why f = 6 in cnnmnist.py?

[cyckun]

Hi, I'm leaning mpyc, in demo cnnmnist.py, the para f=6, and force python integer to secnum,
scale = lambda a: secnum(int(round(a * f))) # force Python integers;
why f is set to 6? I test f = 1, 2, the demo also work fine.

[lschoe]

Yeah, indeed, the demo will still work in many cases, but the error rate will go up overall if you take small values for f.

The variable f controls the precision used for the CNN parameters (neuron weights and bias for all layers) of the trained network. For f=6 we get the minimum error rate for the MNIST dataset (around 9915 out of 10000 correct). For f=4 the error rate will also be below 1%, but for f=2 the error rate will be around 25% and for f=1 it should be really high.

To see this, it's best if you run the demo with a (random) batch of say 25 samples, like this:

`python cnnmnist.py 25`

This will also run faster than 25 individual runs because some of the costs are amortized (like loading and converting the weights of the trained network, especially for layer 3 which has 12 MB of weights, see mpyc/demos/data/cnn).

Now you should see more errors for f=2 and certainly for f=1?

[cyckun]

Oh, I got it, Thanks for your reply, @lschoe.