Tangent Alternatives

Similar projects and alternatives to tangent based on common topics and language

julia

350 44,510 10.0 Julia tangent VS julia

The Julia Programming Language
dex-lang

25 1,534 8.8 Haskell tangent VS dex-lang

Research language for array processing in the Haskell/ML family
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Enzyme

16 1,153 9.6 LLVM tangent VS Enzyme

High-performance automatic differentiation of LLVM and MLIR. (by EnzymeAD)
autograd

6 6,787 6.0 Python tangent VS autograd

Efficiently computes derivatives of numpy code.
kotlingrad

3 508 3.8 Kotlin tangent VS kotlingrad

🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types
SmallPebble

6 112 0.0 Python tangent VS SmallPebble

Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
pennylane

1 2,106 9.8 Python tangent VS pennylane

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better tangent alternative or higher similarity.

Suggest an alternative to tangent

tangent reviews and mentions

Posts with mentions or reviews of tangent. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-25.

[D] How AD is implemented in JAX/Tensorflow/Pytorch?
1 project | /r/MachineLearning | 25 Dec 2021

Thank you so much for the detail explaination! This remind me of tangent, an abandoned (?) SCT built by google couple of years ago. https://github.com/google/tangent
Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
7 projects | news.ycombinator.com | 25 Dec 2021

No, autograd acts similarly to PyTorch in that it builds a tape that it reverses while PyTorch just comes with more optimized kernels (and kernels that act on GPUs). The AD that I was referencing was tangent (https://github.com/google/tangent). It was an interesting project but it's hard to see who the audience is. Generating Python source code makes things harder to analyze, and you cannot JIT compile the generated code unless you could JIT compile Python. So you might as well first trace to a JIT-compliable sublanguage and do the actions there, which is precisely what Jax does. In theory tangent is a bit more general, and maybe you could mix it with Numba, but then it's hard to justify. If it's more general then it's not for the standard ML community for the same reason as the Julia tools, but then it better do better than the Julia tools in the specific niche that they are targeting. Jax just makes much more sense for the people who were building it, it chose its niche very well.