XJDKC edited a comment on pull request #697:
URL: https://github.com/apache/singa/pull/697#issuecomment-633222142
Sorry, the example above is just to show how to create a layer, so I don't
consider using the latest APIs. And there are no direct params in Model. If we
let users override set_params/get_params，the code for every layer is quite
similar.
```Python
def get_params(self):
self.param_names = ['W', 'b']
super(LayerName, self).get_params()
def set_params(self, **params):
self.param_names = ['W', 'b']
super(LayerName, self).set_params()
```
So if users declare the names of params and states in \_\_init\_\_, we can
handle them well and users just need to override three functions(\_\_init\_\_,
initialize, forward). Another strategy is that we create a subclass of
Tensor(named Param) and use that class to create params. In this way, we can
distinguish params from all member variables.
```Python
# self.W = Tensor(shape=w_shape, requires_grad=True, stores_grad=True)
self.W = Param(shape=w_shape, requires_grad=True, stores_grad=True)
```
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