- 'Deep Network Designer' app can be used to adjust layers according to custom requirement.
- Since there is no direct 'reshapeLayer' function avaialble, a similar functionality can be acheived using 'funcionLayer' function. This is also mentioned in this MATLAB Answer: https://www.mathworks.com/matlabcentral/answers/461988-reshape-layer-in-deep-learning. The section of 'Reformat Data Using Function Layer' would provide necessary information.
- Defining a custom class for the output layer, where the 'reshape' function can be used to adjust the shape of the output layer.
How to do reshape in a NN?
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How can I reshape a NN's layer's output? I have a fully connected layer whose output is a 1D vector. I want to reshape it to a 3D matrix and apply convolution layer after it. Say, is there a similar function or something like "reshape layer" in Tensorflow?
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Rahul
2025 年 4 月 7 日
There are multiple ways to approach the issue in MATLAB. The following can be considered:
The following Mathworks documentations can be referred to know more:
'Deep Network Designer': https://www.mathworks.com/help/deeplearning/ref/deepnetworkdesigner-app.html
'Defining custom Deep Learning Layer': https://www.mathworks.com/help/deeplearning/ug/define-custom-deep-learning-layer-with-formatted-inputs.html
Thanks.
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