python deep learning framework
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Source Files
| Filename | Size | Changed |
|---|---|---|
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FP16-febbb1c163726b5db24bed55cc9dc42529068997.tar. |
0000071108 69.4 KB | |
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FXdiv-b742d1143724d646cd0f914646f1240eacf5bd73.tar |
0000008567 8.37 KB | |
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QNNPACK-7d2a4e9931a82adc3814275b6219a03e24e36b4c.t |
0000205600 201 KB | |
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XNNPACK-7493bfb9d412e59529bcbced6a902d44cfa8ea1c.t |
0001289659 1.23 MB | |
| _constraints | 0000000165 165 Bytes | |
| _link | 0000000124 124 Bytes | |
| _multibuild | 0000000057 57 Bytes | |
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cpuinfo-0e6bde92b343c5fbcfe34ecd41abf9515d54b4a7.t |
0003496649 3.33 MB | |
| fix-call-of-onnxInitGraph.patch | 0000000803 803 Bytes | |
| fix-mov-operand-for-gcc.patch | 0000001638 1.6 KB | |
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foxi-97fe555430a857581b9b826ecd955e4f0a3653f0.tar. |
0000028548 27.9 KB | |
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gemmlowp-3fb5c176c17c765a3492cd2f0321b0dab712f350. |
0000826382 807 KB | |
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gloo-113bde13035594cafdca247be953610b53026553.tar. |
0000224049 219 KB | |
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onnx-9fdae4c68960a2d44cd1cc871c74a6a9d469fa1f.tar. |
0002634626 2.51 MB | |
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psimd-10b4ffc6ea9e2e11668f86969586f88bc82aaefa.tar |
0000006800 6.64 KB | |
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pthreadpool-d465747660ecf9ebbaddf8c3db37e4a13d0c91 |
0000020784 20.3 KB | |
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pybind11-25abf7efba0b2990f5a6dfb0a31bc65c0f2f4d17. |
0000559554 546 KB | |
| python-torch.changes | 0000006479 6.33 KB | |
| python-torch.spec | 0000011563 11.3 KB | |
| pytorch-1.5.1.tar.gz | 0010345641 9.87 MB | |
| releases.html | 0000575533 562 KB | |
| removed-peachpy-depedency.patch | 0000001144 1.12 KB | |
| skip-third-party-check.patch | 0000002992 2.92 KB | |
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sleef-7f523de651585fe25cade462efccca647dcc8d02.tar |
0001174007 1.12 MB |
Revision 19 (latest revision is 44)
Tomáš Chvátal (scarabeus_iv)
accepted
request 816799
from
Christian Goll (mslacken)
(revision 19)
- updated to new stable release 1.5.1 which has following changes: This release includes several major new API additions and improvements. These include new APIs for autograd allowing for easy computation of hessians and jacobians, a significant update to the C++ frontend, ‘channels last’ memory format for more performant computer vision models, a stable release of the distributed RPC framework used for model parallel training, and a new API that allows for the creation of Custom C++ Classes that was inspired by PyBind. Additionally torch_xla 1.5 is now available and tested with the PyTorch 1.5 release providing a mature Cloud TPU experience. * see release.html for detailed information - added patches: * fix-call-of-onnxInitGraph.patch for API mismatch in onnx * fix-mov-operand-for-gcc.patch for aarch64 operands - removed sources: * cpuinfo-89fe1695edf9ee14c22f815f24bac45577a4f135.tar.gz * gloo-7c541247a6fa49e5938e304ab93b6da661823d0f.tar.gz * onnx-fea8568cac61a482ed208748fdc0e1a8e47f62f5.tar.gz * psimd-90a938f30ba414ada2f4b00674ee9631d7d85e19.tar.gz * pthreadpool-13da0b4c21d17f94150713366420baaf1b5a46f4.tar.gz - added sources: * cpuinfo-0e6bde92b343c5fbcfe34ecd41abf9515d54b4a7.tar.gz * gloo-113bde13035594cafdca247be953610b53026553.tar.gz * onnx-9fdae4c68960a2d44cd1cc871c74a6a9d469fa1f.tar.gz * psimd-10b4ffc6ea9e2e11668f86969586f88bc82aaefa.tar.gz * pthreadpool-d465747660ecf9ebbaddf8c3db37e4a13d0c9103.tar.gz - updated to bugfix release 1.4.1 and added _multibuild file so that cuda versions can be build on commandline
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