Adds ModelType.model_parts()/has_multiple_text_encoders()/supported_training_methods()
as the single source of truth for which components a model has and which training
methods it supports. BaseModelTabView.build_content and TopBarController now derive
the Model tab layout and training-method dropdown generically from these, replacing
one hand-written per-model method / if-chain each.

Brings in the Ctk/PySide6 UI split (Base*View.py + *Controller.py) on
top of split-offload's per-component offloading UI. Resolved conflicts:

- ModelType.py: kept centralize-model-type's diffusion-model-first
  _MODEL_PARTS ordering (matches lora-output-formats).
- ModelTab.py/TopBar.py: deleted (already replaced by
  BaseModelTabView.py/TopBarController.py; split-offload never
  diverged on these files, so no porting needed here).
- TrainUI.py/TrainingTab.py: deleted, with their per-component
  offloading UI (__create_offloading_widgets, VAE frame, "Async
  Offloading" switch) ported onto BaseTrainingTabView.py/
  BaseTrainUIView.py in place of the removed OffloadingWindow popup
  and its now-dead Base/Ctk/PySide6OffloadingWindowView.py +
  OffloadingWindowController.py split.

Resolves conflicts by keeping split-offload's per-component offload_fraction API
and reconciling it with centralize-model-type's ModelType/ModelTabController
centralization. Also ports the per-component checkpointing API (3-arg
enable_checkpointing_for_* calls, no global gradient_checkpointing.enabled()
guard) to Anima/Krea2, which were merged in as new files and had missed it, and
fixes the Krea2 16GB LoRA preset to the current per-part offload_fraction format.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

BaseAnimaSetup/BaseKrea2Setup were added wholesale by the centralize-model-type
merge and kept the old enabled()-guarded call pattern instead of the new
part-based one applied to Chroma/Qwen during conflict resolution.

# Conflicts:
#	modules/modelSetup/BaseChromaSetup.py
#	modules/modelSetup/BaseFlux2Setup.py
#	modules/modelSetup/BaseQwenSetup.py
#	modules/modelSetup/BaseZImageSetup.py

- default activation_offloading to False for fresh configs (it previously
  only took effect combined with layer offloading, so a fresh fine-tune
  now offloads activations out of the box, which enable_activation_offloading
  never did)
- hide the no-op "Layer Offload Fraction" control for CLIP text encoders,
  whose conductor is discarded in setup_optimizations
- narrow the caching_threads/layer-offloading guard in create_data_loader
  to the text-encoder parts that actually run in the caching dataloader's
  worker threads, via a new ModelType.text_encoder_parts() helper
- drop the dead model.vae.enable_gradient_checkpointing() call: the base
  SD setup only ever decodes the VAE under torch.no_grad(), so checkpointing
  it never had any effect; VAEs are small enough that FINE_TUNE_VAE doesn't
  need it either

…ding from train

- do not gate checkpointing or offloading on a part's train flag: grad can
  flow through a frozen part (embedding training runs grad through the frozen
  denoiser and text encoders), where checkpointing and offloading still save
  VRAM. checkpointing_enabled() -> gradient_checkpointing; offloading_enabled()
  -> offload_fraction > 0 or activation_offloading. Restores pre-branch
  behaviour for embedding training.
- reject offloading with checkpointing disabled (raise NotImplementedError)
  instead of silently forcing checkpointing on: the current offload modes need
  the use_reentrant recompute to service the backward pass.
- CLIP encoder checkpointing passes offload_enabled=False so a migrated
  offload_fraction can never build a self-activating conductor for a
  non-offloadable text encoder.
- hide the dead Layer Offload Fraction / Offload Activations controls for the
  SD/SDXL unet and Wuerstchen prior (no conductor), and gate the SD/SDXL native
  gradient checkpointing on checkpointing_enabled() so a dead offload toggle
  can no longer flip it on.
- derive ModelType.has_multiple_text_encoders() from model_parts() instead of a
  parallel is_*() chain.
- remove the dead LayerOffloadConductor.layer_offload_activated().

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