Result for 0493661711D5A740CE23726B51016CE0492A29A2

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/opt_einsum/backends/__pycache__/dispatch.cpython-39.pyc
FileSize3507
MD5263333F11FEB8BA7A640ED441512C7ED
SHA-10493661711D5A740CE23726B51016CE0492A29A2
SHA-256EE1BEA868FB61B461E35818A6C0EBF57C02401EDFABD19C37B8DEED8A22063C7
SSDEEP96:VwuWdOywbUR1PeLkMtYwmhCH5kUHrVV9Z2Q1DP:9yrR5eLkoYwTZV9Z2SDP
TLSHT1217187F3A2866675FD77F5F8752A0721C32C577F1B2D840BB40692661E06384683D6CC
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5F119898EA46EB4FDC77A85726360152E
PackageArchnoarch
PackageDescriptionOptimized 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. See the [**documentation**](http://optimized-einsum.readthedocs.io) for more information.
PackageNamepython39-opt-einsum
PackageRelease2.1
PackageVersion3.3.0
SHA-15277513FEDCEED387FBE66D283B02E23FABCB577
SHA-256F5209F8257294FF884575429B524C9185DE82AA496FDEB60695D3ACE28863AC3
Key Value
MD587600B2D04C9EED4EE94DAEA782A6F77
PackageArchnoarch
PackageDescriptionOptimized 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. See the [**documentation**](http://optimized-einsum.readthedocs.io) for more information.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython39-opt-einsum
PackageRelease2.3
PackageVersion3.3.0
SHA-1020EE7C83F7F8158E12F0FB364BA780C2EB92933
SHA-25699DB37F55811B12AB5A277CC28CE9FF4AA828F12981791F3FA4987B4697E04F9