fix: gate feature-injection kwargs on TensorRT backend in SD1.5/2.1 UNet call#12
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…Net call The SD1.5/2.1 branch of unet_step() unconditionally passed kvo_cache/fio_cache/ fi_strength/fi_threshold to self.unet(...). The import-time diffusers patch (_patches/diffusers_kvo_patch.py) adds kvo_cache support to the eager PyTorch UNet, but feature injection is TensorRT-engine-only — the patched forward() has no fio_cache/fi_strength/fi_threshold parameters. Every non-TRT SD1.5/2.1 run (e.g. acceleration: none) crashed on the first call: UNet2DConditionModel.forward() got an unexpected keyword argument 'fio_cache' Mirrors the SDXL branch's existing _check_unet_tensorrt() gate: kvo_cache is always passed (both backends support it), the FI trio only when TRT is active. Adds tests/unit/test_unet_call_backend_gate.py, which reproduces the crash via a real (patched) tiny UNet2DConditionModel at the actual unet_step() call site and locks in that the TensorRT path keeps receiving all four cache kwargs.
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…Net call (#12) (#13) The SD1.5/2.1 branch of unet_step() unconditionally passed kvo_cache/fio_cache/ fi_strength/fi_threshold to self.unet(...). The import-time diffusers patch (_patches/diffusers_kvo_patch.py) adds kvo_cache support to the eager PyTorch UNet, but feature injection is TensorRT-engine-only — the patched forward() has no fio_cache/fi_strength/fi_threshold parameters. Every non-TRT SD1.5/2.1 run (e.g. acceleration: none) crashed on the first call: UNet2DConditionModel.forward() got an unexpected keyword argument 'fio_cache' Mirrors the SDXL branch's existing _check_unet_tensorrt() gate: kvo_cache is always passed (both backends support it), the FI trio only when TRT is active. Adds tests/unit/test_unet_call_backend_gate.py, which reproduces the crash via a real (patched) tiny UNet2DConditionModel at the actual unet_step() call site and locks in that the TensorRT path keeps receiving all four cache kwargs.
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Summary
acceleration: none/xformers/sfast):UNet2DConditionModel.forward() got an unexpected keyword argument 'fio_cache'.unet_step()'s SD1.5/2.1 branch unconditionally passedfio_cache/fi_strength/fi_thresholdtoself.unet(...), but those TensorRT-only feature-injection kwargs are not understood by the patched eager PyTorch UNet (_patches/diffusers_kvo_patch.pyonly addskvo_cache). The SDXL branch already gated these correctly on_check_unet_tensorrt(); the SD1.5/2.1 branch did not.kvo_cache(supported on both backends via the import-time patch), but gatefio_cache/fi_strength/fi_thresholdbehindself._check_unet_tensorrt(), matching the SDXL branch's convention.sd-turbo/SD2.1,acceleration: none).Test plan
tests/unit/test_unet_call_backend_gate.py— constructsStreamDiffusionvia__new__(no model download) and a real patched tinyUNet2DConditionModel; watched red pre-fix (TypeError: unexpected keyword argument 'fio_cache'), green post-fix../venv/Scripts/python.exe -m pytest tests/unit -q).ruff checkclean on both changed files.🤖 Generated with Claude Code