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I have made a very simple neat-python for XOR. This is the summary of the genome. Best genome: Key: 141 Fitness: 2.993003425787766 Nodes: 0 DefaultNodeGene(key=0, bias=-0.8080802310263379, response=1.0, activation=sigmoid, aggregation=sum) Connections: DefaultConnectionGene(key=(-2, 0), weight=1.5655941592328844, enabled=True) DefaultConnectionGene(key=(-1, 0), weight=1.2986799185483175, enabled=True However when I try to calculate it, it does not really make sense. These are the results of a evaluation: input (0.0, 0.0), expected output (0.0,),...

For some reason my training set is not showing as a matplotlib graph, I am using the torchvision dataset MNIST. Sorry if my code is not the most efficient, just starting pytorch. The code is running without any errors however the graph of data won't be shown. I tried doing the .view() to reshape the data shape from a (1, 28, 28) to a...