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How to update weight of pre-trained network (Resnet50) using deep network designer

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hi, i notice that when importing pretrained network using deep network designer the weights of the convolution2dLayer is fixed. Is there any ways for me to update the weight instead of replacing the whole new convolution2dLayer?
The pre-trained network convolution2dLayer
The new convolution2dLayer
Hope someone could enlighten me on this because i try to add another layer on top the original convolutional layer.

Accepted Answer

David Willingham
David Willingham on 22 Jul 2021
Deep Network Designer has no capability of editing Weights directly, this is normally done during the training process.
However it would be great to try and capture your use case, to see if we should consider adding this capability.
Can you elaborate why you'd like to manually replace one layer, and then edit the weights of the network?
Tahir Abbas khan
Tahir Abbas khan on 27 Apr 2022
same issue with me,
Dear, i have use the pretrained model for classification purposes (5 classes),but the accuracy of 3 classes are accurately predicted, but two classes have lower accuracy, when i tried to explore the results of these 2 classes in an other pretrained model,shows better results.. ultimately we need to combined the weights of these two pretrained models or updates the weights of 1st pretrained model of concerned two classes only...hope so, results may improve the overall accuracy by do this....
Thanks & Regards

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