dreamer-pytorch
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A small question of implementation
Thank you for your sharing, but I have a small question. Why do you 1) use F.softplus
for variance(std_dev)
every time and 2) add a constant(min_std_dev). Is it to ensure that the square of variance is positive? If so, why not use Relu
? (click here 1, click here 2)
Example as follows:
prior_std_devs[t + 1] = F.softplus(_prior_std_dev) + self.min_std_dev
Looking forward to your reply.