While I'm training I'am adding new things attempting don't spoil the training. Now I can set any layer to be used as input or output and continue receiving or sending by TCP. Also I can create new layers, connect them...
Now I'm showing the inference for all channels when learning is on. 5 experiences inyected at same time (*2= batch of 10).
Right black margin is the getted error for each channel (not appreciable because error is low)
on this only one channel is used to perform single inference. The other channels is showing some output but is because is receiving from bias neuron
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UPDATE:
Now I have seen the other channels didn't get the error and them batch is a ̶f̶. Fixed up too
and seeing this last one I have seen another big problem now fixed too :)
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