registry

Registries dispatching per-module logic for the unified HF export path.

This mirrors the registration-and-dispatch idiom of QuantModuleRegistry, but not its mechanism: quantization registers replacement classes and converts modules in place, whereas export registers functions that emit compressed weights and scale buffers for a module without changing its class.

Preparation and export use separate registries because they have independent matching precedence. Registering a handler for a new module type replaces what previously required editing if/elif chains inside unified_export_hf.py.

Classes

ExportContext

Shared state for a single export invocation, passed to every handler call.

class ExportContext

Bases: object

Shared state for a single export invocation, passed to every handler call.

Tied-weight dedup is not a handler concern: the driver builds one name-based TiedWeightMap and feeds it to sync_tied_input_amax and postprocess_state_dict directly. Both dense and fused-MoE tied weights are packed independently and their duplicate keys are dropped by name there, so the context carries no tied-weight map (handlers never consulted it).

__init__(model, dtype, is_modelopt_qlora=False, model_type=None)

Parameters:

• model (Module)

• dtype (dtype)

• is_modelopt_qlora (bool)

• model_type (str | None)

Return type:

None

dtype: dtype

is_modelopt_qlora: bool = False

model: Module

model_type: str | None = None

The model’s HF model type (model.config.model_type), used to resolve the model’s spec in modelopt.torch.models. None means unknown: spec lookups then fail loudly instead of guessing.