zhanghang1989 / zhanghang1989/PyTorch-Encoding
About replace in ReLU and Dropout
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- Python
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Description
I noticed that a lot of your code is written like this
nn.ReLU(True),
nn.Dropout(0.1, False),
why you use inplace operator in activation fuction but not in dropout? Does this have any special meaning?
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- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
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Research direction
Start by reading the Python entry points shown in the issue, nn.ReLU and nn.Dropout, and compare their documented arguments and uses in the repository. Done means documenting the distinction between the two boolean arguments and explaining whether their differing values have special meaning.
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Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100