코드 분석

https://www.notion.so/code-7f2c7ae86b8649ef8812686c8b6e5e61

pruning

• utils.py
  • get_weight_threshold(model, rate, args)
  • weight_prune(model, threshold, args)
  • get_filter_mask(model, rate, args)
  • filter_prune(model, filter_mask)
  • cal_sparsity(model)

dpf (dynamic pruning with feedback)

• __init__.py
• mnn.py
  • Masker(torch.autograd.Function)
    • forward(ctx, x, mask)
    • backward(ctx, grad)
  • MaskConv2d(nn.Conv2d)
    • init(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros')
    • forward(self, input)

models (default ResNet)

• __init__.py
• resnet_mask.py
  • BasicBlock(nn.Module)
    • __init__(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm_layer=None)
    • forward(self, x)
  • Bottleneck(nn.Module)
    • __init__(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm_layer=None)
    • forward(self, x)
• ResNet(nn.Module)
  • __init__(self, block, layers, num_classes=1000, zero_init_residual=False, groups=1, width_per_group=64, replace_stride_with_dilation=None, norm_layer=None)
  • _make_layer(self, block, planes, blocks, stride=1, dilate=False)
  • _forward_impl(self, x)
  • forward(self, x) : _forward_impl(x) 실행
• ResNet_CIFAR(nn.Module)
  • __init__(self, block, layers, num_classes=10, zero_init_residual=False, groups=1, width_per_group=64, replace_stride_with_dilation=None, norm_layer=None)
  • _make_layer(self, block, planes, blocks, stride=1, dilate=False)
  • _forward_impl(self, x)
  • forward(self, x) : _forward_impl(x) 실행
• conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1)
• conv1x1(in_planes, out_planes, stride=1)
• resnet(data='cifar10', **kwargs) : data 따라 모델 다르게 설정해서 모델 반환