gau-nernst

from torch import nn
from torchvision.models import resnet, mobilenet, efficientnet
from torchvision.models.feature_extraction import create_feature_extractor


class _Extractor(nn.Module):
    def __init__(self, backbone, node_names):
        super().__init__()
        self.feat_extractor = create_feature_extractor(backbone, node_names)

gau-nernst

from torch import nn

class SeparableConv2d(nn.Sequential):
    def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, padding=1, dilation=1, norm_layer=None, activation=None):
        super().__init__()
        if norm_layer is None:
            norm_layer = nn.BatchNorm2d
        if activation is None:
            activation = nn.ReLU6