Version 1.0!

After a long long time coding and testing, it's time to call it version 1.0! YAY!

Really comprehensive testing has been made. The last batch of testing came from a Generative Adversarial Network Testing that helped to debug a lot.

These are some of the images produces with this testing:

These are the main changes since the last release:

• We have a new convolutional layer type: TNNetConvolutionSharedWeights. Instead of having its own neurons and weights, this convolutional layer uses the same neurons and weights from another existing layer. So, if you need 2 layers with the same neurons, you can add TNNetConvolutionSharedWeights to your network. Why would you need something like this? Maybe, your NN needs to learn the same patterns in different scales (such as big and small dogs are all dogs). You can follow this example.
• Adding FitLoading Example.
• Documentation has been updated: #30 and #33.
• Fixes bugs #35 and #36.
• Added method CountNeurons.
• TNNetDeMaxPool optimization.

There are still open bugs. But this is how life is.

I wish everyone happy pascal coding and to live long and prosper!