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Make API more easy to use by following python's syntax. #76
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I personally believe that we should stay closer to C# conventions instead of exactly mirroring the python API. The goal of the project is in fact to provide a way for C# users to run and build deep learning models through PyTorch, and not the other way around (i.e., PyTorch users that want to use C# instead of python). For instance I have several problems with this:
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We could reactive the KerasSharp, wrap the TorchSharp and TensorFlow.NET or TensorFlowSharp, ML.NET and CNTK. |
This could be a good option! I also like the idea of using Keras API on top of ML.NET (how does that work?) |
@interesaaat The author of KerasSharp doesn't response cesarsouza/keras-sharp#29 . |
A similar project like keras sharp with multiple backends. I can try to include torchsharp soon. |
@deepakkumar1984 Could you add TensorFlow.NET as a backend? |
I can add it as a variation to Tensorflow implementation. Already using
Tensorflowsharp but I can this library as well and rest upto the user to
use specific backend.
…On Tue, Mar 26, 2019 at 2:56 PM Haiping ***@***.***> wrote:
@deepakkumar1984 <https://github.com/deepakkumar1984> Could you add
TensorFlow.NET <https://github.com/SciSharp/TensorFlow.NET> as a backend?
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Regards,
Deepak
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Refer this thread, you will know how valuable it is. The most important is TensorFlow.NET can Build Graph -> Train -> Inference model in one library. @deepakkumar1984 |
Does it support CUDA?
…On Tue, Mar 26, 2019 at 3:15 PM Haiping ***@***.***> wrote:
Refer this thread <SciSharp/TensorFlow.NET#180>,
you will know how valuable it is. The most important is TensorFlow.NET can
Build Graph -> Train -> Inference model in one library. @deepakkumar1984
<https://github.com/deepakkumar1984>
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Deepak
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Sure, cross-platform, run in CUDA. |
This seems to be a recurring issue with libraries ported from other languages to .NET - what naming convention to use for the API? There are two schools of thought:
Both of these schools of thought are equally valid, but of course they conflict with each other. I think school of thought 1 is best for the early stages of the library, getting started, etc... but I think long term 2 is the best. Supporting both in parallel would be ideal though. It would be nice if there were some automated way to generate a .NET convention version of the API surface in parallel to the Python-style API. As an aside, it's interesting to me that F# uses a naming convention more like Python (for historical reasons, given F# is based on the ML family of languages), but only for private methods within an implementation and for the F# standard library. Even for F# facing libraries written in F#, the recommended conventions for public facing APIs is to use the .NET convention, though that seems to be inconsistently followed in the wild. |
Just to note that if I was starting this repo from scratch, I would make it part of SciSharp, and follow SciSharp's naming conventions (i.e. use PyTorch Python naming conventions) But for now we will stick to the naming conventions we have here |
I'm closing this as it's covered by #95 |
Is it possible change the high level API like what SciSharp's done? Check the README: https://github.com/SciSharp/TensorFlow.NET.
For example:
Will be
Mirror API first would make progress be faster that move ML model to .NET world. Project will be done faster than ML.NET. @migueldeicaza When most of the thing runs well, we can refactor code that be more .NET conventions.
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