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support ltx-2 training

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mi804
2026-02-25 17:19:57 +08:00
parent 288bbc7128
commit 586ac9d8a6
40 changed files with 893 additions and 49 deletions
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56
diffsynth/configs/model_configs.py
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@@ -607,6 +607,12 @@ ltx2_series = [
"model_class": "diffsynth.models.ltx2_dit.LTXModel",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_dit.LTXModelStateDictConverter",
},
{
"model_hash": "c567aaa37d5ed7454c73aa6024458661",
"model_name": "ltx2_dit",
"model_class": "diffsynth.models.ltx2_dit.LTXModel",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_dit.LTXModelStateDictConverter",
},
{
# Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
"model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -614,6 +620,12 @@ ltx2_series = [
"model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoEncoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoEncoderStateDictConverter",
},
{
"model_hash": "7f7e904a53260ec0351b05f32153754b",
"model_name": "ltx2_video_vae_encoder",
"model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoEncoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoEncoderStateDictConverter",
},
{
# Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
"model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -621,6 +633,12 @@ ltx2_series = [
"model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoDecoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoDecoderStateDictConverter",
},
{
"model_hash": "dc6029ca2825147872b45e35a2dc3a97",
"model_name": "ltx2_video_vae_decoder",
"model_class": "diffsynth.models.ltx2_video_vae.LTX2VideoDecoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_video_vae.LTX2VideoDecoderStateDictConverter",
},
{
# Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
"model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -628,6 +646,12 @@ ltx2_series = [
"model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioDecoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioDecoderStateDictConverter",
},
{
"model_hash": "7d7823dde8f1ea0b50fb07ac329dd4cb",
"model_name": "ltx2_audio_vae_decoder",
"model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioDecoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioDecoderStateDictConverter",
},
{
# Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
"model_hash": "aca7b0bbf8415e9c98360750268915fc",
@@ -635,16 +659,34 @@ ltx2_series = [
"model_class": "diffsynth.models.ltx2_audio_vae.LTX2Vocoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2VocoderStateDictConverter",
},
# { # not used currently
# # Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
# "model_hash": "aca7b0bbf8415e9c98360750268915fc",
# "model_name": "ltx2_audio_vae_encoder",
# "model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioEncoder",
# "state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioEncoderStateDictConverter",
# },
{
"model_hash": "f471360f6b24bef702ab73133d9f8bb9",
"model_name": "ltx2_audio_vocoder",
"model_class": "diffsynth.models.ltx2_audio_vae.LTX2Vocoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2VocoderStateDictConverter",
},
{
# Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
"model_hash": "aca7b0bbf8415e9c98360750268915fc",
"model_name": "ltx2_audio_vae_encoder",
"model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioEncoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioEncoderStateDictConverter",
},
{
"model_hash": "29338f3b95e7e312a3460a482e4f4554",
"model_name": "ltx2_audio_vae_encoder",
"model_class": "diffsynth.models.ltx2_audio_vae.LTX2AudioEncoder",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_audio_vae.LTX2AudioEncoderStateDictConverter",
},
{
# Example: ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors")
"model_hash": "aca7b0bbf8415e9c98360750268915fc",
"model_name": "ltx2_text_encoder_post_modules",
"model_class": "diffsynth.models.ltx2_text_encoder.LTX2TextEncoderPostModules",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_text_encoder.LTX2TextEncoderPostModulesStateDictConverter",
},
{
"model_hash": "981629689c8be92a712ab3c5eb4fc3f6",
"model_name": "ltx2_text_encoder_post_modules",
"model_class": "diffsynth.models.ltx2_text_encoder.LTX2TextEncoderPostModules",
"state_dict_converter": "diffsynth.utils.state_dict_converters.ltx2_text_encoder.LTX2TextEncoderPostModulesStateDictConverter",

30
diffsynth/diffusion/loss.py
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@@ -28,6 +28,36 @@ def FlowMatchSFTLoss(pipe: BasePipeline, **inputs):
return loss
def FlowMatchSFTAudioVideoLoss(pipe: BasePipeline, **inputs):
max_timestep_boundary = int(inputs.get("max_timestep_boundary", 1) * len(pipe.scheduler.timesteps))
min_timestep_boundary = int(inputs.get("min_timestep_boundary", 0) * len(pipe.scheduler.timesteps))
timestep_id = torch.randint(min_timestep_boundary, max_timestep_boundary, (1,))
timestep = pipe.scheduler.timesteps[timestep_id].to(dtype=pipe.torch_dtype, device=pipe.device)
# video
noise = torch.randn_like(inputs["input_latents"])
inputs["video_latents"] = pipe.scheduler.add_noise(inputs["input_latents"], noise, timestep)
training_target = pipe.scheduler.training_target(inputs["input_latents"], noise, timestep)
# audio
if inputs.get("audio_input_latents") is not None:
audio_noise = torch.randn_like(inputs["audio_input_latents"])
inputs["audio_latents"] = pipe.scheduler.add_noise(inputs["audio_input_latents"], audio_noise, timestep)
training_target_audio = pipe.scheduler.training_target(inputs["audio_input_latents"], audio_noise, timestep)
models = {name: getattr(pipe, name) for name in pipe.in_iteration_models}
noise_pred, noise_pred_audio = pipe.model_fn(**models, **inputs, timestep=timestep)
loss = torch.nn.functional.mse_loss(noise_pred.float(), training_target.float())
loss = loss * pipe.scheduler.training_weight(timestep)
if inputs.get("audio_input_latents") is not None:
loss_audio = torch.nn.functional.mse_loss(noise_pred_audio.float(), training_target_audio.float())
loss_audio = loss_audio * pipe.scheduler.training_weight(timestep)
loss = loss + loss_audio
return loss
def DirectDistillLoss(pipe: BasePipeline, **inputs):
pipe.scheduler.set_timesteps(inputs["num_inference_steps"])
pipe.scheduler.training = True

57
diffsynth/models/ltx2_audio_vae.py
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@@ -5,8 +5,65 @@ import einops
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchaudio
from .ltx2_common import VideoLatentShape, AudioLatentShape, Patchifier, NormType, build_normalization_layer
class AudioProcessor(nn.Module):
"""Converts audio waveforms to log-mel spectrograms with optional resampling."""
def __init__(
self,
sample_rate: int = 16000,
mel_bins: int = 64,
mel_hop_length: int = 160,
n_fft: int = 1024,
) -> None:
super().__init__()
self.sample_rate = sample_rate
self.mel_transform = torchaudio.transforms.MelSpectrogram(
sample_rate=sample_rate,
n_fft=n_fft,
win_length=n_fft,
hop_length=mel_hop_length,
f_min=0.0,
f_max=sample_rate / 2.0,
n_mels=mel_bins,
window_fn=torch.hann_window,
center=True,
pad_mode="reflect",
power=1.0,
mel_scale="slaney",
norm="slaney",
)
def resample_waveform(
self,
waveform: torch.Tensor,
source_rate: int,
target_rate: int,
) -> torch.Tensor:
"""Resample waveform to target sample rate if needed."""
if source_rate == target_rate:
return waveform
resampled = torchaudio.functional.resample(waveform, source_rate, target_rate)
return resampled.to(device=waveform.device, dtype=waveform.dtype)
def waveform_to_mel(
self,
waveform: torch.Tensor,
waveform_sample_rate: int,
) -> torch.Tensor:
"""Convert waveform to log-mel spectrogram [batch, channels, time, n_mels]."""
waveform = self.resample_waveform(waveform, waveform_sample_rate, self.sample_rate)
mel = self.mel_transform(waveform)
mel = torch.log(torch.clamp(mel, min=1e-5))
mel = mel.to(device=waveform.device, dtype=waveform.dtype)
return mel.permute(0, 1, 3, 2).contiguous()
class AudioPatchifier(Patchifier):
def __init__(
self,

2
diffsynth/models/ltx2_dit.py
View File

@@ -1446,6 +1446,6 @@ class LTXModel(torch.nn.Module):
cross_pe_max_pos = max(self.positional_embedding_max_pos[0], self.audio_positional_embedding_max_pos[0])
self._init_preprocessors(cross_pe_max_pos)
video = Modality(video_latents, video_timesteps, video_positions, video_context)
audio = Modality(audio_latents, audio_timesteps, audio_positions, audio_context)
audio = Modality(audio_latents, audio_timesteps, audio_positions, audio_context) if audio_latents is not None else None
vx, ax = self._forward(video=video, audio=audio, perturbations=None)
return vx, ax

65
diffsynth/pipelines/ltx2_audio_video.py
View File

@@ -18,7 +18,7 @@ from ..diffusion.base_pipeline import BasePipeline, PipelineUnit
from ..models.ltx2_text_encoder import LTX2TextEncoder, LTX2TextEncoderPostModules, LTXVGemmaTokenizer
from ..models.ltx2_dit import LTXModel
from ..models.ltx2_video_vae import LTX2VideoEncoder, LTX2VideoDecoder, VideoLatentPatchifier
from ..models.ltx2_audio_vae import LTX2AudioEncoder, LTX2AudioDecoder, LTX2Vocoder, AudioPatchifier
from ..models.ltx2_audio_vae import LTX2AudioEncoder, LTX2AudioDecoder, LTX2Vocoder, AudioPatchifier, AudioProcessor
from ..models.ltx2_upsampler import LTX2LatentUpsampler
from ..models.ltx2_common import VideoLatentShape, AudioLatentShape, VideoPixelShape, get_pixel_coords, VIDEO_SCALE_FACTORS
from ..utils.data.media_io_ltx2 import ltx2_preprocess
@@ -50,6 +50,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
self.video_patchifier: VideoLatentPatchifier = VideoLatentPatchifier(patch_size=1)
self.audio_patchifier: AudioPatchifier = AudioPatchifier(patch_size=1)
self.audio_processor: AudioProcessor = AudioProcessor()
self.in_iteration_models = ("dit",)
self.units = [
@@ -57,6 +58,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
LTX2AudioVideoUnit_ShapeChecker(),
LTX2AudioVideoUnit_PromptEmbedder(),
LTX2AudioVideoUnit_NoiseInitializer(),
LTX2AudioVideoUnit_InputAudioEmbedder(),
LTX2AudioVideoUnit_InputVideoEmbedder(),
LTX2AudioVideoUnit_InputImagesEmbedder(),
]
@@ -95,7 +97,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
stage2_lora_config.download_if_necessary()
pipe.stage2_lora_path = stage2_lora_config.path
# Optional, currently not used
# pipe.audio_vae_encoder = model_pool.fetch_model("ltx2_audio_vae_encoder")
pipe.audio_vae_encoder = model_pool.fetch_model("ltx2_audio_vae_encoder")
# VRAM Management
pipe.vram_management_enabled = pipe.check_vram_management_state()
@@ -157,7 +159,6 @@ class LTX2AudioVideoPipeline(BasePipeline):
num_frames=121,
# Classifier-free guidance
cfg_scale: Optional[float] = 3.0,
cfg_merge: Optional[bool] = False,
# Scheduler
num_inference_steps: Optional[int] = 40,
# VAE tiling
@@ -186,7 +187,7 @@ class LTX2AudioVideoPipeline(BasePipeline):
"input_images": input_images, "input_images_indexes": input_images_indexes, "input_images_strength": input_images_strength,
"seed": seed, "rand_device": rand_device,
"height": height, "width": width, "num_frames": num_frames,
"cfg_scale": cfg_scale, "cfg_merge": cfg_merge,
"cfg_scale": cfg_scale,
"tiled": tiled, "tile_size_in_pixels": tile_size_in_pixels, "tile_overlap_in_pixels": tile_overlap_in_pixels,
"tile_size_in_frames": tile_size_in_frames, "tile_overlap_in_frames": tile_overlap_in_frames,
"use_two_stage_pipeline": use_two_stage_pipeline, "use_distilled_pipeline": use_distilled_pipeline,
@@ -422,7 +423,7 @@ class LTX2AudioVideoUnit_NoiseInitializer(PipelineUnit):
def process_stage(self, pipe: LTX2AudioVideoPipeline, height, width, num_frames, seed, rand_device, frame_rate=24.0):
video_pixel_shape = VideoPixelShape(batch=1, frames=num_frames, width=width, height=height, fps=frame_rate)
video_latent_shape = VideoLatentShape.from_pixel_shape(shape=video_pixel_shape, latent_channels=pipe.video_vae_encoder.latent_channels)
video_latent_shape = VideoLatentShape.from_pixel_shape(shape=video_pixel_shape, latent_channels=128)
video_noise = pipe.generate_noise(video_latent_shape.to_torch_shape(), seed=seed, rand_device=rand_device)
latent_coords = pipe.video_patchifier.get_patch_grid_bounds(output_shape=video_latent_shape, device=pipe.device)
@@ -455,17 +456,48 @@ class LTX2AudioVideoUnit_NoiseInitializer(PipelineUnit):
class LTX2AudioVideoUnit_InputVideoEmbedder(PipelineUnit):
def __init__(self):
super().__init__(
input_params=("input_video", "video_noise", "audio_noise", "tiled", "tile_size", "tile_stride"),
output_params=("video_latents", "audio_latents"),
input_params=("input_video", "video_noise", "tiled", "tile_size_in_pixels", "tile_overlap_in_pixels"),
output_params=("video_latents", "input_latents"),
onload_model_names=("video_vae_encoder")
)
def process(self, pipe: LTX2AudioVideoPipeline, input_video, video_noise, audio_noise, tiled, tile_size, tile_stride):
def process(self, pipe: LTX2AudioVideoPipeline, input_video, video_noise, tiled, tile_size_in_pixels, tile_overlap_in_pixels):
if input_video is None:
return {"video_latents": video_noise, "audio_latents": audio_noise}
return {"video_latents": video_noise}
else:
# TODO: implement video-to-video
raise NotImplementedError("Video-to-video not implemented yet.")
pipe.load_models_to_device(self.onload_model_names)
input_video = pipe.preprocess_video(input_video)
input_latents = pipe.video_vae_encoder.encode(input_video, tiled, tile_size_in_pixels, tile_overlap_in_pixels).to(dtype=pipe.torch_dtype, device=pipe.device)
if pipe.scheduler.training:
return {"video_latents": input_latents, "input_latents": input_latents}
else:
# TODO: implement video-to-video
raise NotImplementedError("Video-to-video not implemented yet.")
class LTX2AudioVideoUnit_InputAudioEmbedder(PipelineUnit):
def __init__(self):
super().__init__(
input_params=("input_audio", "audio_noise"),
output_params=("audio_latents", "audio_input_latents", "audio_positions", "audio_latent_shape"),
onload_model_names=("audio_vae_encoder",)
)
def process(self, pipe: LTX2AudioVideoPipeline, input_audio, audio_noise):
if input_audio is None:
return {"audio_latents": audio_noise}
else:
input_audio, sample_rate = input_audio
pipe.load_models_to_device(self.onload_model_names)
input_audio = pipe.audio_processor.waveform_to_mel(input_audio.unsqueeze(0), waveform_sample_rate=sample_rate).to(dtype=pipe.torch_dtype)
audio_input_latents = pipe.audio_vae_encoder(input_audio)
audio_noise = torch.randn_like(audio_input_latents)
audio_latent_shape = AudioLatentShape.from_torch_shape(audio_input_latents.shape)
audio_positions = pipe.audio_patchifier.get_patch_grid_bounds(audio_latent_shape, device=pipe.device)
if pipe.scheduler.training:
return {"audio_latents": audio_input_latents, "audio_input_latents": audio_input_latents, "audio_positions": audio_positions, "audio_latent_shape": audio_latent_shape}
else:
# TODO: implement video-to-video
raise NotImplementedError("Video-to-video not implemented yet.")
class LTX2AudioVideoUnit_InputImagesEmbedder(PipelineUnit):
def __init__(self):
@@ -530,9 +562,12 @@ def model_fn_ltx2(
video_timesteps = timestep.repeat(1, video_latents.shape[1], 1)
if denoise_mask_video is not None:
video_timesteps = video_patchifier.patchify(denoise_mask_video) * video_timesteps
_, c_a, _, mel_bins = audio_latents.shape
audio_latents = audio_patchifier.patchify(audio_latents)
audio_timesteps = timestep.repeat(1, audio_latents.shape[1], 1)
if audio_latents is not None:
_, c_a, _, mel_bins = audio_latents.shape
audio_latents = audio_patchifier.patchify(audio_latents)
audio_timesteps = timestep.repeat(1, audio_latents.shape[1], 1)
else:
audio_timesteps = None
#TODO: support gradient checkpointing in training
vx, ax = dit(
video_latents=video_latents,
@@ -546,5 +581,5 @@ def model_fn_ltx2(
)
# unpatchify
vx = video_patchifier.unpatchify_video(vx, f, h, w)
ax = audio_patchifier.unpatchify_audio(ax, c_a, mel_bins)
ax = audio_patchifier.unpatchify_audio(ax, c_a, mel_bins) if ax is not None else None
return vx, ax

7
examples/ltx2/model_inference/LTX-2-I2AV-DistilledPipeline.py
View File

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

7
examples/ltx2/model_inference/LTX-2-I2AV-OneStage.py
View File

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
)

7
examples/ltx2/model_inference/LTX-2-I2AV-TwoStage.py
View File

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-In.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-Left.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-Out.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Dolly-Right.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Jib-Down.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Jib-Up.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-Camera-Control-Static.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference/LTX-2-T2AV-DistilledPipeline.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

15
examples/ltx2/model_inference/LTX-2-T2AV-OneStage.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
)
@@ -40,3 +44,12 @@ write_video_audio_ltx2(
fps=24,
audio_sample_rate=24000,
)
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_encoder.safetensors", **vram_config),
# ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),

6
examples/ltx2/model_inference/LTX-2-T2AV-TwoStage.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

7
examples/ltx2/model_inference_low_vram/LTX-2-I2AV-DistilledPipeline.py
View File

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

7
examples/ltx2/model_inference_low_vram/LTX-2-I2AV-OneStage.py
View File

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,

7
examples/ltx2/model_inference_low_vram/LTX-2-I2AV-TwoStage.py
View File

@@ -19,7 +19,12 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_encoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-In.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-Left.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-Out.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Dolly-Right.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Jib-Down.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Jib-Up.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-Camera-Control-Static.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-DistilledPipeline.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer_distilled.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-OneStage.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,

6
examples/ltx2/model_inference_low_vram/LTX-2-T2AV-TwoStage.py
View File

@@ -17,7 +17,11 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-19b-dev.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(model_id="Lightricks/LTX-2", origin_file_pattern="ltx-2-spatial-upscaler-x2-1.0.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),

35
examples/ltx2/model_training/full/LTX-2-T2AV-splited.sh Normal file
View File

@@ -0,0 +1,35 @@
# Splited Training
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path data/example_video_dataset/ltx2 \
--dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
--data_file_keys "video,input_audio" \
--extra_inputs "input_audio" \
--height 512 \
--width 768 \
--num_frames 49 \
--dataset_repeat 1 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV-full-splited-cache" \
--trainable_models "dit" \
--use_gradient_checkpointing \
--task "sft:data_process"
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path ./models/train/LTX2-T2AV-full-splited-cache \
--data_file_keys "video,input_audio" \
--extra_inputs "input_audio" \
--height 512 \
--width 768 \
--num_frames 49 \
--dataset_repeat 100 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV-full" \
--trainable_models "dit" \
--use_gradient_checkpointing \
--task "sft:train"

56
examples/ltx2/model_training/lora/LTX-2-T2AV-noaudio.sh Normal file
View File

@@ -0,0 +1,56 @@
# single stage training
# accelerate launch examples/ltx2/model_training/train.py \
# --dataset_base_path data/example_video_dataset/ltx2 \
# --dataset_metadata_path data/example_video_dataset/ltx2_t2v.csv \
# --height 256 \
# --width 384 \
# --num_frames 25\
# --dataset_repeat 100 \
# --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors,DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
# --learning_rate 1e-4 \
# --num_epochs 5 \
# --remove_prefix_in_ckpt "pipe.dit." \
# --output_path "./models/train/LTX2-T2AV-noaudio_lora" \
# --lora_base_model "dit" \
# --lora_target_modules "to_k,to_q,to_v,to_out.0" \
# --lora_rank 32 \
# --use_gradient_checkpointing \
# --find_unused_parameters
# Splited Training
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path data/example_video_dataset/ltx2 \
--dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
--height 256 \
--width 384 \
--num_frames 49\
--dataset_repeat 1 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV-noaudio_lora-splited-cache" \
--lora_base_model "dit" \
--lora_target_modules "to_k,to_q,to_v,to_out.0" \
--lora_rank 32 \
--use_gradient_checkpointing \
--task "sft:data_process"
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path ./models/train/LTX2-T2AV-noaudio_lora-splited-cache \
--height 256 \
--width 384 \
--num_frames 49\
--dataset_repeat 100 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV-noaudio_lora" \
--lora_base_model "dit" \
--lora_target_modules "to_k,to_q,to_v,to_out.0" \
--lora_rank 32 \
--use_gradient_checkpointing \
--task "sft:train"

40
examples/ltx2/model_training/lora/LTX-2-T2AV-splited.sh Normal file
View File

@@ -0,0 +1,40 @@
# Splited Training
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path data/example_video_dataset/ltx2 \
--dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
--data_file_keys "video,input_audio" \
--extra_inputs "input_audio" \
--height 512 \
--width 768 \
--num_frames 49 \
--dataset_repeat 1 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV_lora-splited-cache" \
--lora_base_model "dit" \
--lora_target_modules "to_k,to_q,to_v,to_out.0" \
--lora_rank 32 \
--use_gradient_checkpointing \
--task "sft:data_process"
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path ./models/train/LTX2-T2AV_lora-splited-cache \
--data_file_keys "video,input_audio" \
--extra_inputs "input_audio" \
--height 512 \
--width 768 \
--num_frames 49 \
--dataset_repeat 100 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV_lora" \
--lora_base_model "dit" \
--lora_target_modules "to_k,to_q,to_v,to_out.0" \
--lora_rank 32 \
--use_gradient_checkpointing \
--task "sft:train"

19
examples/ltx2/model_training/lora/LTX-2-T2AV.sh Normal file
View File

@@ -0,0 +1,19 @@
accelerate launch examples/ltx2/model_training/train.py \
--dataset_base_path data/example_video_dataset/ltx2 \
--dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
--data_file_keys "video,input_audio" \
--extra_inputs "input_audio" \
--height 256 \
--width 384 \
--num_frames 25\
--dataset_repeat 100 \
--model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors,DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/LTX2-T2AV_lora" \
--lora_base_model "dit" \
--lora_target_modules "to_k,to_q,to_v,to_out.0" \
--lora_rank 32 \
--use_gradient_checkpointing \
--find_unused_parameters

162
examples/ltx2/model_training/train.py Normal file
View File

@@ -0,0 +1,162 @@
import torch, os, argparse, accelerate, warnings
from diffsynth.core import UnifiedDataset
from diffsynth.core.data.operators import LoadAudioWithTorchaudio, ToAbsolutePath
from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
from diffsynth.diffusion import *
os.environ["TOKENIZERS_PARALLELISM"] = "false"
class LTX2TrainingModule(DiffusionTrainingModule):
def __init__(
self,
model_paths=None, model_id_with_origin_paths=None,
tokenizer_path=None,
trainable_models=None,
lora_base_model=None, lora_target_modules="", lora_rank=32, lora_checkpoint=None,
preset_lora_path=None, preset_lora_model=None,
use_gradient_checkpointing=True,
use_gradient_checkpointing_offload=False,
extra_inputs=None,
fp8_models=None,
offload_models=None,
device="cpu",
task="sft",
):
super().__init__()
# Warning
if not use_gradient_checkpointing:
warnings.warn("Gradient checkpointing is detected as disabled. To prevent out-of-memory errors, the training framework will forcibly enable gradient checkpointing.")
use_gradient_checkpointing = True
# Load models
model_configs = self.parse_model_configs(model_paths, model_id_with_origin_paths, fp8_models=fp8_models, offload_models=offload_models, device=device)
tokenizer_config = ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized") if tokenizer_path is None else ModelConfig(tokenizer_path)
self.pipe = LTX2AudioVideoPipeline.from_pretrained(torch_dtype=torch.bfloat16, device=device, model_configs=model_configs, tokenizer_config=tokenizer_config)
self.pipe = self.split_pipeline_units(task, self.pipe, trainable_models, lora_base_model)
# Training mode
self.switch_pipe_to_training_mode(
self.pipe, trainable_models,
lora_base_model, lora_target_modules, lora_rank, lora_checkpoint,
preset_lora_path, preset_lora_model,
task=task,
)
# Store other configs
self.use_gradient_checkpointing = use_gradient_checkpointing
self.use_gradient_checkpointing_offload = use_gradient_checkpointing_offload
self.extra_inputs = extra_inputs.split(",") if extra_inputs is not None else []
self.fp8_models = fp8_models
self.task = task
self.task_to_loss = {
"sft:data_process": lambda pipe, *args: args,
"sft": lambda pipe, inputs_shared, inputs_posi, inputs_nega: FlowMatchSFTAudioVideoLoss(pipe, **inputs_shared, **inputs_posi),
"sft:train": lambda pipe, inputs_shared, inputs_posi, inputs_nega: FlowMatchSFTAudioVideoLoss(pipe, **inputs_shared, **inputs_posi),
}
def parse_extra_inputs(self, data, extra_inputs, inputs_shared):
for extra_input in extra_inputs:
inputs_shared[extra_input] = data[extra_input]
return inputs_shared
def get_pipeline_inputs(self, data):
inputs_posi = {"prompt": data["prompt"]}
inputs_nega = {}
inputs_shared = {
# Assume you are using this pipeline for inference,
# please fill in the input parameters.
"input_video": data["video"],
"height": data["video"][0].size[1],
"width": data["video"][0].size[0],
"num_frames": len(data["video"]),
# Please do not modify the following parameters
# unless you clearly know what this will cause.
"cfg_scale": 1,
"tiled": False,
"rand_device": self.pipe.device,
"use_gradient_checkpointing": self.use_gradient_checkpointing,
"use_gradient_checkpointing_offload": self.use_gradient_checkpointing_offload,
"video_patchifier": self.pipe.video_patchifier,
"audio_patchifier": self.pipe.audio_patchifier,
}
inputs_shared = self.parse_extra_inputs(data, self.extra_inputs, inputs_shared)
return inputs_shared, inputs_posi, inputs_nega
def forward(self, data, inputs=None):
if inputs is None: inputs = self.get_pipeline_inputs(data)
inputs = self.transfer_data_to_device(inputs, self.pipe.device, self.pipe.torch_dtype)
for unit in self.pipe.units:
inputs = self.pipe.unit_runner(unit, self.pipe, *inputs)
loss = self.task_to_loss[self.task](self.pipe, *inputs)
return loss
def ltx2_parser():
parser = argparse.ArgumentParser(description="Simple example of a training script.")
parser = add_general_config(parser)
parser = add_video_size_config(parser)
parser.add_argument("--tokenizer_path", type=str, default=None, help="Path to tokenizer.")
parser.add_argument("--frame_rate", type=float, default=24, help="frame rate of the training videos. If not specified, it will be determined by the dataset.")
parser.add_argument("--initialize_model_on_cpu", default=False, action="store_true", help="Whether to initialize models on CPU.")
return parser
if __name__ == "__main__":
parser = ltx2_parser()
args = parser.parse_args()
accelerator = accelerate.Accelerator(
gradient_accumulation_steps=args.gradient_accumulation_steps,
kwargs_handlers=[accelerate.DistributedDataParallelKwargs(find_unused_parameters=args.find_unused_parameters)],
)
dataset = UnifiedDataset(
base_path=args.dataset_base_path,
metadata_path=args.dataset_metadata_path,
repeat=args.dataset_repeat,
data_file_keys=args.data_file_keys.split(","),
main_data_operator=UnifiedDataset.default_video_operator(
base_path=args.dataset_base_path,
max_pixels=args.max_pixels,
height=args.height,
width=args.width,
height_division_factor=16,
width_division_factor=16,
num_frames=args.num_frames,
time_division_factor=4,
time_division_remainder=1,
),
special_operator_map={
"input_audio": ToAbsolutePath(args.dataset_base_path) >> LoadAudioWithTorchaudio(duration=float(args.num_frames) / float(args.frame_rate)),
}
)
model = LTX2TrainingModule(
model_paths=args.model_paths,
model_id_with_origin_paths=args.model_id_with_origin_paths,
tokenizer_path=args.tokenizer_path,
trainable_models=args.trainable_models,
lora_base_model=args.lora_base_model,
lora_target_modules=args.lora_target_modules,
lora_rank=args.lora_rank,
lora_checkpoint=args.lora_checkpoint,
preset_lora_path=args.preset_lora_path,
preset_lora_model=args.preset_lora_model,
use_gradient_checkpointing=args.use_gradient_checkpointing,
use_gradient_checkpointing_offload=args.use_gradient_checkpointing_offload,
extra_inputs=args.extra_inputs,
fp8_models=args.fp8_models,
offload_models=args.offload_models,
task=args.task,
device="cpu" if args.initialize_model_on_cpu else accelerator.device,
)
model_logger = ModelLogger(
args.output_path,
remove_prefix_in_ckpt=args.remove_prefix_in_ckpt,
)
launcher_map = {
"sft:data_process": launch_data_process_task,
"direct_distill:data_process": launch_data_process_task,
"sft": launch_training_task,
"sft:train": launch_training_task,
"direct_distill": launch_training_task,
"direct_distill:train": launch_training_task,
}
launcher_map[args.task](accelerator, dataset, model, model_logger, args=args)

47
examples/ltx2/model_training/validate_full/LTX-2-T2AV.py Normal file
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import torch
from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
vram_config = {
"offload_dtype": torch.bfloat16,
"offload_device": "cpu",
"onload_dtype": torch.bfloat16,
"onload_device": "cuda",
"preparing_dtype": torch.bfloat16,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = LTX2AudioVideoPipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
ModelConfig(path="./models/train/LTX2-T2AV-full/epoch-4.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
)
prompt = "A beautiful sunset over the ocean."
negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
height, width, num_frames = 512, 768, 121
video, audio = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
seed=43,
height=height,
width=width,
num_frames=num_frames,
tiled=True,
cfg_scale=4.0
)
write_video_audio_ltx2(
video=video,
audio=audio,
output_path='ltx2_onestage.mp4',
fps=24,
audio_sample_rate=24000,
)

49
examples/ltx2/model_training/validate_lora/LTX-2-T2AV.py Normal file
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import torch
from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
vram_config = {
"offload_dtype": torch.bfloat16,
"offload_device": "cpu",
"onload_dtype": torch.bfloat16,
"onload_device": "cuda",
"preparing_dtype": torch.bfloat16,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = LTX2AudioVideoPipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
)
pipe.load_lora(pipe.dit, "models/train/LTX2-T2AV_lora/epoch-4.safetensors")
prompt = "A beautiful sunset over the ocean."
negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
height, width, num_frames = 512, 768, 121
height, width, num_frames = 256, 384, 25
video, audio = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
seed=43,
height=height,
width=width,
num_frames=num_frames,
tiled=True,
cfg_scale=4.0
)
write_video_audio_ltx2(
video=video,
audio=audio,
output_path='ltx2_onestage.mp4',
fps=24,
audio_sample_rate=24000,
)

49
examples/ltx2/model_training/validate_lora/LTX-2-T2AV_noaudio.py Normal file
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import torch
from diffsynth.pipelines.ltx2_audio_video import LTX2AudioVideoPipeline, ModelConfig
from diffsynth.utils.data.media_io_ltx2 import write_video_audio_ltx2
vram_config = {
"offload_dtype": torch.bfloat16,
"offload_device": "cpu",
"onload_dtype": torch.bfloat16,
"onload_device": "cuda",
"preparing_dtype": torch.bfloat16,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = LTX2AudioVideoPipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized", origin_file_pattern="model-*.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="transformer.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="text_encoder_post_modules.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="video_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vae_decoder.safetensors", **vram_config),
ModelConfig(model_id="DiffSynth-Studio/LTX-2-Repackage", origin_file_pattern="audio_vocoder.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="google/gemma-3-12b-it-qat-q4_0-unquantized"),
)
pipe.load_lora(pipe.dit, "models/train/LTX2-T2AV-noaudio_lora/epoch-4.safetensors")
prompt = "A beautiful sunset over the ocean."
negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
height, width, num_frames = 512, 768, 121
height, width, num_frames = 256, 384, 25
video, audio = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
seed=43,
height=height,
width=width,
num_frames=num_frames,
tiled=True,
cfg_scale=4.0
)
write_video_audio_ltx2(
video=video,
audio=audio,
output_path='ltx2_onestage.mp4',
fps=24,
audio_sample_rate=24000,
)

104
examples/ltx2/scripts/split_model_statedicts.py Normal file
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from safetensors.torch import save_file
from diffsynth import hash_state_dict_keys
from diffsynth.core import load_state_dict
from diffsynth.models.model_loader import ModelPool
model_pool = ModelPool()
state_dict = load_state_dict("models/Lightricks/LTX-2/ltx-2-19b-dev.safetensors")
dit_state_dict = {}
for name in state_dict:
if name.startswith("model.diffusion_model."):
new_name = name.replace("model.diffusion_model.", "")
if new_name.startswith("audio_embeddings_connector.") or new_name.startswith("video_embeddings_connector."):
continue
dit_state_dict[name] = state_dict[name]
print(f"dit_state_dict keys hash: {hash_state_dict_keys(dit_state_dict)}")
save_file(dit_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/transformer.safetensors")
model_pool.auto_load_model(
"models/DiffSynth-Studio/LTX-2-Repackage/transformer.safetensors",
)
video_vae_encoder_state_dict = {}
for name in state_dict:
if name.startswith("vae.encoder."):
video_vae_encoder_state_dict[name] = state_dict[name]
elif name.startswith("vae.per_channel_statistics."):
video_vae_encoder_state_dict[name] = state_dict[name]
save_file(video_vae_encoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/video_vae_encoder.safetensors")
print(f"video_vae_encoder keys hash: {hash_state_dict_keys(video_vae_encoder_state_dict)}")
model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/video_vae_encoder.safetensors")
video_vae_decoder_state_dict = {}
for name in state_dict:
if name.startswith("vae.decoder."):
video_vae_decoder_state_dict[name] = state_dict[name]
elif name.startswith("vae.per_channel_statistics."):
video_vae_decoder_state_dict[name] = state_dict[name]
save_file(video_vae_decoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/video_vae_decoder.safetensors")
print(f"video_vae_decoder keys hash: {hash_state_dict_keys(video_vae_decoder_state_dict)}")
model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/video_vae_decoder.safetensors")
audio_vae_decoder_state_dict = {}
for name in state_dict:
if name.startswith("audio_vae.decoder."):
audio_vae_decoder_state_dict[name] = state_dict[name]
elif name.startswith("audio_vae.per_channel_statistics."):
audio_vae_decoder_state_dict[name] = state_dict[name]
save_file(audio_vae_decoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_decoder.safetensors")
print(f"audio_vae_decoder keys hash: {hash_state_dict_keys(audio_vae_decoder_state_dict)}")
model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_decoder.safetensors")
audio_vae_encoder_state_dict = {}
for name in state_dict:
if name.startswith("audio_vae.encoder."):
audio_vae_encoder_state_dict[name] = state_dict[name]
elif name.startswith("audio_vae.per_channel_statistics."):
audio_vae_encoder_state_dict[name] = state_dict[name]
save_file(audio_vae_encoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_encoder.safetensors")
print(f"audio_vae_encoder keys hash: {hash_state_dict_keys(audio_vae_encoder_state_dict)}")
model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/audio_vae_encoder.safetensors")
audio_vocoder_state_dict = {}
for name in state_dict:
if name.startswith("vocoder."):
audio_vocoder_state_dict[name] = state_dict[name]
save_file(audio_vocoder_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/audio_vocoder.safetensors")
print(f"audio_vocoder keys hash: {hash_state_dict_keys(audio_vocoder_state_dict)}")
model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/audio_vocoder.safetensors")
text_encoder_post_modules_state_dict = {}
for name in state_dict:
if name.startswith("text_embedding_projection."):
text_encoder_post_modules_state_dict[name] = state_dict[name]
elif name.startswith("model.diffusion_model.video_embeddings_connector."):
text_encoder_post_modules_state_dict[name] = state_dict[name]
elif name.startswith("model.diffusion_model.audio_embeddings_connector."):
text_encoder_post_modules_state_dict[name] = state_dict[name]
save_file(text_encoder_post_modules_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/text_encoder_post_modules.safetensors")
print(f"text_encoder_post_modules keys hash: {hash_state_dict_keys(text_encoder_post_modules_state_dict)}")
model_pool.auto_load_model("models/DiffSynth-Studio/LTX-2-Repackage/text_encoder_post_modules.safetensors")
state_dict = load_state_dict("models/Lightricks/LTX-2/ltx-2-19b-distilled.safetensors")
dit_state_dict = {}
for name in state_dict:
if name.startswith("model.diffusion_model."):
new_name = name.replace("model.diffusion_model.", "")
if new_name.startswith("audio_embeddings_connector.") or new_name.startswith("video_embeddings_connector."):
continue
dit_state_dict[name] = state_dict[name]
print(f"dit_state_dict keys hash: {hash_state_dict_keys(dit_state_dict)}")
save_file(dit_state_dict, "models/DiffSynth-Studio/LTX-2-Repackage/transformer_distilled.safetensors")
model_pool.auto_load_model(
"models/DiffSynth-Studio/LTX-2-Repackage/transformer_distilled.safetensors",
)