Files
automatic/modules/ltx/ltx_capabilities.py
T
CalamitousFelicitousness 5cf46d2f81 feat(ltx): canonical LTX-2.x Stage 2 recipe (LoRA + guidance + connectors)
Implement the Lightricks two-stage recipe (diffusers PR #13217) for the
LTX-2.x Dev family: Stage 1 at half-res with full four-way guidance,
2x latent upsample, Stage 2 with distilled LoRA + scheduler swap + identity
guidance on STAGE_2_DISTILLED_SIGMA_VALUES.

Extends to both LTX-2.0 and LTX-2.3 Dev via per-family distilled-LoRA
repos carried on the caps; Distilled variants take the same flow minus
the LoRA swap. Auto-couples Refine with a fixed 2x upsample on any Dev
variant with a known LoRA when the user enables Refine without Upsample.

- caps: is_ltx_2_3, use_cross_timestep, default_dynamic_shift,
  stage2_dev_lora_repo, supports_canonical_stage2, modality_default_scale,
  guidance_rescale_default; LTX-2.x defaults realigned to canonical
  cfg=3.0 / steps=30; per-variant STG block and four-way guidance wired
  for non-distilled 2.x
- process: canonical Stage 1/Stage 2 helpers, scheduler + opts snapshot
  under try/finally, per-family upsampler repo, audio latents threaded
  from Stage 1 into Stage 2, use_cross_timestep gated per caps
- overrides: skip the redundant unsharded LTX-2.3 connectors blob and
  share LTX2TextConnectors weights across 2.3 variants when te_shared_t5
- load: Gemma3 shared-TE path for LTX-2.3; gate use_dynamic_shifting=False
  override to 0.9.x only so LTX-2.x stays on its canonical token-count
  dynamic shift
2026-04-19 03:37:25 +01:00

135 lines
4.5 KiB
Python

from dataclasses import dataclass, field
from typing import Optional
from modules.logger import log
@dataclass
class LTXCaps:
name: str
repo_cls_name: str
family: str # '0.9' or '2.x'
is_distilled: bool
is_ltx_2_3: bool
is_i2v: bool
supports_input_media: bool
supports_multi_condition: bool
supports_image_cond_noise_scale: bool
supports_decode_timestep: bool
supports_stg: bool
supports_audio: bool
supports_frame_rate_kwarg: bool
# 2.3 transformer cross-attn reads the other modality's sigma; unset falls back to 2.0's
# independent-sigma path, which is a joint-distribution mismatch for 2.3 weights.
use_cross_timestep: bool
default_cfg: float
default_steps: int
default_sampler_shift: float
default_dynamic_shift: bool
default_width: int
default_height: int
default_frames: int
default_frame_rate: int
stg_default_scale: float = 0.0
stg_default_blocks: list = field(default_factory=list)
# Dev 2.x trained under cfg + stg + modality + rescale four-way composition;
# distilled bakes these into its sigma schedule and stays at pipeline identity.
modality_default_scale: float = 1.0
guidance_rescale_default: float = 0.0
supports_canonical_stage2: bool = False
stage2_dev_lora_repo: Optional[str] = None
CONDITION_CLASSES = {'LTXConditionPipeline', 'LTX2ConditionPipeline'}
LTX2_CLASSES = {'LTX2Pipeline', 'LTX2ImageToVideoPipeline', 'LTX2ConditionPipeline'}
ALL_LTX_CLASSES = {
'LTXPipeline',
'LTXImageToVideoPipeline',
'LTXConditionPipeline',
'LTX2Pipeline',
'LTX2ImageToVideoPipeline',
'LTX2ConditionPipeline',
}
def _repo_cls_name(model_name: str) -> Optional[str]:
from modules.video_models.models_def import models
entries = models.get('LTX Video', [])
for m in entries:
if m.name == model_name:
if m.repo_cls is None:
return None
return m.repo_cls.__name__
return None
def get_caps(model_name: str) -> Optional[LTXCaps]:
if not model_name or model_name == 'None':
return None
cls_name = _repo_cls_name(model_name)
if cls_name is None:
log.warning(f'LTX caps: model="{model_name}" has no repo_cls registered')
return None
if cls_name not in ALL_LTX_CLASSES:
log.warning(f'LTX caps: model="{model_name}" repo_cls="{cls_name}" is not an LTX pipeline')
return None
is_ltx2 = cls_name in LTX2_CLASSES
family = '2.x' if is_ltx2 else '0.9'
is_distilled = 'Distilled' in model_name
is_i2v = 'I2V' in model_name or cls_name in ('LTXImageToVideoPipeline', 'LTX2ImageToVideoPipeline')
is_condition_cls = cls_name in CONDITION_CLASSES
supports_input_media = is_i2v or is_condition_cls
is_ltx_2_3 = is_ltx2 and '2.3' in model_name
caps = LTXCaps(
name=model_name,
repo_cls_name=cls_name,
family=family,
is_distilled=is_distilled,
is_ltx_2_3=is_ltx_2_3,
is_i2v=is_i2v,
supports_input_media=supports_input_media,
supports_multi_condition=is_condition_cls,
supports_image_cond_noise_scale=(cls_name == 'LTXConditionPipeline'),
supports_decode_timestep=(family == '0.9'),
supports_stg=is_ltx2,
supports_audio=is_ltx2,
supports_frame_rate_kwarg=is_ltx2,
use_cross_timestep=is_ltx_2_3,
default_cfg=3.0,
default_steps=30 if is_ltx2 else 50,
default_sampler_shift=-1.0,
default_dynamic_shift=is_ltx2,
default_width=768,
default_height=512,
default_frames=121 if is_ltx2 else 161,
default_frame_rate=24 if is_ltx2 else 25,
)
if is_distilled:
caps.default_cfg = 1.0
caps.default_steps = 8
if is_ltx2 and not is_distilled:
if is_ltx_2_3:
caps.stage2_dev_lora_repo = 'CalamitousFelicitousness/LTX-2.3-distilled-lora-384-Diffusers'
elif '2.0' in model_name:
caps.stage2_dev_lora_repo = 'CalamitousFelicitousness/LTX-2.0-distilled-lora-384-Diffusers'
caps.supports_canonical_stage2 = caps.stage2_dev_lora_repo is not None
if is_ltx2:
if '2.3' in model_name:
caps.stg_default_blocks = [28]
elif '2.0' in model_name:
caps.stg_default_blocks = [29]
else:
caps.stg_default_blocks = [28]
if not is_distilled:
# canonical T2V composition from huggingface/diffusers#13217
caps.stg_default_scale = 1.0
caps.modality_default_scale = 3.0
caps.guidance_rescale_default = 0.7
return caps