Result for 0065C4203618C54401F3132411B75B7667CF113C

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/caffe2/python/operator_test/__pycache__/index_hash_ops_test.cpython-38.pyc
FileSize2896
MD5DD6494D2F87549B37325CE1D1EC40E7C
SHA-10065C4203618C54401F3132411B75B7667CF113C
SHA-2562776AA1E06EB9BA0E9917E05E8FD3911D76C421761B2A83ED551A2C17234618A
SSDEEP48:WZ1mld5sE5dZASL0yOQ2MPDwTvLOxkjOeyRYXmB4gRTfFimwi3T1l6W:ZXHsyOmkLOSyRY21RTfFvRL6W
TLSHT1DB51E6D9D44A6E2AFB24F1FC81BE1F6644389A8E0A8500470F70557E8D617C4AA7DF7C
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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