dgasmith / opt_einsumLinks
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
☆940Updated 3 months ago
Alternatives and similar repositories for opt_einsum
Users that are interested in opt_einsum are comparing it to the libraries listed below
Sorting:
- KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows☆1,133Updated last month
- Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python☆496Updated 2 weeks ago
- Extending JAX with custom C++ and CUDA code☆400Updated last year
- functorch is JAX-like composable function transforms for PyTorch.☆1,437Updated last month
- Hardware accelerated, batchable and differentiable optimizers in JAX.☆996Updated 5 months ago
- A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python☆331Updated 11 months ago
- ☆882Updated last month
- PyTorch, TensorFlow, JAX and NumPy — all of them natively using the same code☆695Updated 2 years ago
- Python 3.8+ toolbox for submitting jobs to Slurm☆1,512Updated 4 months ago
- A pedagogical implementation of Autograd☆997Updated 5 years ago
- BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.☆590Updated 9 months ago
- NumPy and SciPy on Multi-Node Multi-GPU systems☆934Updated this week
- Constrained optimization toolkit for PyTorch☆698Updated 2 months ago
- Optax is a gradient processing and optimization library for JAX.☆2,022Updated last week
- Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/☆1,539Updated 5 months ago
- OpTree: Optimized PyTree Utilities☆195Updated this week
- Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation☆855Updated 4 months ago
- Turn SymPy expressions into trainable JAX expressions.☆351Updated 5 months ago
- A High Level API for Deep Learning in JAX☆475Updated 2 years ago
- Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX☆207Updated last month
- jax-triton contains integrations between JAX and OpenAI Triton☆424Updated 3 weeks ago
- Manipulate JSON-like data with NumPy-like idioms.☆909Updated this week
- Profiling and inspecting memory in pytorch☆1,071Updated 3 weeks ago
- ☆593Updated last month
- Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/☆2,532Updated last week
- CLU lets you write beautiful training loops in JAX.☆356Updated 3 months ago
- Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/☆470Updated last month
- Mathematical operations for JAX pytrees☆200Updated 9 months ago
- Second Order Optimization and Curvature Estimation with K-FAC in JAX.☆288Updated last week
- Compositional Linear Algebra☆492Updated 2 months ago