leezu commented on a change in pull request #20262:
URL: https://github.com/apache/incubator-mxnet/pull/20262#discussion_r647241837



##########
File path: 
docs/python_docs/python/tutorials/packages/gluon/blocks/custom-layer.md
##########
@@ -131,50 +128,47 @@ Output:
  [-0.05046433]
  [-1.2375476 ]
  [-0.15506986]]
-<NDArray 5x1 @cpu(0)>
 ```
 
 
 ## Parameters of a custom layer
 
 Usually, a layer has a set of associated parameters, sometimes also referred 
as weights. This is an internal state of a layer. Most often, these parameters 
are the ones, that we want to learn during backpropogation step, but sometimes 
these parameters might be just constants we want to use during forward pass.
 
-All parameters of a block are stored and accessed via 
[ParameterDict](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/parameter.py#L508)
 class. This class helps with initialization, updating, saving and loading of 
the parameters. Each layer can have multiple set of parameters, and all of them 
can be stored in a single instance of the `ParameterDict` class. On a block 
level, the instance of the `ParameterDict` class is accessible via 
`self.params` field, and outside of a block one can access all parameters of 
the network via 
[collect_params()](https://mxnet.apache.org/api/python/gluon/gluon.html#mxnet.gluon.Block.collect_params)
 method called on a `container`. `ParameterDict` uses 
[Parameter](https://mxnet.apache.org/api/python/gluon/gluon.html#mxnet.gluon.Parameter)
 class to represent parameters inside of Apache MxNet neural network. If 
parameter doesn't exist, trying to get a parameter via `self.params` will 
create it automatically.
+All parameters of a block are stored and accessed via 
[ParameterDict](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/parameter.py#L508)
 class. This class helps with initialization, updating, saving and loading of 
the parameters. Each layer can have multiple set of parameters, and all of them 
can be stored in a single instance of the `ParameterDict` class. On a block 
level, the instance of the `ParameterDict` class is accessible via 
`self.params` field, and outside of a block one can access all parameters of 
the network via 
[collect_params()](https://mxnet.apache.org/api/python/gluon/gluon.html#mxnet.gluon.Block.collect_params)
 method called on a `container`. `ParameterDict` uses 
[Parameter](https://mxnet.apache.org/api/python/gluon/gluon.html#mxnet.gluon.Parameter)
 class to represent parameters inside of Apache MxNet neural network.

Review comment:
       Good catch. Let's remove the reference to ParameterDict and call it a 
`dict` of Parameters. It's also an option to use the 
https://docs.python.org/3/library/typing.html syntax to describe the type.




-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

For queries about this service, please contact Infrastructure at:
[email protected]


Reply via email to