igul222/improved_wgan_training

interpolates in wgan-gp

Willjay90 opened this issue · 1 comments

Willjay90 commented

I'm following Algorithm 1 in the paper with MNIST dataset.

x ̃ ← G θ ( z )
xˆ ← εx + (1 − ε)x ̃

However, in the code, it shows

differences = fake_data - real_data
interpolates = real_data + (alpha*differences)
             = read_data + alpha*(fake_data - real_data) 
             = alpha * fake_data + (1-alpha) * real_data

why?

pierremac commented

Well, set alpha = 1 - epsilon and I guess you get the result!
And as alpha is set to be sampled uniformly at random between 0 and 1, so is epsilon.

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