Please help me with understanding of 04_modern_net.py

[ruzrobert]

Hello!
@nlintz , your TensorFlow tutorials are very good, and they are also compact, comparing to other Tutorials/Examples on github.

But I need some help with understanding of 4 modern net.
Please help me understand these lines:

30 line: w_h = init_weights([784, 625])
So, 784 is 28x28, which is flatten image data array.
But what is 625 ?
We also have next line: w_h2 = init_weights([625, 625])
Is 625 something related to batches/hidden layer units ?

47 line: for i in range(100):
What is 100 in that line? Is that epoches count ?

48 line: for start, end in zip(range(0, len(trX), 128), range(128, len(trX)+1, 128)):
Cannot understand how that is working at all. Could you please explain what we are doing here?
Is that 128 - batch size ?
What range of mnist.train.images we are taking? All 55k ?

Thank you!

I hope to get an answer

[ruzrobert]

Okay, so I figured out, that for
2. yes, it is epoches count
3. yes, 128 is batch size, and range is length of trX, which is 55 000.

But I still don't know what 625 in the first question is. And thoughts?
Hidden layer connection count / units count ?

[hunkim]

625 is something arbitrary.

w_h = init_weights([784, XXX]) #784 input
w_h2 = init_weights([XXX, YYY])
w_h3 = init_weights([YYY, ZZZ])
w_h4 = init_weights([ZZZ, 1]) # one output

The input and output are fixed, but others are your hyperparameters.

[ruzrobert]

Okay, so looks like this is something like hidden layer units count. Thank you!