+ "ݳjGTaRt 0t^RIt^RIHtHtHt^RIt^RIHt/t ]^kRt R#)N)CallableDictType) AOBaseConfigcFa\P!S4V3Rl4pV#)a" A decorator to register a transform function to map from a workflow configuration (child of `AOBaseConfig`) to a function that transforms a `torch.nn.Module` according to the specified configuration. For example:: # user facing code class WorkflowFooConfig(AOBaseConfig): ... # configuration for workflow `Foo` is defined here bar = 'baz' # non user facing code @register_quantize_module_handler(WorkflowFooConfig) def _transform( mod: torch.nn.Module, config: WorkflowFooConfig, ) -> torch.nn.Module: # the transform is implemented here, usually a tensor sublass # weight swap or a module swap ... # then, the user calls `quantize_` with a config, and `_transform` is called # under the hood by `quantize_. c<V\S&V#)N)_QUANTIZE_CONFIG_HANDLER)func config_types&f/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torchao/quantization/transform_module.py decorator3register_quantize_module_handler..decorator/s04 - ) functoolswraps)r r sf r register_quantize_module_handlerrs(8__[!" rcV^8dQh/^\9de\\\,\\ P P\.\ P P3,3,;R&#)r )__conditional_annotations__rrrrtorchnnModule)formats"r __annotate__rsS$ ehhoo| ,ehhoo =>@r) rrtypingrrrrtorchao.core.configrr rr)rs@r rs. '' ,  !r