import copy import torch.nn as nn from torch.ao.quantization.fuser_method_mappings import get_fuser_method # for backward compatibility from torch.ao.quantization.fuser_method_mappings import fuse_conv_bn # noqa: F401 from torch.ao.quantization.fuser_method_mappings import fuse_conv_bn_relu # noqa: F401 from torch.nn.utils.parametrize import type_before_parametrizations from typing import List, Optional __all__ = [ "fuse_known_modules", "fuse_modules", "fuse_modules_qat", ] # Generalization of getattr def _get_module(model, submodule_key): tokens = submodule_key.split('.') cur_mod = model for s in tokens: cur_mod = getattr(cur_mod, s) return cur_mod # Generalization of setattr def _set_module(model, submodule_key, module): tokens = submodule_key.split('.') sub_tokens = tokens[:-1] cur_mod = model for s in sub_tokens: cur_mod = getattr(cur_mod, s) setattr(cur_mod, tokens[-1], module) def fuse_known_modules(mod_list, is_qat, additional_fuser_method_mapping=None): r"""Return a list of known fuse modules. Returns a list of modules that fuses the operations specified in the input module list. Fuses only the following sequence of modules: conv, bn conv, bn, relu conv, relu linear, bn linear, relu For these sequences, the first element in the output module list performs the fused operation. The rest of the elements are set to nn.Identity() """ types = tuple(type_before_parametrizations(m) for m in mod_list) fuser_method = get_fuser_method(types, additional_fuser_method_mapping) if fuser_method is None: raise NotImplementedError(f"Cannot fuse modules: {types}") new_mod : List[Optional[nn.Module]] = [None] * len(mod_list) fused = fuser_method(is_qat, *mod_list) # NOTE: forward hooks not processed in the two following for loops will be lost after the fusion # Move pre forward hooks of the base module to resulting fused module for pre_hook_fn in mod_list[0]._forward_pre_hooks.values(): fused.register_forward_pre_hook(pre_hook_fn) mod_list[0]._forward_pre_hooks.clear() # Move post forward hooks of the last module to resulting fused module for hook_fn in mod_list[-1]._forward_hooks.values(): fused.register_forward_hook(hook_fn) mod_list[-1]._forward_hooks.clear() new_mod[0] = fused for i in range(1, len(mod_list)): identity = nn.Identity() identity.training = mod_list[0].training new_mod[i] = identity return new_mod def _fuse_modules_helper(model, modules_to_fuse, is_qat, fuser_func=fuse_known_modules, fuse_custom_config_dict=None): if fuse_custom_config_dict is None: fuse_custom_config_dict = {} additional_fuser_method_mapping = fuse_custom_config_dict.get("additional_fuser_method_mapping", {}) mod_list = [] for item in modules_to_fuse: mod_list.append(_get_module(model, item)) # Fuse list of modules new_mod_list = fuser_func(mod_list, is_qat, additional_fuser_method_mapping) # Replace original module list with fused module list for i, item in enumerate(modules_to_fuse): _set_module(model, item, new_mod_list[i]) def _fuse_modules(model, modules_to_fuse, is_qat, inplace=False, fuser_func=fuse_known_modules, fuse_custom_config_dict=None): if not inplace: model = copy.deepcopy(model) if all(isinstance(module_element, str) for module_element in modules_to_fuse): # Handle case of modules_to_fuse being a list _fuse_modules_helper(model, modules_to_fuse, is_qat, fuser_func, fuse_custom_config_dict) else: # Handle case of modules_to_fuse being a list of lists for module_list in modules_to_fuse: _fuse_modules_helper(model, module_list, is_qat, fuser_func, fuse_custom_config_dict) return model def fuse_modules(model, modules_to_fuse, inplace=False, fuser_func=fuse_known_modules, fuse_custom_config_dict=None): r"""Fuse a list of modules into a single module. Fuses only the following sequence of modules: conv, bn conv, bn, relu conv, relu linear, relu bn, relu All other sequences are left unchanged. For these sequences, replaces the first item in the list with the fused module, replacing the rest of the modules with identity. Args: model: Model containing the modules to be fused modules_to_fuse: list of list of module names to fuse. Can also be a list of strings if there is only a single list of modules to fuse. inplace: bool specifying if fusion happens in place on the model, by default a new model is returned fuser_func: Function that takes in a list of modules and outputs a list of fused modules of the same length. For example, fuser_func([convModule, BNModule]) returns the list [ConvBNModule, nn.Identity()] Defaults to torch.ao.quantization.fuse_known_modules `fuse_custom_config_dict`: custom configuration for fusion .. code-block:: python # Example of fuse_custom_config_dict fuse_custom_config_dict = { # Additional fuser_method mapping "additional_fuser_method_mapping": { (torch.nn.Conv2d, torch.nn.BatchNorm2d): fuse_conv_bn }, } Returns: model with fused modules. A new copy is created if inplace=True. Examples:: >>> # xdoctest: +SKIP >>> m = M().eval() >>> # m is a module containing the sub-modules below >>> modules_to_fuse = [ ['conv1', 'bn1', 'relu1'], ['submodule.conv', 'submodule.relu']] >>> fused_m = torch.ao.quantization.fuse_modules(m, modules_to_fuse) >>> output = fused_m(input) >>> m = M().eval() >>> # Alternately provide a single list of modules to fuse >>> modules_to_fuse = ['conv1', 'bn1', 'relu1'] >>> fused_m = torch.ao.quantization.fuse_modules(m, modules_to_fuse) >>> output = fused_m(input) """ return _fuse_modules( model, modules_to_fuse, is_qat=False, inplace=inplace, fuser_func=fuser_func, fuse_custom_config_dict=fuse_custom_config_dict) def fuse_modules_qat(model, modules_to_fuse, inplace=False, fuser_func=fuse_known_modules, fuse_custom_config_dict=None): """QAT version for `fuse_modules`.""" return _fuse_modules( model, modules_to_fuse, is_qat=True, inplace=inplace, fuser_func=fuser_func, fuse_custom_config_dict=fuse_custom_config_dict)