Result for 6CD0E74C34AD9EE40221E3B41B8812101A3708A7

Query result

Key Value
FileNameusr/lib/python3.12/site-packages/opt_einsum/backends/dispatch.py
FileSize4420
MD5F6C97A2BFA6D2DD0EC8CAE7140747316
SHA-16CD0E74C34AD9EE40221E3B41B8812101A3708A7
SHA-2568930D14035B2CB757D1717423A4801513AD1F5A402CC2856BA2FC71D3F676DDC
SHA-512503263609A9AB99572F935E07CBDA45EF9936BBC22602355A076507549C29A6A1DCA2BD55078E34B6171C9B79BE9106DDB58E955FDBEBFA0D40074CC6D7BE2A8
SSDEEP96:SMKNhV1dPeVknmthEpa4fHPQkBaF0rBeaO0WPo:S3bHPeVkKhkvNaFweaxWPo
TLSHT113914077E79B58765F31D5C6753642A1CB3C084F3E053024B8ED81E21FA211E8AB85AC
insert-timestamp1728248935.2988455
mimetypetext/plain
sourcesnap:XSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_936
tar:gnameroot
tar:unameroot
hashlookup:parent-total43
hashlookup:trust100

Network graph view

Parents (Total: 43)

The searched file hash is included in 43 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
SHA-101094331C315996BD9740D19E85E15A36C1C2286
snap-authoritycanonical
snap-filenameXSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_695.snap
snap-idXSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_695
snap-nameroot-framework
snap-publisher-idVoUAJzdpg1T1K8hp70EmA7f7dJkxb7BA
snap-signkeyBWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul
snap-timestamp2020-11-27T06:22:05.033990Z
source-urlhttps://api.snapcraft.io/api/v1/snaps/download/XSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_695.snap
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
SHA-10BD43A023CD2ABA0D757FE61CEADD4FD43C8C403
snap-authoritycanonical
snap-filenameXSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_620.snap
snap-idXSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_620
snap-nameroot-framework
snap-publisher-idVoUAJzdpg1T1K8hp70EmA7f7dJkxb7BA
snap-signkeyBWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul
snap-timestamp2020-11-27T06:22:05.033990Z
source-urlhttps://api.snapcraft.io/api/v1/snaps/download/XSlaE4S2cu0h5r6o7dFaFiQIsugKLFpa_620.snap
Key Value
SHA-10D1449986F6E37C3B72DB99134F8BB709C2242BD
snap-authoritycanonical
snap-filenamejtBG52gsnZJLjq3VteGFOyMnEqtHAWAs_535.snap
snap-idjtBG52gsnZJLjq3VteGFOyMnEqtHAWAs_535
snap-nameweebl-tools
snap-publisher-idG1rqdx35XwIQVfWVmEqirmnuYKCXHT66
snap-signkeyBWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul
snap-timestamp2019-07-31T16:57:59.595562Z
source-urlhttps://api.snapcraft.io/api/v1/snaps/download/jtBG52gsnZJLjq3VteGFOyMnEqtHAWAs_535.snap
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
FileNamehttp://dl-cdn.alpinelinux.org/alpine/latest-stable//community//s390x//py3-opt_einsum-3.3.0-r1.apk
MD5A617D78ECDF4D84B172F9D1AA64481BB
SHA-1194C3E31DD50354E62EADC2D937B023009ABFD3E
SHA-256048B5BAFFD266152F7FAFFF1DF09D6CBA9C795111F7FF4ADD1A40DFBCFDDA48C
SSDEEP768:YLuDPIdRMFeI6EyFCCjiEf5XIRZ+xp02NNs4GEqEcdz6yI2eOn5dapxghX02CTlR:+uLIdRcifiExYZn9EtEaGdap6LySaBQK
TLSHT14A23F249E0A9F21DED1CCAE462ACF045EDAE70A58D61765D034CDA7F9A2D2E3E0035CD
Key Value
FileNamehttp://dl-cdn.alpinelinux.org/alpine/latest-stable//community//s390x//py3-opt_einsum-3.3.0-r2.apk
MD5B5CC54FC915487C2205B07550AE93597
SHA-119D16F3586BB60FBE626C59876F63836C7B99FBA
SHA-2566C5C2F92A9C9BD60611BFCD64E81BD082747DC57F35C018BB87F720C4E1D6BC0
SSDEEP768:Yx1BgkSL5bXE4Xx7RsoqmLXdfrnwLP5B2ld/Ot0ue4CB2lW7fWLGBIFGoMhh43vR:ygzXRBkT23GO5zWKmFGnad/xRwuB
TLSHT10C23F1376764D09C351FD2DFA38ADE71C865B5F70F91199A4684238B298AC03BED3920
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