Result for 01A36D4B4DBC9DF4AC7FE403C0F50BAED8ED92D2

Query result

Key Value
FileName./usr/share/doc/packages/python3-opt-einsum/README.md
FileSize5358
MD5AC5810693B4BECFE42E07966FD580541
SHA-101A36D4B4DBC9DF4AC7FE403C0F50BAED8ED92D2
SHA-256CD2EAA20852EB9D5480B6314F1FCEF4637539CE8C4E74F0547506E87D2765856
SSDEEP96:DSzkksBpr6Z9zf3aeznxRRfk95GofkZxDcvY3mJ7rduFPTgWGo5LuwbcqgGqdxIf:Dq2CBT9k948kn4g3mLuFP8WGELuwbJ0Y
TLSHT1C7B187FB7BC75F2007464ED025A696F86B27D23C9EFD04068978D17392607B052B72C8
hashlookup:parent-total16
hashlookup:trust100

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Parents (Total: 16)

The searched file hash is included in 16 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD502AC521107A8229E897DC25B0C94C4F0
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.
PackageNamepython3-opt-einsum
PackageReleaselp153.3.4
PackageVersion3.3.0
SHA-100DA61D719889443ABF8567D6D4B874EFEA65930
SHA-2562022490622682BB0726245282C6EF96F4071D6259766D6C7FE0BC5F1ECD237AA
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
Key Value
MD570F635437F076188EDD995A9E481C7AA
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.
PackageNamepython3-opt-einsum
PackageRelease3.3
PackageVersion3.3.0
SHA-11348D56D21BDB7D8815E546AAB0964FD4533554B
SHA-25693AFA0A2D2B6A81872552D03ABA6CE886B035A585B3473694A13C0DF66BC997C
Key Value
MD5BF6C5B00412788CBCFDC9E420E0E652C
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
PackageNamepython310-opt-einsum
PackageRelease2.3
PackageVersion3.3.0
SHA-121293A6AD9894DCE3F346289944DF047FED7E64A
SHA-256AD8BB20A9A9E6188F4BB59CF1713210F3433EDDE77D95103223828CD922C165B
Key Value
MD5C5AC5542AEF1749FCE5D1DEB97E3BF25
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.
PackageNamepython3-opt-einsum
PackageReleaselp152.3.3
PackageVersion3.3.0
SHA-1255228479BF3B8285E848FB28A8CF97BF9FBD6F1
SHA-2561048CE221CFA61EF786ECD05D9DB0C35A152DBF1166D63194588C8930CD08D0D
Key Value
MD5AAB54F380CD5EE8F2EA26C39526CA733
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.
PackageNamepython3-opt-einsum
PackageRelease3.3
PackageVersion3.3.0
SHA-13CD839CA4110BE1E4B97B02F439E5B6922444BD0
SHA-2566DA87A1CEE32EA705D8A9832CDD29DFF4222909FA72A4661F97C00982236160B
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
MD55A94FE8B8A58AA5AA894518F16E457B2
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.
PackageNamepython3-opt-einsum
PackageReleaselp154.3.1
PackageVersion3.3.0
SHA-15CB0A2666B896EBEB64EC806CEE033B2749D09F9
SHA-256F691F4CAE6C347ED867286734660D221F5407DB9A54CF7C117CFFF0C30CB4135
Key Value
MD54C06D0EC1423F12A83653C6960700939
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.
PackageNamepython3-opt-einsum
PackageRelease3.3
PackageVersion3.3.0
SHA-169A09408C1EE3D5AF8D329AE4D65DB1902B63BA8
SHA-256EA5D616940AA453509F7B0DB7D244703D4BB20812B074873720D8E53D687B1ED
Key Value
MD581E6E3B4844B4CA7ECCD6A14126B5257
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.
PackageNamepython3-opt-einsum
PackageRelease3.3
PackageVersion3.3.0
SHA-18CB7BFE40737544DF10EED03F8B5A25E34DC1D20
SHA-256700BA131AE3E6B6FF81A3C32FB6DE94831394CF6984B9895CD45092E1A5D42C8