Three source recipes (T2VA, keyframes, Ref2VA) on one model page under
MiniMax H3, with knobs for task, resolution tier, aspect bucket,
duration, NVFP4 decoder and text encoder, offload mode, and GPU count.
The page uses the official Pika-Labs Hugging Face avatar.
The runbook now gives the FASTVIDEO_ATTENTION_BACKEND=FLASH_ATTN
FASTVIDEO_FA4=1 launch prefix and the SDPA fallback, the tier override,
and measured GB200 timings and memory. The example selects the bucket
with --resolution/--aspect, the frame count with --duration, and
--offload resident|lazy.
An adapter that trains a subset of the wrapped linears (Pika skips the
AdaLN projections) logged one warning per layer, about 200 per run.
Log one summary with the count and a few names.
The sampling param and presets fill 768x1344 before input preparation, so
an exact p768 bucket always won and the configured tier never applied.
Resolve the omitted canvas in apply_request_constraints, where explicit
request fields are still distinguishable; explicit sizes keep their tier
and one-sided sizes are rejected.
Applying the automatic Pika adapter inside the transformer's lazy load ran
_drop_pinned_host_copies, which read __dict__ through every LazyModule
proxy and reloaded the already-released text encoder and both VAEs.
Skip unmaterialized proxies and clear the real module of resident ones.
Expose the exported H3 NVFP4 VAE decoder through ComponentConfig and map it to FastVideoArgs, alongside the existing text-encoder weight override. Add example flags and docs for the 36L quality and 8L fast decoder tiers, including the 8L depth-cut and no-NVFP4-VAE-encoder caveats. Add compat translation tests.
The constructor LoRA adapter (Pika H3 Flex's released adapter) reads
param_names_mapping through the LazyModule proxy while the materialize
transform is still running. Nothing was published yet, so the access
re-entered materialize and reloaded the 66 GB transformer repeatedly,
ending in CUDA OOM with lazy_module_load=True (the example default).
Publish the loaded instance before running the transform.
Remove the unsupported pipeline.preset selection from the example; the compatibility adapter rejects it before model loading. Load the last image as a PIL image because the request adapter does not do it for the stage. Document that the local Ref2VA path enforces reference counts and the 22-frame video floor, but not Pika's hosted per-clip/per-modality duration caps.
Add Pika H3 Flex (MiniMax-H3 plus the released fl2va/ref2va rank-128 adapters) as a FastVideo model family: registry/config/presets, bucket geometry with tiered reference sizing, automatic adapter selection and manifest validation, the fixed six-forward re-noise sampler, T2VA/I2VA/L2VA/FL2VA/Ref2VA pipeline support, an example, docs, and CPU unit tests.
GPU end-to-end validation is still pending. This change does not add PDD, VSA, or new kernel paths.
BaseLayerWithLoRA.forward was decorated with torch.compile, so wrapping a linear also compiled its base layer.
Compiling a packed NVFP4/FP8 linear on its own changes its numerics, so a wrapped layer at strength 0 could differ
from the unwrapped layer. forward now adds no compiled region: the base layer runs exactly as it would unwrapped
(eagerly, or traced with a caller's compiled block), and only the adapter delta is compiled.
The unit lane fails on main in two contract tests. All three failures are
bookkeeping that drifted from the code, not runtime bugs:
- `test_env_policy.py::test_env_doc_table_matches_registry`: the generated
table in docs/contributing/env_vars.md is stale for
FASTVIDEO_MLX_QUANT_GEMM. Regenerated with the documented command
(`python fastvideo/tests/contract/test_env_policy.py`).
- `test_env_policy.py::test_env_access_follows_policy`: two new violations.
- fastvideo/tests/mlx/test_mlx_affine_dq_gemm.py wrote
FASTVIDEO_MLX_QUANT_GEMM through monkeypatch.setenv; now uses the
registered field's override() through the env_overrides fixture.
- fastvideo/tests/train/models/test_load_kandinsky5.py read
FASTVIDEO_ATTENTION_BACKEND with `not in os.environ`; now uses
envs.FASTVIDEO_ATTENTION_BACKEND.is_set() and override(). Its entry in
KNOWN_VIOLATIONS is deleted, as the shrinking-list rule requires.
- `test_schema_parity_inventory.py::..._extension_fields_are_classified`:
MiniMaxH3PipelineConfig declares video_scheduler_shift and
audio_scheduler_shift (training-time noise clocks rejected by
check_pipeline_config at inference); both are added to
pipeline_config_extensions.internal_only.
Test plan (CPU, no GPU required):
python -m pytest fastvideo/tests/contract/test_env_policy.py \
fastvideo/tests/api/test_schema_parity_inventory.py \
fastvideo/tests/mlx/test_mlx_affine_dq_gemm.py -q
# 45 passed
python -m pytest fastvideo/tests/contract/ fastvideo/tests/api/ -q -m "not gpu"
# 501 passed
VideoGenerator.from_config calls from_fastvideo_args with a log_queue keyword
argument. The StreamingVideoGenerator override did not accept it, so
StreamingVideoGenerator.from_pretrained raised TypeError. The override now
accepts log_queue and passes it to the executor through VideoGenerator.__init__.
A new test covers the call.
The HunyuanVideo batch test wrote MASTER_PORT, MASTER_ADDR and
FASTVIDEO_ATTENTION_BACKEND with monkeypatch.setenv, so the environment-variable
contract test failed. The fixture now uses envs.override_external and the
registry override. The values and the restore behavior do not change.
Aryan Kumar