Optimized einsum can significantly reduce the overall execution time of einsum-like expressions (e.g., np.einsum, dask.array.einsum, pytorch.einsum, tensorflow.einsum) by optimizing the expression's contraction order and dispatching many operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch, Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially any library which conforms to a standard API.
Optimized einsum can significantly reduce the overall execution time of einsum-like expressions (e.g., np.einsum, dask.array.einsum, pytorch.einsum, tensorflow.einsum) by optimizing the expression's contraction order and dispatching many operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch, Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially any library which conforms to a standard API.
To install py310-opt_einsum, run the following command in macOS terminal (Applications->Utilities->Terminal)
sudo port install py310-opt_einsum
To see what files were installed by py310-opt_einsum, run:
port contents py310-opt_einsum
To later upgrade py310-opt_einsum, run:
sudo port selfupdate && sudo port upgrade py310-opt_einsum
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