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)
![](https://cdn.hackaday.io/images/5595371644280524529.png)
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
![](https://cdn.hackaday.io/images/5247921644280924723.png)
------------------------------------------------------------------------------
UPDATE:
Now I have seen the other channels didn't get the error and them batch is a ̶f̶. Fixed up too
![](https://cdn.hackaday.io/images/1369441644339856141.png)
and seeing this last one I have seen another big problem now fixed too :)
![](https://cdn.hackaday.io/images/8630661644349396854.png)
Discussions
Become a Hackaday.io Member
Create an account to leave a comment. Already have an account? Log In.