Key | Value |
---|---|
MD5 | 3D24FA6CD4AA40119C15188AEA7C80BA |
PackageArch | i586 |
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 | 6.4 |
PackageVersion | 1.6.0 |
SHA-1 | 41A30FA8DD2137FFFCD5A7881601D57FDAAEDA3D |
SHA-256 | 6A5FF53DBFAEA135330A29B505A75077864B70B89310C3ED041BE5D442843E57 |
hashlookup:children-total | 2617 |
hashlookup:trust | 50 |
The searched file hash includes 2617 children files known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileName | snap-hashlookup-import/app/machine-learning/python-packages/onnx/backend/test/data/node/test_unique_not_sorted_without_axis/test_data_set_0/input_0.pb |
FileSize | 33 |
MD5 | 744756E3B1EEA26D2734BF9EA1062270 |
SHA-1 | 00249AEF2BFD0861B303F9731A71AE2B599CEA3E |
SHA-256 | 36CF0EC69194FE4F0FB0DF6612A387CAA57A529A5E0885DA9F0978DAED006F58 |
SHA-512 | 58242C9D6A342A868078152674FE1DAB1464994C9376C526480FC15470D239C1A1FC97247CBFF8513FDCE64B0BC3605AF261005A291B5B4A33EBBFD2D4B2ADA0 |
SSDEEP | 3:TknOlQotlXlln:onKQ49 |
TLSH | |
insert-timestamp | 1721647816.5803854 |
mimetype | application/octet-stream |
source | snap:RE98ktTqRPHHtxUS9I7T7NQXPIxYHG4q_143 |
Key | Value |
---|---|
FileName | snap-hashlookup-import/app/machine-learning/python-packages/onnx/backend/test/data/node/test_pow/test_data_set_0/input_0.pb |
FileSize | 254 |
MD5 | 1236606A29D429E5853E78CF5A383D37 |
SHA-1 | 004A45FCBA63BB2681290081A128A54F31ADBB54 |
SHA-256 | 018FD53069CA24142BC3DF2DCFFA9815166EEA86EE5C2F9D190C898CAACA8CAA |
SHA-512 | D7F6A8DE3DA5E32FCDD77AFD266FCD4E677270E5F164EED514133529A43F579B92D16C474D8B24C69BCAB8A483BCC3CBB5E07250201BD0514258872F109F2447 |
SSDEEP | 3:0hGhVEtWlvvFl/lk9sl6cl/slqMlPsla0u1N2dl+ldGN1OVSlTnZ7n1TnRrntznR:0/WM9EtEd91MdslsNMVSf |
TLSH | T141D08053774897D1E1685D304DE33D1763474C7C51B5300C4F67031B15D4157550DC87 |
insert-timestamp | 1721647809.7144208 |
mimetype | application/octet-stream |
source | snap:RE98ktTqRPHHtxUS9I7T7NQXPIxYHG4q_143 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/onnx/backend/test/case/node/__pycache__/logsoftmax.cpython-38.opt-1.pyc |
FileSize | 2378 |
MD5 | B197952618EB5C84F013B1F999709483 |
SHA-1 | 00F91AA53BAF8953CD00A09002EE1C17A5A42026 |
SHA-256 | BCF465789911FC91995486A30A4B5BD0512E7FE963A4B780D9BE1B685A9E4E02 |
SSDEEP | 48:MD110UED+ndOT5l10q+VhVNUY0u91o9q+VV9Gbm98RBA2OSk86yqk5/TtQHJzHYI:MHp2Kq+rVNU89O9q+f9n983m186yqoBc |
TLSH | T14C414382D84FAB46F92CF6B640AFC991D7E2B71D937860C7396486086F8D1752A3D60C |
Key | Value |
---|---|
FileName | ./usr/lib64/python3.6/site-packages/onnx/backend/test/data/node/test_tan_example/model.onnx |
FileSize | 87 |
MD5 | 9E4F287C0ED66271FD53BDB80FC4DA27 |
SHA-1 | 0100A9052740D8D2732DE346B73147533265A52A |
SHA-256 | ABE8800BB5A6BB436087FB185E020ECF721D4E4DC88349433D80C2242597B6B5 |
SSDEEP | 3:upkZAthd3VmZBUu3Mptm0VNtkptmnmn:uq+7dhDm8tkDmnmn |
TLSH | T175B012CA0A1204014B32C01FC8110633900DC551448CF7C51385C44D4D82CA14886344 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/onnx/backend/test/case/node/__pycache__/dequantizelinear.cpython-38.opt-1.pyc |
FileSize | 1111 |
MD5 | 658A4DA0943FF63979ED44ACB89A2BDA |
SHA-1 | 015B57F3C585D5372C4EA7BF9B5DDFA2F9FC3F30 |
SHA-256 | 67C9AF6B27A5E8397904100EF8B5ADBE6C4838BACBA1183F1177686D450369CA |
SSDEEP | 24:rFDz1uGv1UI/lBBKy3mkh2ca7qAWR8XhZgi6wm9v5lyaOE+M:hD1BdKkmkhPa+ATX0i6dNjuM |
TLSH | T13A2135C1C484EAF6FE24F0F550AF075D5576442A5FC615425B88545A6C043E12920568 |
Key | Value |
---|---|
FileName | snap-hashlookup-import/app/machine-learning/python-packages/onnx/backend/test/data/pytorch-converted/test_AvgPool3d_stride/model.onnx |
FileSize | 196 |
MD5 | C35533FBAF16988482DDAE450CCBF859 |
SHA-1 | 015CFE60A9DA4E71A8B2F2B6D13545E27C764893 |
SHA-256 | 8B80276BBF2F4E3E031BFEEF5A8F5342AA7CAD1D52B0C250CCD3ED119B6771D6 |
SHA-512 | 3EECBD63E9A613DD0519D1F7B55B566685D4EE5BC8BCBD835C744379EA280A250B8E9B1162D6B203DB703BECD798374472D6EC308BFF8B6D4744CB96080ECBD8 |
SSDEEP | 6:ui2RKXfhEUiMJWWeRg1JRU99u4LPAvb6kcAvr:ui2qEfRy0Sb69Kr |
TLSH | T122D01213048914D8EB092014F49659984543E00D15CD87E155CAEF07BC44D4D4A845D9 |
insert-timestamp | 1721647789.7102919 |
mimetype | application/octet-stream |
source | snap:RE98ktTqRPHHtxUS9I7T7NQXPIxYHG4q_143 |
Key | Value |
---|---|
FileName | snap-hashlookup-import/app/machine-learning/python-packages/onnx/backend/test/data/node/test_scatter_with_axis/model.onnx |
FileSize | 199 |
MD5 | 1848210776A05751E8F7C5A8705889EC |
SHA-1 | 01602490EEDAED1C47366D487CB4E7247769C76D |
SHA-256 | 98278975EB8059E4367087D4D78678024E2F9E52B3D429951F870B4AC167D497 |
SHA-512 | C5C141F57D8BF404678B2208018929B06F35B1C655F6D757AD7AAABD9C54928907317879190984071ADAD64D475F74FD30BD2C97053C7F57CC8EF5273D823695 |
SSDEEP | 3:E9vyTXBBjwzRB9uS9zX6z2WwiL4d/G/TN7D0/GlQVB4XptS/GoV3rv4d/Gs3n:E9vyNr+exwi8Y717lQV0ptNoV374Ys3 |
TLSH | T19CD022B3D020A80E072F10182892B7987412F41908C64B908108C7370D62DB4F8EE333 |
insert-timestamp | 1721647811.0299919 |
mimetype | application/octet-stream |
source | snap:RE98ktTqRPHHtxUS9I7T7NQXPIxYHG4q_143 |
Key | Value |
---|---|
FileName | snap-hashlookup-import/app/machine-learning/python-packages/onnx/backend/test/data/node/test_reduce_sum_square_negative_axes_keepdims_random_expanded/test_data_set_0/output_0.pb |
FileSize | 43 |
MD5 | FC666F6BDA36D47375D022C6C615F46D |
SHA-1 | 017EC79D5C208495B80277B2AC4605AA8525D707 |
SHA-256 | 4FEB9DD68CA76CFAD4EA4F286D40EF62AC50A02B2AD0DF92FFC4892B1B61B819 |
SHA-512 | 953283E3F750F17C939295FC042700063639B9D5845ED26E37E5F3C9DB4A6B68479034AA50F1BA65940C48811EBBA6B121EBF6549D68BE414276FA63B5DFB427 |
SSDEEP | 3:0kflfsanjunlPnn:0kVJnj4Pnn |
TLSH | |
insert-timestamp | 1721647814.033244 |
mimetype | application/octet-stream |
source | snap:RE98ktTqRPHHtxUS9I7T7NQXPIxYHG4q_143 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/onnx/backend/test/case/node/__pycache__/averagepool.cpython-38.opt-1.pyc |
FileSize | 10164 |
MD5 | A927856633AF9BF569DE1065E25754FF |
SHA-1 | 01836336056F4A93923E706E5FC41A7604A877AB |
SHA-256 | CF0475FBFC448C32BC2CD2DEF8183D89D01B694609F7BC349F5540863058EE57 |
SSDEEP | 192:xks89aOSqrYiBB3BdKDPjj+ohThpqAlyA2j+DhEVSj4v7El6zn2BaZPE7:Ss89aOSw73BC2ohloAlyAI+DWVJol6C1 |
TLSH | T19C22208744493F5EFD13F0B336E10D126F94C65B974598B2BA1CA7AFDB092C2093469A |
Key | Value |
---|---|
FileName | ./usr/lib64/python3.6/site-packages/onnx/backend/test/data/node/test_mod_mixed_sign_float16/model.onnx |
FileSize | 131 |
MD5 | 65EC34E5AE89A1E16D4EA7E20440E2B2 |
SHA-1 | 0183F846EF9F6BEA20749AECE6769B487996CDED |
SHA-256 | C115075EC02FEEF6EC5062F4D3266D8EB361F730C1647A07C632BC4AF866F569 |
SSDEEP | 3:E9vpLV3WGRPudx9Mk/WR6/XTt//HHptD+f1tvpt79f3ptbln:E9vnpudx90R6bNGNtdF |
TLSH | T160C09B82F57565340F34916DEC39127B0218CAC5267433CFC745640E45C8D21914D744 |