fix(ltx2-sr): close port gaps surfaced by alignment harness retries

LTX-2 SR pipeline now passes module load + stage graph build on the
public side. Each retry of scripts/ltx2_sr_alignment.py surfaced one
more gap; this commit closes them so the pipeline progresses to the
upsample → stage-2 → decode tail.

* harness: PipelineSelection (real class name; PipelineConfig was a typo)
* FastVideoArgs: generic refine_* fields (preferred user-facing API)
* LTX2Pipeline.initialize_pipeline: getattr-with-default for
  debug_model_sums / debug_model_detail (public args lack the debug
  fields; LTX-2 still flips the env-var toggles when set)
* VAEConfig: use_temporal_scaling_frames default True (LTX-2 latent
  prep reads this in the schedule-shift gate)
* LTX2LatentPreparationStage._randn_ltx2_video_latents: switch to
  randn_tensor so list-of-generators batches work (matches internal
  sampling order)
* ModelRegistry: register LTX2LatentUpsampler in _UPSAMPLERS
* component_loader: register spatial_upsampler / temporal_upsampler
  with UpsamplerLoader (was hitting the generic stub loader);
  UpsamplerLoader gains LTX-2 fallback when pipeline_config.upsampler_config
  isn't a multi-config tuple, plus the 'model.'-prefix-stripping
  weight load path the internal version uses

7 retries -> public side now reaches the upsample stage.

Co-authored-by: Junda (David) Su <90978028+Davids048@users.noreply.github.com>
Co-authored-by: Matthew Noto <99706358+RandNMR73@users.noreply.github.com>
Co-authored-by: XOR-op <17672363+XOR-op@users.noreply.github.com>
Co-authored-by: Zhang Peiyuan <42993249+jzhang38@users.noreply.github.com>

scripts/ltx2_sr_alignment.py

@@ -140,12 +140,12 @@ def _run_typed(args: argparse.Namespace) -> RunResult:
     from fastvideo import VideoGenerator  # noqa: PLC0415
     from fastvideo.api import (  # noqa: PLC0415
         ComponentConfig, EngineConfig, GenerationRequest, GeneratorConfig,
-        InputConfig, OutputConfig, PipelineConfig, SamplingConfig)
+        InputConfig, OutputConfig, PipelineSelection, SamplingConfig)
 
     config = GeneratorConfig(
         model_path=args.model,
         engine=EngineConfig(num_gpus=1, ),
-        pipeline=PipelineConfig(
+        pipeline=PipelineSelection(
             components=ComponentConfig(),
             preset_overrides={
                 "refine": {