自定义剪枝需要继承 torch.nn.utils.prune.BasePruningMethod 类。三步: 通常情况下,你只需要实现 __init__() 和compute_mask()。 BasePruningMethod 类中的 call(), apply_mask(), apply(), prune(), and remove() 这些方法,通常你都不需要改动。 指定剪枝的类型:structured, unstructured, or global #...
# Using Sequential to create a small model.model = nn.Sequential(nn.Conv2d(1,20,5),nn.ReLU(),nn.Conv2d(20,64,5),nn.ReLU())# Using Sequential with OrderedDict. This is functionally the# same as the above codemodel = nn.Sequential(OrderedDict([('conv1', nn.Conv2d(1,20,5)),('...
torch.nn.utils.clip_grad_norm_ Unsupported. 188 torch.nn.utils.clip_grad_value_ Unsupported. 189 torch.nn.utils.parameters_to_vector Supported 190 torch.nn.utils.vector_to_parameters Supported 197 torch.nn.utils.prune.PruningContainer Supported ...
model = resnet18(pretrained=True).eval() tp.prune_conv_out_channels(model.conv1, idxs=[0,1]) # 剪枝前两个通道 tp.prune_batchnorm_out_channels(model.bn1, idxs=[0,1]) # 尝试修复bn tp.prune_batchnorm_in_channels(model.layer1[0].conv1, idxs=[0,1]) # 尝试修复紧邻的conv output...
Modules and Classes in torch.nn Module Pytorch uses a torch.nn base class which can be used to wrap parameters, functions, and layers in the torch.nn modules. Any deep learning model is developed using the subclass of the torch.nn module it uses method like forward(input) which returns th...
execution_count=88&line=1) pruned_model = YOLO("prune.pt") File [~/.virtualenvs/ashray_dev/lib/python3.10/site-packages/ultralytics/engine/model.py:94](https://file+.vscode-resource.vscode-cdn.net/home/ashi/Documents/projects/~/.virtualenvs/ashray_dev/lib/python3.10/site-packages/...
torch.nn.utils.clip_grad_norm_ Unsupported. 188 torch.nn.utils.clip_grad_value_ Unsupported. 189 torch.nn.utils.parameters_to_vector Supported 190 torch.nn.utils.vector_to_parameters Supported 197 torch.nn.utils.prune.PruningContainer Supported ...
用于处理DenseNet中的局部耦合的情况layer=dep.target.module# 获取 nn.Moduleprune_fn=dep.handler# 获取 剪枝函数# 3. 这里我们简化问题,仅计算卷积输出通道的重要性ifisinstance(layer,nn.Conv2d)andprune_fn==tp.prune_conv_out_channels:w=layer.weight.data[idxs].flatten(1)# 用索引列表获取耦合通道对应...