Result for 000CA523E59D31DF108246969A72EBC1C31C3288

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/caffe2/python/operator_test/__pycache__/sparse_lengths_sum_benchmark.cpython-38.opt-1.pyc
FileSize3303
MD55E48677B0FBBC722721B95E7D1092287
SHA-1000CA523E59D31DF108246969A72EBC1C31C3288
SHA-256BC1E8737EC103381BE371BD4E021E0F633610951F9C1109089A88B666F90D59C
SSDEEP96:V3RgEnt+tBPQeRgncnmzaUCaFVpPMH1YJpN+2xmWXqPwIDYQ:VhgEnaoeRgncnEaUCajUYJa2xmhpn
TLSHT1A061C7590F00F02EF52FFFB95C9F02309A724558A3161A827D08A2B5DC81F5F2B7A609
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD591D42436C11A9C545E383823EC6E575D
PackageArchx86_64
PackageDescriptionPyTorch enables fast, flexible experimentation and efficient production through a hybrid front-end, distributed training, and ecosystem of tools and libraries. The library is developed by Facebook and other groups. PyTorch provides two high-level features: * Tensor computing (like NumPy) with strong acceleration via graphics * processing units (GPU) Deep neural networks built on a tape-based autodiff system
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython38-torch
PackageRelease6.3
PackageVersion1.5.1
SHA-12DCBCC0643BC260D886A69975796021438020D3B
SHA-256049F5F9511BF52C61E15446761DF5E17B192C8984542B5A71D457E5627B4D221