Calculating gradients for partial graph #7269
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JiayiFeng
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Jan 8, 2018
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| def calc_gradient(targets, inputs, target_gradients=None, no_grad_set=None): |
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I have a few questions about the calc_gradient:
- It seems that this API appends partial backward to calculate gradients of
targetstoinputs. Can this API be used by users directly? And when will users use it? - Here are some special handlings(like
_rename_grad_) to make sure this API can be invoked for multiple times. However, in each invoking theprogramitself will be changed(some backward ops are appended). So during the second invoke, the backward part generated in the first time is still in the program and is regarded as forwarding part. Is this reasonable?
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- Yes. Some algorithm have its own way of calculating gradients. One example is Learning to learn by gradient descent by gradient descent.
- Yes. This happens in cases where gradients from different parts needs to be combined in some way to calculate the final result.
added 3 commits
January 9, 2018 18:21
Added backward.calc_gradient to backpropagate gradient from given targets to inputs.
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Added backward.calc_gradient to backpropagate gradient from given targets to inputs.