Source code for torch.ao.quantization.fuse_modules
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
[docs]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)
