# Visualize Convolutional layer of Alexnet

**URL:** <https://discuss.pytorch.org/t/visualize-convolutional-layer-of-alexnet/80679>\
**Category:** vision\
**Created:** [May 11, 2020, 10:26am UTC](https://discuss.pytorch.org/t/visualize-convolutional-layer-of-alexnet/80679 "2020-05-11T10:26:43Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Sania](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/sania/32/12527_2.png) [@Sania](https://discuss.pytorch.org/u/Sania)\
**Post date:** [May 11, 2020, 10:26am UTC](https://discuss.pytorch.org/t/visualize-convolutional-layer-of-alexnet/80679/1 "2020-05-11T10:26:43Z")

</div>

Hello All,  
I am newbie into this field. I was trying to visualize the feature map/activation map of Alexnet.  
I am working on cifar-10 dataset and was trying to visualize the kernels and feature map.

AlexNet(  
(features): Sequential(  
(0): Conv2d(3, 64, kernel\_size=(11, 11), stride=(4, 4), padding=(2, 2))  
(1): ReLU(inplace)  
(2): MaxPool2d(kernel\_size=3, stride=2, padding=0, dilation=1, ceil\_mode=False)  
(3): Conv2d(64, 192, kernel\_size=(5, 5), stride=(1, 1), padding=(2, 2))  
(4): ReLU(inplace)  
(5): MaxPool2d(kernel\_size=3, stride=2, padding=0, dilation=1, ceil\_mode=False)  
(6): Conv2d(192, 384, kernel\_size=(3, 3), stride=(1, 1), padding=(1, 1))  
(7): ReLU(inplace)  
(8): Conv2d(384, 256, kernel\_size=(3, 3), stride=(1, 1), padding=(1, 1))  
(9): ReLU(inplace)  
(10): Conv2d(256, 256, kernel\_size=(3, 3), stride=(1, 1), padding=(1, 1))  
(11): ReLU(inplace)  
(12): MaxPool2d(kernel\_size=3, stride=2, padding=0, dilation=1, ceil\_mode=False)  
)  
(avgpool): AdaptiveAvgPool2d(output\_size=(6, 6))  
(classifier): Sequential(  
(0): Dropout(p=0.5)  
(1): Linear(in\_features=9216, out\_features=4096, bias=True)  
(2): ReLU(inplace)  
(3): Dropout(p=0.5)  
(4): Linear(in\_features=4096, out\_features=2048, bias=True)  
(5): ReLU(inplace)  
(6): Linear(in\_features=2048, out\_features=1024, bias=True)  
(7): ReLU(inplace)  
(8): Linear(in\_features=1024, out\_features=10, bias=True)  
)  
)

I have few questions on visualization.

1. How do I visualize feature map of Alexnet?
2. Is there any supporting code for visualizing the convolutional layers of Alexnet?

Thanks in advance…

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<div class="post-metadata">

**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\
**Post date:** [May 12, 2020, 6:11am UTC](https://discuss.pytorch.org/t/visualize-convolutional-layer-of-alexnet/80679/2 "2020-05-12T06:11:57Z")

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You could use forward hooks to get the activation maps and visualize them as described [here](https://discuss.pytorch.org/t/visualize-feature-map/29597/2). The topic also includes another post to [visualize kernels](https://discuss.pytorch.org/t/visualize-feature-map/29597/4).