Julius Kunze

You can already use`random_key()` within `@parametrized`: ```python @parametrized def dropout(inputs): keep_rate = 1 - rate keep = random.bernoulli(random_key(), keep_rate, inputs.shape) return np.where(keep, inputs / keep_rate, 0) ``` An independent `seed`...

Hey! You can download it from https://clarin.phonetik.uni-muenchen.de/BASRepository/, but (if I remember correctly) you have to register/login to the website first.

Hi @sruteesh, thank you! ASG is not supported, but an implementation can be plugged in at https://github.com/JuliusKunze/speechless/blob/master/speechless/net.py#L397.

@jakevdp I hadn't yet (probably should have), thanks for doing this, very interesting! How would you explain this behavior, i. e. is branching optimized out during compilation or just dirt-cheap?...