Add SCAIL-2 training integration (Phase 3, ltx-trainer FlexibleStrategy)

Wire SCAIL-2 driving + in-context mask conditioning into the trainer via the
unified FlexibleStrategy, so the widened patchify_proj (Phase 2) can be trained.

- flexible.py: new DrivingConditionConfig (driving-latent concat with a RoPE
  width offset ΔW) and MaskChannelsConditionConfig (semantic masks -> per-token
  channels), added to the condition union and get_data_sources. Driving is
  prepended (cond-first, target stays at the tail for loss slicing); mask
  channels are written onto the driving tokens via Modality.cond_channels,
  reusing ltx-core encode_mask_channels. The noisy target keeps a zero mask.
- model_loader.load_transformer gains mask_conditioning_channels, widening the
  video patchify_proj with zero-init columns via a new live-module helper
  (widen_module_patchify_proj_for_mask_channels). ModelConfig exposes the field.
- trainer unfreezes patchify_proj in LoRA mode when mask channels are active
  (the new input columns are new base params LoRA cannot reach).
- configs/scail_animation_lora.yaml plus README / training-modes table rows.

Verified on CPU (verify_phase3_trainer.py): config round-trips, prepare_training
_inputs builds cond_channels [B,T,56] with the mask on the driving tokens, a tiny
widened model forwards and compute_loss returns a finite [B] loss, and the widen
helper is output-preserving at zero init. Real training needs Linux+GPU+checkpoint;
dataset preprocessing (driving latents + semantic masks) and validation-runner
wiring are left for later.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

packages/ltx-trainer/configs/README.md

@@ -23,5 +23,10 @@ adjust paths, dataset, and hyperparameters.
 | **Audio Inpainting**  | —         | Generated | `mask`              | [`audio_inpainting_lora.yaml`](./audio_inpainting_lora.yaml) |
 | **A2A IC-LoRA**       | —         | Generated | `reference`         | [`a2a_ic_lora.yaml`](./a2a_ic_lora.yaml) |
 | **AV2AV IC-LoRA**     | Generated | Generated | `reference` (both)  | [`av2av_ic_lora.yaml`](./av2av_ic_lora.yaml) |
+| **SCAIL Animation**   | Generated | —         | `driving` + `mask_channels` | [`scail_animation_lora.yaml`](./scail_animation_lora.yaml) |
 
 The [`accelerate/`](./accelerate) directory holds the Accelerate launch configs (FSDP, DDP) for multi-GPU training.
+
+> **SCAIL Animation** (SCAIL-2 character animation) also sets `model.mask_conditioning_channels: 56` to widen the
+> video `patchify_proj` for the in-context mask channels; in LoRA mode that projection is unfrozen so the new columns
+> train. See [Training Modes Guide](../docs/training-modes.md).