PyTorchPractice

Pytorch implementation of visulaization of Convolutional Neural Nework weights

Variational Encoder on MNIST

Training and visulization of results of a Variational Auto Encoder based on the example in https://github.com/pytorch/examples/tree/master/vae

Iteration 1	Iteration 24	Iteration 50

CNN Layer weight and output visualization

Plotted filter weights and outputs for a test image of popular pretrained convolutional neural network models ( ResNet, AlexNet) based on example in https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-neural-networks-using-pytorch/ and https://towardsdatascience.com/visualizing-convolution-neural-networks-using-pytorch-3dfa8443e74e

Filter Visualization of Alex Net

Layer 0 (Multi Channel)	Layer 3 (Single Channel)	Layer 6 (single Channel)

First layer weight of ResNet

Test Image for ResNet output

Layer 0 (Multi Channel)	Layer 3 (Single Channel)	Layer 6 (single Channel)