModel",local:"diffusers.LTX2VideoTransformer3DModel",headingTag:"h2"}}),g=new oe({props:{name:"class diffusers.LTX2VideoTransformer3DModel",anchor:"diffusers.LTX2VideoTransformer3DModel",parameters:[{name:"in_channels",val:": int = 128"},{name:"out_channels",val:": int | None = 128"},{name:"patch_size",val:": int = 1"},{name:"patch_size_t",val:": int = 1"},{name:"num_attention_heads",val:": int = 32"},{name:"attention_head_dim",val:": int = 128"},{name:"cross_attention_dim",val:": int = 4096"},{name:"vae_scale_factors",val:": tuple = (8, 32, 32)"},{name:"pos_embed_max_pos",val:": int = 20"},{name:"base_height",val:": int = 2048"},{name:"base_width",val:": int = 2048"},{name:"audio_in_channels",val:": int = 128"},{name:"audio_out_channels",val:": int | None = 128"},{name:"audio_patch_size",val:": int = 1"},{name:"audio_patch_size_t",val:": int = 1"},{name:"audio_num_attention_heads",val:": int = 32"},{name:"audio_attention_head_dim",val:": int = 64"},{name:"audio_cross_attention_dim",val:": int = 2048"},{name:"audio_scale_factor",val:": int = 4"},{name:"audio_pos_embed_max_pos",val:": int = 20"},{name:"audio_sampling_rate",val:": int = 16000"},{name:"audio_hop_length",val:": int = 160"},{name:"num_layers",val:": int = 48"},{name:"activation_fn",val:": str = 'gelu-approximate'"},{name:"qk_norm",val:": str = 'rms_norm_across_heads'"},{name:"norm_elementwise_affine",val:": bool = False"},{name:"norm_eps",val:": float = 1e-06"},{name:"caption_channels",val:": int = 3840"},{name:"attention_bias",val:": bool = True"},{name:"attention_out_bias",val:": bool = True"},{name:"rope_theta",val:": float = 10000.0"},{name:"rope_double_precision",val:": bool = True"},{name:"causal_offset",val:": int = 1"},{name:"timestep_scale_multiplier",val:": int = 1000"},{name:"cross_attn_timestep_scale_multiplier",val:": int = 1000"},{name:"rope_type",val:": str = 'interleaved'"}],parametersDescription:[{anchor:"diffusers.LTX2VideoTransformer3DModel.in_channels",description:`<strong>in_channels</strong> (<code>int</code>, defaults to <code>128</code>) &#x2014;
The number of channels in the input.`,name:"in_channels"},{anchor:"diffusers.LTX2VideoTransformer3DModel.out_channels",description:`<strong>out_channels</strong> (<code>int</code>, defaults to <code>128</code>) &#x2014;
The number of channels in the output.`,name:"out_channels"},{anchor:"diffusers.LTX2VideoTransformer3DModel.patch_size",description:`<strong>patch_size</strong> (<code>int</code>, defaults to <code>1</code>) &#x2014;
The size of the spatial patches to use in the patch embedding layer.`,name:"patch_size"},{anchor:"diffusers.LTX2VideoTransformer3DModel.patch_size_t",description:`<strong>patch_size_t</strong> (<code>int</code>, defaults to <code>1</code>) &#x2014;
The size of the tmeporal patches to use in the patch embedding layer.`,name:"patch_size_t"},{anchor:"diffusers.LTX2VideoTransformer3DModel.num_attention_heads",description:`<strong>num_attention_heads</strong> (<code>int</code>, defaults to <code>32</code>) &#x2014;
The number of heads to use for multi-head attention.`,name:"num_attention_heads"},{anchor:"diffusers.LTX2VideoTransformer3DModel.attention_head_dim",description:`<strong>attention_head_dim</strong> (<code>int</code>, defaults to <code>64</code>) &#x2014;
The number of channels in each head.`,name:"attention_head_dim"},{anchor:"diffusers.LTX2VideoTransformer3DModel.cross_attention_dim",description:`<strong>cross_attention_dim</strong> (<code>int</code>, defaults to <code>2048 </code>) &#x2014;
The number of channels for cross attention heads.`,name:"cross_attention_dim"},{anchor:"diffusers.LTX2VideoTransformer3DModel.num_layers",description:`<strong>num_layers</strong> (<code>int</code>, defaults to <code>28</code>) &#x2014;
The number of layers of Transformer blocks to use.`,name:"num_layers"},{anchor:"diffusers.LTX2VideoTransformer3DModel.activation_fn",description:`<strong>activation_fn</strong> (<code>str</code>, defaults to <code>&quot;gelu-approximate&quot;</code>) &#x2014;
Activation function to use in feed-forward.`,name:"activation_fn"},{anchor:"diffusers.LTX2VideoTransformer3DModel.qk_norm",description:`<strong>qk_norm</strong> (<code>str</code>, defaults to <code>&quot;rms_norm_across_heads&quot;</code>) &#x2014;
The normalization layer to use.`,name:"qk_norm"}],source:"https://github.com/huggingface/diffusers/blob/vr_13182/src/diffusers/models/transformers/transformer_ltx2.py#L862"}}),T=new oe({props:{name:"forward",anchor:"diffusers.LTX2VideoTransformer3DModel.forward",parameters:[{name:"hidden_states",val:": Tensor"},{name:"audio_hidden_states",val:": Tensor"},{name:"encoder_hidden_states",val:": Tensor"},{name:"audio_encoder_hidden_states",val:": Tensor"},{name:"timestep",val:": LongTensor"},{name:"audio_timestep",val:": torch.LongTensor | None = None"},{name:"encoder_attention_mask",val:": torch.Tensor | None = None"},{name:"audio_encoder_attention_mask",val:": torch.Tensor | None = None"},{name:"num_frames",val:": int | None = None"},{name:"height",val:": int | None = None"},{name:"width",val:": int | None = None"},{name:"fps",val:": float = 24.0"},{name:"audio_num_frames",val:": int | None = None"},{name:"video_coords",val:": torch.Tensor | None = None"},{name:"audio_coords",val:": torch.Tensor | None = None"},{name:"attention_kwargs",val:": dict[str, typing.Any] | None = None"},{name:"return_dict",val:": bool = True"}],parametersDescription:[{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.hidden_states",description:`<strong>hidden_states</strong> (<code>torch.Tensor</code>) &#x2014;
Input patchified video latents of shape <code>(batch_size, num_video_tokens, in_channels)</code>.`,name:"hidden_states"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.audio_hidden_states",description:`<strong>audio_hidden_states</strong> (<code>torch.Tensor</code>) &#x2014;
Input patchified audio latents of shape <code>(batch_size, num_audio_tokens, audio_in_channels)</code>.`,name:"audio_hidden_states"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.encoder_hidden_states",description:`<strong>encoder_hidden_states</strong> (<code>torch.Tensor</code>) &#x2014;
Input video text embeddings of shape <code>(batch_size, text_seq_len, self.config.caption_channels)</code>.`,name:"encoder_hidden_states"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.audio_encoder_hidden_states",description:`<strong>audio_encoder_hidden_states</strong> (<code>torch.Tensor</code>) &#x2014;
Input audio text embeddings of shape <code>(batch_size, text_seq_len, self.config.caption_channels)</code>.`,name:"audio_encoder_hidden_states"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.timestep",description:`<strong>timestep</strong> (<code>torch.Tensor</code>) &#x2014;
Input timestep of shape <code>(batch_size, num_video_tokens)</code>. These should already be scaled by
<code>self.config.timestep_scale_multiplier</code>.`,name:"timestep"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.audio_timestep",description:`<strong>audio_timestep</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Input timestep of shape <code>(batch_size,)</code> or <code>(batch_size, num_audio_tokens)</code> for audio modulation
params. This is only used by certain pipelines such as the I2V pipeline.`,name:"audio_timestep"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.encoder_attention_mask",description:`<strong>encoder_attention_mask</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Optional multiplicative text attention mask of shape <code>(batch_size, text_seq_len)</code>.`,name:"encoder_attention_mask"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.audio_encoder_attention_mask",description:`<strong>audio_encoder_attention_mask</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
Optional multiplicative text attention mask of shape <code>(batch_size, text_seq_len)</code> for audio modeling.`,name:"audio_encoder_attention_mask"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.num_frames",description:`<strong>num_frames</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The number of latent video frames. Used if calculating the video coordinates for RoPE.`,name:"num_frames"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.height",description:`<strong>height</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The latent video height. Used if calculating the video coordinates for RoPE.`,name:"height"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.width",description:`<strong>width</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The latent video width. Used if calculating the video coordinates for RoPE.`,name:"width"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.fps",description:`<strong>fps</strong> &#x2014; (<code>float</code>, <em>optional</em>, defaults to <code>24.0</code>):
The desired frames per second of the generated video. Used if calculating the video coordinates for
RoPE.`,name:"fps"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.audio_num_frames",description:`<strong>audio_num_frames</strong> &#x2014; (<code>int</code>, <em>optional</em>):
The number of latent audio frames. Used if calculating the audio coordinates for RoPE.`,name:"audio_num_frames"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.video_coords",description:`<strong>video_coords</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
The video coordinates to be used when calculating the rotary positional embeddings (RoPE) of shape
<code>(batch_size, 3, num_video_tokens, 2)</code>. If not supplied, this will be calculated inside <code>forward</code>.`,name:"video_coords"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.audio_coords",description:`<strong>audio_coords</strong> (<code>torch.Tensor</code>, <em>optional</em>) &#x2014;
The audio coordinates to be used when calculating the rotary positional embeddings (RoPE) of shape
<code>(batch_size, 1, num_audio_tokens, 2)</code>. If not supplied, this will be calculated inside <code>forward</code>.`,name:"audio_coords"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.attention_kwargs",description:`<strong>attention_kwargs</strong> (<code>dict[str, Any]</code>, <em>optional</em>) &#x2014;
Optional dict of keyword args to be passed to the attention processor.`,name:"attention_kwargs"},{anchor:"diffusers.LTX2VideoTransformer3DModel.forward.return_dict",description:`<strong>return_dict</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) &#x2014;
Whether to return a dict-like structured output of type <code>AudioVisualModelOutput</code> or a tuple.`,name:"return_dict"}],source:"https://github.com/huggingface/diffusers/blob/vr_13182/src/diffusers/models/transformers/transformer_ltx2.py#L1095",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>If <code>return_dict</code> is <code>True</code>, returns a structured output of type <code>AudioVisualModelOutput</code>, otherwise a
<code>tuple</code> is returned where the first element is the denoised video latent patch sequence and the second
element is the denoised audio latent patch sequence.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>AudioVisualModelOutput</code> or <code>tuple</code></p>
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