| Key | Value |
|---|---|
| FileName | ./usr/lib64/python3.6/site-packages/onnx/backend/test/case/__pycache__/utils.cpython-36.pyc |
| FileSize | 1068 |
| MD5 | B8A85BE1446637AFF417CA876657C498 |
| SHA-1 | 002E97B6AD28C94A510F54EF03CDDB0F0C84F40C |
| SHA-256 | 4442ECED9AB7B293347F06B813723F768EA8EE5670E7D48CAD24359704BD1C4C |
| SSDEEP | 24:SW+T6sQNuGtF75yHVwSGlUp9O0RvoBatIyag5c2i62msfkln:NIn02ag5c292Ls |
| TLSH | T1571132B206164ED7FE4DE5F0EC25407ACCF6639687D46943760C26F74E022A79670EA4 |
| 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 | 0D124E1D096043BE9A73FDB6576BC608 |
| 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 | lp153.2.78 |
| PackageVersion | 1.8.1 |
| SHA-1 | CF1717814C8C1495A3BF5B49BBCF2AB8B1B36218 |
| SHA-256 | AAE2D7A08EF1A705F010B32FF3A2865FBC644F0ABE66BA83D2EB088EF2F0A207 |