get_fqn_to_example_inputs

class torch.ao.quantization.utils.get_fqn_to_example_inputs(model, example_inputs)

Given a model and its example inputs, return a dictionary from fully qualified name of submodules to example_inputs for that submodule, e.g. {"linear1": (tensor1,), "linear2": (tensor2,), "sub": (tensor3,), "sub.linear1": (tensor4,), ...}

Used to make quantizing submodules easier now that FX Graph Mode Quantization requires example inputs.

Also works for keyword arguments with default values, we would flatten keyword arguments as positional arguments and fill in the missing keyword args with default values, e.g. if we have a forward function:

def forward(self, x, key1=3, key2=3): ...

and we call it with self.submodule(x, key2=6) we’ll get example_inputs: (x, 3, 6)

user can also override key1 with positional arguments as well: for self.submodule(x, 5, key2=6) we’ll get: (x, 5, 6)

variable positional arguments and variable positional keyword arguments in forward function are not supported currently, so please make sure no submodules is using them.

Return type:

dict[str, tuple[Any, …]]