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      "description": "Optimized einsum can significantly reduce the overall execution time of einsum-like expressions (e.g.,\n[`np.einsum`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.einsum.html),\n[`dask.array.einsum`](https://docs.dask.org/en/latest/array-api.html#dask.array.einsum),\n[`pytorch.einsum`](https://pytorch.org/docs/stable/torch.html#torch.einsum),\n[`tensorflow.einsum`](https://www.tensorflow.org/api_docs/python/tf/einsum),\n)\nby optimizing the expression's contraction order and dispatching many\noperations to canonical BLAS, cuBLAS, or other specialized routines. Optimized\neinsum is agnostic to the backend and can handle NumPy, Dask, PyTorch,\nTensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially\nany library which conforms to a standard API. See the\n[**documentation**](http://optimized-einsum.readthedocs.io) for more\ninformation.",
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