Result for 0062F897A34948250D46C1A10BE948B42E81D876

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/onnx/backend/test/case/node/__pycache__/size.cpython-38.pyc
FileSize1166
MD5B0125F18195C92C555A0796B6E3E2958
SHA-10062F897A34948250D46C1A10BE948B42E81D876
SHA-2564B65EA65BDD3C54CA334F39471213C3A0EF4E9008ADE752415EBE9AD006A42F6
SSDEEP24:92FDz1uGv1UIygxA9avxMVA1hZ4c6/xut1AwmcY/W6n5WsUlKJaOYIYI:wD1ByqZeEcdLdfX5WsWKAYYI
TLSHT1A92142C2C5429F77FF28F0F6C4EE4114D1B190AD97D15D063B85663A2C082EA1C60B49
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
MD54968FBDE3FAADCE4D785DB8019E3BA23
PackageArchi586
PackageDescriptionOpen format to represent deep learning models. With ONNX, AI developers can more easily move models between state-of-the-art tools and choose the combination that is best for them. ONNX is developed and supported by a community of partners.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython38-onnx
PackageRelease1.10
PackageVersion1.8.1
SHA-1527D2BF4F7F9FAEF88C1F4F157FFCEF52875A0AE
SHA-256B161199B6B4B874CC5564379D12DE2FC460B2F57BF6BD0300BC4B381C8D56112