U d@sddlZddlmZddlmZddlmZddlmZddlmZddl m Z m Z ddZ d d Z dd d Zedfd dZdedfddZdedfddZdedfddZdS)N)get_fuser_method) fuse_conv_bn)fuse_conv_bn_relutype_before_parametrizations)ListOptionalcCs&|d}|}|D]}t||}q|S)N.)splitgetattr)model submodule_keytokenscur_modsrF/tmp/pip-unpacked-wheel-ua33x9lu/torch/ao/quantization/fuse_modules.py _get_modules   rcCsB|d}|dd}|}|D]}t||}qt||d|dS)Nr )r r setattr)r r modulerZ sub_tokensrrrrr _set_modules    rc Cstdd|D}t||}|dkr2td|dgt|}||f|}|djD]\}}|||dj|=q\|djD]\}} | | |dj|=q||d<t dt|D] } t } |dj | _ | || <q|S)a|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() css|]}t|VqdSNr).0mrrr -sz%fuse_known_modules..NzCannot fuse modules: {}rr)tuplerNotImplementedErrorformatlenZ_forward_pre_hooksitemsZregister_forward_pre_hookZ_forward_hooksZregister_forward_hookrangennZIdentityZtraining) mod_listis_qatadditional_fuser_method_mappingtypesZ fuser_methodnew_modZfusedZ handle_idZ pre_hook_fnZhook_fniidentityrrrfuse_known_modules s$      r+c Csh|dkr i}|di}g}|D]}|t||q ||||}t|D]\} }t|||| qJdS)Nr&)getappendr enumerater) r modules_to_fuser% fuser_funcfuse_custom_config_dictr&r$itemZ new_mod_listr)rrr_fuse_modules_helperEs  r3FcCsP|st|}tdd|Dr2t|||||n|D]}t|||||q6|S)Ncss|]}t|tVqdSr) isinstancestr)rZmodule_elementrrrrXsz _fuse_modules..)copydeepcopyallr3)r r/r%inplacer0r1Z module_listrrr _fuse_modulesTs r:cCst||d|tddS)aDFuses 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:: >>> 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) FNr%r9r0r1r:r+r r/r9r0r1rrr fuse_modulesas6r>cCst||d|tddS)z$ QAT version for `fuse_modules` TNr;r<r=rrrfuse_modules_qatsr?)N)r6Ztorch.nnr#Z+torch.ao.quantization.fuser_method_mappingsrrrZtorch.nn.utils.parametrizertypingrrrrr+r3r:r>r?rrrrs      % >