mirror of
https://github.com/huggingface/pytorch-image-models.git
synced 2025-06-03 15:01:08 +08:00
57 lines
1.5 KiB
Python
57 lines
1.5 KiB
Python
""" Norm Layer Factory
|
|
|
|
Create norm modules by string (to mirror create_act and creat_norm-act fns)
|
|
|
|
Copyright 2022 Ross Wightman
|
|
"""
|
|
import functools
|
|
import types
|
|
from typing import Type
|
|
|
|
import torch.nn as nn
|
|
|
|
from .norm import GroupNorm, GroupNorm1, LayerNorm, LayerNorm2d, RmsNorm
|
|
from torchvision.ops import FrozenBatchNorm2d
|
|
|
|
_NORM_MAP = dict(
|
|
batchnorm=nn.BatchNorm2d,
|
|
batchnorm2d=nn.BatchNorm2d,
|
|
batchnorm1d=nn.BatchNorm1d,
|
|
groupnorm=GroupNorm,
|
|
groupnorm1=GroupNorm1,
|
|
layernorm=LayerNorm,
|
|
layernorm2d=LayerNorm2d,
|
|
rmsnorm=RmsNorm,
|
|
frozenbatchnorm2d=FrozenBatchNorm2d,
|
|
)
|
|
_NORM_TYPES = {m for n, m in _NORM_MAP.items()}
|
|
|
|
|
|
def create_norm_layer(layer_name, num_features, **kwargs):
|
|
layer = get_norm_layer(layer_name)
|
|
layer_instance = layer(num_features, **kwargs)
|
|
return layer_instance
|
|
|
|
|
|
def get_norm_layer(norm_layer):
|
|
if not norm_layer:
|
|
# None or '' should return None
|
|
return None
|
|
assert isinstance(norm_layer, (type, str, types.FunctionType, functools.partial))
|
|
norm_kwargs = {}
|
|
|
|
# unbind partial fn, so args can be rebound later
|
|
if isinstance(norm_layer, functools.partial):
|
|
norm_kwargs.update(norm_layer.keywords)
|
|
norm_layer = norm_layer.func
|
|
|
|
if isinstance(norm_layer, str):
|
|
layer_name = norm_layer.replace('_', '')
|
|
norm_layer = _NORM_MAP[layer_name]
|
|
else:
|
|
norm_layer = norm_layer
|
|
|
|
if norm_kwargs:
|
|
norm_layer = functools.partial(norm_layer, **norm_kwargs) # bind/rebind args
|
|
return norm_layer
|