[GitHub] [singa] nudles commented on pull request #688: Autograd refactor

[GitBox <gi...@apache.org>]

nudles commented on pull request #688:
URL: https://github.com/apache/singa/pull/688#issuecomment-623231858


   > 
   > 
   > changes:
   > 
   >     1. an example of make `class Xxx(Operation)` to private `class _Xxx(Operation)`. Because `class Operation` should be only for internal. For the term `Operation` in the user space, it should be the operation functions `def xxx(x):...`. Also these operation function should be used by the user
   > 
   >     2. fix bug for `set_param` when given Tensor as params
   > 
   >     3. Modified `Linear` constructor to `(self,out_features, in_features=None, bias=True):`. `out_features` comes first, leaving `in_features` as optional. When `Linear` is constructed with only `out_features`, it's params, `W` and `b`, are not initialized. After `set_params` or `forward`/`__call__`,  it's params, `W` and `b`, are initialized.
   
   For the last point, it will break the compatibility.. 
   there are two solutions
   1. use *args and **kwargs
   2. assume the old code passes (in_features, out_features, bias=True) and the new code passes (out_features, bias=True), then we check if in_features is None or not to decide the argument order. 
   
   In V4, we can update the API completely. 


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