| Key | Value |
|---|---|
| FileName | ./usr/lib64/python3.6/site-packages/onnx/backend/test/case/node/__pycache__/maxunpool.cpython-36.pyc |
| FileSize | 1922 |
| MD5 | 6F1FCA863CFCED756FD74DD395AFD1E1 |
| SHA-1 | 013F6427706BE4FC9431A65691C53EA5FAF6386C |
| SHA-256 | 1A1D06D88DE2109C2BDFFB14486C10E3714C28633AA1A23656432C03F18FCA1F |
| SSDEEP | 48:pD110GBgaHGvMw0BZ+qMDgNccKmQ8L17GlzOoMDYI:pnhgampu7i+cc7BL6zOoAP |
| TLSH | T1924165D1900C1EABFD55F0F884B5025AFBA440DE0F712863FF05B68ADD185D4182295E |
| hashlookup:parent-total | 1 |
| hashlookup:trust | 55 |
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 |
|---|---|
| MD5 | 58477028865FBC5CFF586C80B10047AF |
| PackageArch | x86_64 |
| PackageDescription | Open 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. |
| PackageName | python3-onnx |
| PackageRelease | lp152.2.98 |
| PackageVersion | 1.8.1 |
| SHA-1 | 6DF7EBA43B586B95199776B5F9004A59181F686C |
| SHA-256 | B6FFB6FB78AAE389339AB0BECE909E22DDD0CC5A3FCA6BBA4D902F15D86BF72E |