deepakkumar1984 / MxNet.Sharp

.NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. https://mxnet.tech-quantum.com/

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The BostonHousing Regression example cannot be compiled

evo11x opened this issue · comments

The BostonHousing Regression example cannot be compiled with MXNet.Sharp 1.5.2
Can I compile it with the current mxnet source from github ?

Thank you, but that example also does not work with the 1.5.2 from NuGet
https://www.nuget.org/packages/MxNet.Sharp
it's not the same as https://github.com/deepakkumar1984/MxNet.Sharp/tree/v1.5.2.0 ?

MxNet.NN cannot be found

Error CS0234 The type or namespace name 'NN' does not exist in the namespace 'MxNet' (are you missing an assembly reference?)

error CS1503: Argument 1: cannot convert from 'int' to 'MxNet.Symbol'
error CS0117: 'ActivationType' does not contain a definition for 'ReLU'
error CS1061: 'Module' does not contain a definition for 'Add' and no accessible extension method 'Add' accepting a first argument of type 'Module' could be found (are you missing a using directive or an assembly reference?)
error CS0103: The name 'LossType' does not exist in the current context

the Gluon logistic regression example works

My work with MxNet is experimental so I can use a pre-release if you want me to help you with the issues

I am a Windows C++ developer since 1996, with some C# experience about 4 years, but I have zero experience with python/numpy and minimal with github.
I need a C# deep learning api like this which supports CUDA 11 (RTX3060) to implement it in one of my C# projects, for the start I also can use the CPU.
I have tried CNTK but it does not work with CUDA 11 and is a discontinued project, tensorflow is too much python and java oriented so I believe MxNet would be a better choice. I would be glad to contribute with something which I know.

No worries, give me 1-2 week of timeframe to publish the preview version. Will make sure the examples are running.