jiangjiajun commented on pull request #9126:
URL: https://github.com/apache/tvm/pull/9126#issuecomment-933273751


   > Coming together well. I think I am ok with merging this in the current 
state as part of a more experimental frontend, but would like another pair of 
eyes on this.
   > 
   > Still a few comments which will make this better:
   > 
   > 1. Can you add more substantial test cases to your tests? E.g. different 
input shapes and those of different ranks at least for some of the relevant 
ops. I feel that some issues might come to light from this. Do not worry about 
PR size anymore
   > 2. Please add type annotations to functions for this and future PRs. e.g.
   > 
   > def myFunc(a: int, b: List[string]) -> None: ...
   
   - More cases have been added in tests, but only for the new operators in 
this pull request. I will send another pull request for the previous operators.
   - Type annotation is a good code habit, but for the function like 
`convert_dot(g : GraphProto, op : paddle.fluid.framework.operators, block: 
paddle.fluid.framework.Block)`, the type annotation will bring dependency of 
paddlepaddle for TVM, I noticed that all the frontends putting framework 
importing in `from_xxx` function to avoid strong dependency for TVM.


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