| Key | Value |
|---|---|
| FileName | ./usr/lib64/python3.6/site-packages/onnx/backend/test/report/__pycache__/coverage.cpython-36.opt-1.pyc |
| FileSize | 7081 |
| MD5 | A73726CFDD8C05F0E13A2417515A92C5 |
| SHA-1 | 0076B546FB7A4A261E1D8B65916B27C69EF6FDFA |
| SHA-256 | 3A4C737A1528827CD6CEF2646622C31B3F2334B9187C15750AFCD41776693482 |
| SSDEEP | 192:O9eP3ALwHrD/qmxehUK6s6S57wIZvCrBTEI4:cevALyrD/QbN0rpEI4 |
| TLSH | T126E1C782D9415F9FFC3EF3B8F54E039CA290E3BAD2CC9257541981179C5A2D40B3C5AA |
| 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 |