Every parameter, attribute, and keyword argument that carries the runtime
config is named resolved_config instead of fastvideo_args, including the
RPC kwargs keys between the executors and the workers. The module path
fastvideo.fastvideo_args is unchanged. The rename is mechanical (a
token-level rewrite) plus yapf line wrapping.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
ResolvedGeneratorConfig becomes the runtime config of every mode. Resolution
builds the model's PipelineConfig once, freezes it, and attaches it as
resolved_config.pipeline_config; it also exposes mode, training_mode, and
inference_mode. VideoGenerator, fastvideo serve, the OpenAI server state,
the executors, the worker, and ComposedPipelineBase receive the resolved
config instead of a FastVideoArgs, and generator_config_to_fastvideo_args
is no longer on the inference path.
- Schema: ExecutionMode and WorkloadType move to fastvideo/api/schema.py;
typed homes for mode, output_type, boundary_ratio, master_port,
moba_config, and the LTX-2 refine settings; Enum parsing.
- Resolution: steps for the refine preset overrides, flat experimental
keys, the V-MoBA config, the validation that check_fastvideo_args did,
the num_gpus bump, the model's vae_tiling default, and a final
fill_runtime_defaults step for typed fields no earlier step decides.
- fastvideo/api/training_schema.py: TrainingRunConfig and
PreprocessRunConfig roots, their resolvers, and a --config plus dotted
override loader.
- fastvideo/api/device_policy.py: the device offload policy as functions
that return an overridden config; the worker keeps the result. The LTX-2
and MiniMax-H3 checkpoint defaults rebind the pipeline's config.
- fastvideo/api/flat_name_fallback.py answers the flat FastVideoArgs names
on the resolved config until the readers move to typed paths.
Golden changes: the decisions of the steps above are recorded, and
FastVideoArgs.ltx2_vae_tiling holds the model's vae_tiling (it held None;
no runtime code reads it). Against the 3f6893a0 goldens every
FastVideoArgs field, PipelineConfig, and SamplingParam matches, except
disable_autocast and boundary_ratio, which FastVideoArgs held at their
defaults because flattening routed them only to PipelineConfig.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
python -m fastvideo.entrypoints.openai.api_server parsed the hand-written
FastVideoArgs argparse flags, an inference input path next to the typed config
that fastvideo serve reads. It is removed; start the server with
fastvideo serve --config SERVE_CONFIG and dotted overrides such as
--server.port 8000. The GPU integration test starts the server that way, with
the same model, GPU count, and DiT offload.
FastVideoArgs.add_cli_args stays for the legacy training and preprocessing
scripts.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
python -m fastvideo.entrypoints.openai.api_server parses the hand-written
FastVideoArgs argparse flags, a second input system next to the typed config
that fastvideo serve reads. It keeps working unchanged during the transition
and logs a warning that points to fastvideo serve --config with dotted
overrides.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
