Davids048andClaude Opus 5.5
4117696a4f
- Docs, AGENTS.md files, and skills describe ResolvedGeneratorConfig, resolve_inference_config, typed YAML, and --config plus dotted overrides for training and preprocessing instead of FastVideoArgs and flat flags. - The local tests build resolved configs (or small fakes that expose typed paths) instead of FastVideoArgs; the LoRA extraction scripts build pipelines with from_pretrained(model_path, resolved_config=...). - The mixkit README's NVFP4 snippet uses from_config with engine.quantization.transformer_quant (the from_pretrained keyword it used is rejected). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
FLUX.1-dev Local Tests
Prerequisites
- CUDA GPU
official_weights/FLUX.1-dev(Diffusers layout) or setFLUX_DEV_ROOTFASTVIDEO_ATTENTION_BACKEND=TORCH_SDPAfor parity tests
Download weights:
huggingface-cli download black-forest-labs/FLUX.1-dev --local-dir official_weights/FLUX.1-dev
Component Loader Smoke Test
Verifies CLIP/T5 encoders, tokenizers, VAE, and FlowMatch scheduler all load from the Diffusers checkpoint layout.
pytest tests/local_tests/flux/test_flux_dev_component_loaders.py -vs
Status: requires weights — not run in CI.
Pipeline Smoke Test
Short denoise + decode (2 steps, 256×256) end-to-end.
FASTVIDEO_ATTENTION_BACKEND=TORCH_SDPA \
pytest tests/local_tests/pipelines/test_flux_dev_pipeline_smoke.py -vs
Status: requires weights — not run in CI.
Pipeline Parity Test
Compares FastVideo FluxPipeline decoded image output against Diffusers FluxPipeline under identical prompt, seed, and inference parameters (4 steps, 256×256, seed=42). Tolerance: atol=5e-2.
FASTVIDEO_ATTENTION_BACKEND=TORCH_SDPA \
pytest tests/local_tests/pipelines/test_flux_dev_pipeline_parity.py -vs
Status: PASS on A40 (2026-05-11) — requires weights; not run in CI.
DiT Parity Test
Single-forward comparison of FastVideo FluxTransformer2DModel against
Diffusers FluxTransformer2DModel under identical random inputs.
FASTVIDEO_ATTENTION_BACKEND=TORCH_SDPA \
pytest fastvideo/tests/transformers/test_flux.py -vs
Status: requires weights — not run in CI. Pass evidence: PASS recorded in PORT_STATUS.md (A40, 2026-05-11).
SSIM Regression Test
Full-quality image generation compared against per-device reference images.
Reference images must be seeded first via reference_videos_cli.py.
FASTVIDEO_ATTENTION_BACKEND=TORCH_SDPA \
FASTVIDEO_TEST_FLUX_T2I_MODEL_DIR=official_weights/FLUX.1-dev \
pytest fastvideo/tests/ssim/test_flux_t2i_similarity.py -vs
Status: seeded reference images committed (TORCH_SDPA, A40, 2026-05-11) — see PORT_STATUS.md.