[bugfix]: apply the LTX-2 refine LoRA to the refine transformer
The from_pretrained keyword ltx2_refine_lora_path set pipeline.components.lora_path, which reaches FastVideoArgs.lora_path and loads as the main LoRA on the stage-1 transformer. The refine stage reads FastVideoArgs.ltx2_refine_lora_path, which stayed unset. The conversion also turned an empty string into None. An empty string is how callers such as the Dreamverse GPU pool disable the refine LoRA, and None makes LTX2Pipeline load the checkpoint default instead: fastvideo_refine_lora_path in model_index.json is FastVideo/LTX2-Distilled-LoRA for the LTX-2 Diffusers checkpoints. The refine LoRA gets its own field, pipeline.ltx2.refine.lora_path, whose flat name is ltx2_refine_lora_path. None keeps the checkpoint default, and an empty string disables the refine LoRA. The Dreamverse contract test, the Dynamo contract example, and the parity inventory point at the field. Golden changes: kwargs/ltx2_refine_lora_path now records the path on ltx2_refine_lora_path instead of lora_path, and the added case kwargs/ltx2_refine_lora_disabled pins the empty string. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
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@@ -56,7 +56,7 @@ Typed-API mapping (legacy kwarg ↔ typed field)
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- ``ltx2_vae_tiling`` ↔ ``pipeline.vae_tiling``
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- ``ltx2_refine_enabled`` ↔ ``pipeline.preset_overrides["refine"]["enabled"]``
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- ``ltx2_refine_upsampler_path`` ↔ ``pipeline.components.upsampler_weights``
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- ``ltx2_refine_lora_path`` ↔ ``pipeline.components.lora_path``
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- ``ltx2_refine_lora_path`` ↔ ``pipeline.ltx2.refine.lora_path``
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- ``ltx2_refine_num_inference_steps`` ↔ ``pipeline.preset_overrides["refine"]["num_inference_steps"]``
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- ``ltx2_refine_guidance_scale`` ↔ ``pipeline.preset_overrides["refine"]["guidance_scale"]``
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- ``ltx2_refine_add_noise`` ↔ ``pipeline.preset_overrides["refine"]["add_noise"]``
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