TorchSharp
beartype
TorchSharp | beartype | |
---|---|---|
5 | 18 | |
1,271 | 2,468 | |
2.8% | 1.9% | |
9.5 | 9.4 | |
5 days ago | 4 days ago | |
C# | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TorchSharp
- AI .NET
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Machine learning with NET
There exist TorchSharp that is a С# wrapper around the same libtorch.dll that is wrapped by Python code in PyTorch, https://github.com/dotnet/TorchSharp. Though I don't know how exhaustive it is.
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When the client's management is happy but their dev team is a pain
https://github.com/dotnet/TorchSharp here you go.
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Does anyone actually use ML.NET?
With TorchSharp, you have access to libtorch in .NET, the library that powers PyTorch. This is what's currently backing the Text Classification API
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.NET Core
In Artificial Intelligence Series-Overview
TorchSharp is a .NET library that provides access to libraries that support PyTorch. (Github https://github.com/xamarin/TorchSharp)
beartype
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Writing Python Like Rust
https://github.com/beartype/beartype
I wish more people started using Beartype, it makes Python bearable
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ChatGPT Git Hook Writes Your Commit Messages
I saw this on /r/Python the other day...
- When the client's management is happy but their dev team is a pain
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Returning to snake's nest after a long journey, any major advances in python for science ?
As other folks have commented, type hints are now a big deal. For static typing the best checker is pyright. For runtime checking there is typeguard and beartype. These can be integrated with array libraries through jaxtyping. (Which also works for PyTorch/numpy/etc., despite the name.)
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What are some features you wish Python had?
Maybe you're looking for https://github.com/beartype/beartype for runtime type enforcement; it's only at function calls, though, but probably a decent solution for codebases that are not completely typed for MyPy or pyright.
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svg.py: Type-safe and powerful Python library to generate SVG files
It is though, if you add a type checker to your pipeline and use it without any escape hatches such as `Any` or `type: ignore`, you are essentially making the promise that your code is statically typed. But I say it is a matter of perspective because in my opinion runtime type checking should be avoided if we can get away with statically typed code, but there are type checkers that perform runtime type checking via annotations such as [Beartype](https://github.com/beartype/beartype) (with some trickery like assuming homogenous data structures as to not have to check every element of every structure). Anyway the definition of "type safe" is not 100% even in compiled languages.
- Python’s “Type Hints” are a bit of a disappointment to me
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What's the best practice to validate parameter types at runtime in Python, with and without a third-party module?
There is the beartype project.
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Statically typed Python
Personally I find working around mypy's quirks to be more effort than it's worth, so to offer another option: typeguard or beartype can be used to perform run-time type checking.
- Beartype: Unbearably fast runtime type checking in Python
What are some alternatives?
TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
typeguard - Run-time type checker for Python
NumSharp - High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
pydantic - Data validation using Python type hints
TensorFlowSharp - TensorFlow API for .NET languages
mypy - Optional static typing for Python
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
mypyc - Compile type annotated Python to fast C extensions
DotMLBooks
toit - Program your microcontrollers in a fast and robust high-level language.
nerfstudio - A collaboration friendly studio for NeRFs
benchmarks - Some benchmarks of different languages