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# Tensor.NET
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Tensor.NET is a lightweight and high-performance tensor library which provides numpy-like operations but .NET style interfaces. It supports generic tensor, Linq, C# native slices and so on. It is young so that it may may lack some features or have some BUGs. Please tell us on github or via email, thank you!
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## Why using Tensor.NET
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Currently, there has been some repositories to support tensor operation, providing numpy-like interfaces, such as [NumSharp](https://github.com/SciSharp/NumSharp) and [TensorFlow.NET](https://github.com/SciSharp/TensorFlow.NET). I also learned a lot from them and thanks for the authors of the two repositories sincerely!
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- Support reading and writing tensor from image, excel, csv and other more formats.
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## API map from Numpy to Tensor.NET
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## API map from Numpy to Tensor.NET (WIP)
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```Tensor.NET``` implements the main features of ```Numpy```. The mapping from Numpy API to Tensor.NET API could be found [here](./doc/API_Mapping.md).
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For how to build from source, please refer to [this doc](./doc/Build.md)
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For how to use, please refer to [the user guide]()
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For how to use, please refer to [the user guide]() (WIP)
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For examples, please refer to [this repository]()
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## Benchmarks
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## Benchmarks (WIP)
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Benchmarks will be privided later.
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varamin=src.Argmin(1);
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```
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## The main shortcoming
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## The major shortcoming
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Despite the advantages above, ```Tensor.NET``` does have some shortcomings, the main shortcoming is its basic arithment with operator ```+ - % /```.
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Since ```Tensor.NET``` use generic class in its design and operations between tensors of different types are supposed, there's no way to provide these operators in .NET 6 and C# 10 except the operations between tensors of the same data type. For tensors with different data types, ```Add, Sub, Mod, Div``` methods are provided. However, still, there will be some inconvinience.
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This problem is supposed to be solved in .NET 7 with its new features. Thanks for the using and waiting!
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This problem is supposed to be solved in .NET 7 with its new features. Thanks for the using and waiting!
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