One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD
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Updated
Jun 3, 2024 - Julia
One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD
Provides compile-time contraction pattern analysis to determine optimal tensor operation to perform.
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
Hyper optimized contraction trees for large tensor networks and einsums
Einsum Expressions in Julia
Rust accelerated contraction ordering primitives for tensor networks and einsums
An implementation of EinsumNetworks in PyTorch.
Stats, linear algebra and einops for xarray
MyPy Type Checking for NumPy/Jax/PyTorch Einsum Operations
einsum via batch matrix multiply
Convolutions and more as einsum for PyTorch
A collection of state-of-the-art contraction ordering algorithms. https://arxiv.org/abs/2209.12332
Memory-efficient optimum einsum using opt_einsum planning and PyTorch kernels.
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