{"push_id":2832307079,"size":164,"distinct_size":31,"ref":"refs/heads/bump-onnx","head":"43dc0c2040443845eeeb6d13be50d9561635c0e5","before":"380f880287ec3fbeb33d599d1f624865377009de","commits":[{"sha":"6667d55e7378ce5cef502be3e3790324aeaf2197","author":{"name":"Summer Deng","email":"601255e35563852a4b111fcd0d33280e92d488e9@fb.com"},"message":"Disallow input filler for GatherRangesOp (#10592)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10592\n\nFilter out GatherRanges ops\n\nReviewed By: highker\n\nDifferential Revision: D9365220\n\nfbshipit-source-id: e21ab00dc9e553c9aaf172e1241206e0c0a7a23d","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/6667d55e7378ce5cef502be3e3790324aeaf2197"},{"sha":"0aefb9f26c2b656ede508d934237fee3391ac6e4","author":{"name":"onnxbot","email":"828d3dd9b917b018df0616359d3221a16e923c7e@gmail.com"},"message":"Update onnx to onnx/onnx@7848f1e (#10613)\n\nSummary:\nhttps://github.com/onnx/onnx/commit/7848f1e\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10613\n\nReviewed By: houseroad\n\nDifferential Revision: D9376224\n\nPulled By: bddppq\n\nfbshipit-source-id: ce8a53255ba24f0f8f989570e8b015837f8442fb","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/0aefb9f26c2b656ede508d934237fee3391ac6e4"},{"sha":"cc53807be5abfafea61cf3e43680e5e0a7f98a87","author":{"name":"Jongsoo Park","email":"9a3e35cef3c98d8190c15db076afab6069cc7549@fb.com"},"message":"group conv with NHWC layout (#10585)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10585\n\ngroup conv with NHWC layout\n\nReviewed By: BIT-silence\n\nDifferential Revision: D7547497\n\nfbshipit-source-id: da0ec5a4512c15a0a0d7b79e6ce00c1f8f77f661","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/cc53807be5abfafea61cf3e43680e5e0a7f98a87"},{"sha":"51222500e28b49084d77555f63f5a383ddd91b80","author":{"name":"Tongliang Liao","email":"ef12c0d2718a09340470c6e8b2679ab2d56126fa@microsoft.com"},"message":"Add AT_CORE_EXPORT and AT_CORE_IMPORT. (#10602)\n\nSummary:\nFix \"error LNK2019: unresolved external symbol\" from \"CAFFE_KNOWN_TYPE\" in tests where we should use dllexport instead of AT_CORE_API(=dllimport).\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10602\n\nDifferential Revision: D9377394\n\nPulled By: Yangqing\n\nfbshipit-source-id: 993062a461ffce393f2321c5391db5afb9b4e7ba","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/51222500e28b49084d77555f63f5a383ddd91b80"},{"sha":"ff3a481aee00a053a5e0ad731159cdc99a1dfea8","author":{"name":"Nikita Melentev","email":"5b36635666423dfedf141c477fe73492a84fa0f1@kronshtadt.ru"},"message":"fix python interpreter can not be found (#10543)\n\nSummary:\nCustom python installation, which have no aliases to `python` or `python3` can't be found by cmake `findPythonInterp` without extra cmake argument.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10543\n\nDifferential Revision: D9378844\n\nPulled By: ezyang\n\nfbshipit-source-id: 022e20aab7e27a5a56b8eb91b6026151116193c7","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/ff3a481aee00a053a5e0ad731159cdc99a1dfea8"},{"sha":"03982fb8d3a4f1285ad4d11c35e835d2307ab4a2","author":{"name":"Yinghai Lu","email":"0674548f4d596393408a51d6287a76ebba2f42aa@fb.com"},"message":"Fix subgraph cutting wrt recent external_input change in nomnigraph (#10598)\n\nSummary:\nhttps://github.com/pytorch/pytorch/pull/10100 recently take external input/output in nomnigraph. This PR makes adjust to\n0. Relax some of the conditions on external input\n1. Update NNModule inputs/outputs when pruning the input/output.\n2. Avoiding copying external input/output as nomnigraph already takes care of it.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10598\n\nReviewed By: bwasti\n\nDifferential Revision: D9371730\n\nPulled By: yinghai\n\nfbshipit-source-id: 9273be5041dc4cc8585587f47cb6721e518a06a8","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/03982fb8d3a4f1285ad4d11c35e835d2307ab4a2"},{"sha":"31c7a32d1c2a32545106890fd0beaae921abd7d4","author":{"name":"Junjie Bai","email":"e125fa9f869484580157ed79c2b726bc1aed894f@fb.com"},"message":"Include aten_op by default in caffe2\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10603\n\nReviewed By: ahhegazy, dzhulgakov\n\nDifferential Revision: D9364309\n\nfbshipit-source-id: e72d9f2b1e99cb0fb2186c737fcd925b14d42754","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/31c7a32d1c2a32545106890fd0beaae921abd7d4"},{"sha":"e190505e84e6b03970e718f1e74b41c7675dec57","author":{"name":"Elias Ellison","email":"32bcb86024d493ca261d5686b38111589a7092c1@fb.com"},"message":"Adding support for inlining if branches (#10084)\n\nSummary:\nInlining if branches which have constant inputs.  If an if node gets inlined, the set of mutated variables returned by its ancestors may have changed. In the following example the block should\nreturn a mutated set of (a) and not (a, b).\n\n```\nif cond:\n  if True:\n\t a = a - 1\n    else:\n\tb = b - 1\n```\nTo calculate this we recursively update mutate variables in if branches from the leaf nodes up.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10084\n\nReviewed By: michaelsuo\n\nDifferential Revision: D9340429\n\nPulled By: eellison\n\nfbshipit-source-id: b0dd638a5cace9fdec3130460428fca655ce4b98","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/e190505e84e6b03970e718f1e74b41c7675dec57"},{"sha":"ff440b61f6689c51b8a5d4e53043b97bb49b9eab","author":{"name":"Edward Yang","email":"dbd597f5635f432486c5d365e9bb585b3eaa1853@fb.com"},"message":"Revert D9378844: [pytorch][PR] fix python interpreter can not be found\n\nDifferential Revision:\nD9378844\n\nOriginal commit changeset: 022e20aab7e2\n\nfbshipit-source-id: 962280707e84edff2a4f59b1ce2f4211a579a055","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/ff440b61f6689c51b8a5d4e53043b97bb49b9eab"},{"sha":"bd9ab650aedb3ad202b3100d9a7f92855247f1bd","author":{"name":"Jongsoo Park","email":"9a3e35cef3c98d8190c15db076afab6069cc7549@fb.com"},"message":"fix compile error in math_hip.cc from new Im2Col/Col2Im interface (#10623)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10623\n\nFix compile error in https://ci.pytorch.org/jenkins/job/caffe2-builds/job/py2-clang3.8-rocm1.7.1-ubuntu16.04-build/10280//console\n\nReviewed By: ezyang\n\nDifferential Revision: D9379451\n\nfbshipit-source-id: 67cc3964981edba1915b93c49643caa300d63c16","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/bd9ab650aedb3ad202b3100d9a7f92855247f1bd"},{"sha":"b4e72ea811cf7af71f1d54dda37d37314db697c0","author":{"name":"Andrey Malevich","email":"41d47f81927577564ba647e53d5ac36ee1fa4827@fb.com"},"message":"Revert D9377394: [pytorch][PR] [Caffe2] Add AT_CORE_EXPORT and AT_CORE_IMPORT.\n\nDifferential Revision:\nD9377394\n\nOriginal commit changeset: 993062a461ff\n\nfbshipit-source-id: af8ab92e9b88466602508981d9b3ea24ce393dfc","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/b4e72ea811cf7af71f1d54dda37d37314db697c0"},{"sha":"52058204d6759d435988db10247ccd3383657634","author":{"name":"Wanchao Liang","email":"cec3728d98a9425a5de254a15f6461e93e451168@users.noreply.github.com"},"message":"Add nn functional tests in JIT (#10409)\n\nSummary:\nThe PR is the first step to integrate torch.nn library with JIT. It adds the tests for nn functional interfaces in trace/script mode, and tries to find out the different between torch.nn.functional ops and the ATen ops, to see the work need to be done in order to support a full set of nn functional in script mode.\n\nSome statistics in summary:\n\n- Totally 84 useful functions in torch.nn.functional (the number does not include helper funcs and deprecated funcs in torch.nn.functional).\n\n- 7 functions/ops does not support higher gradient, so just excluded from the whole test.\n\n- 36 functions is different with the Aten op for different reasons. Among those 36 functions, bunch of them (roughly around 10-15) are just naming difference and simple transformation using other ops inside the function.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10409\n\nDifferential Revision: D9350694\n\nPulled By: wanchaol\n\nfbshipit-source-id: 8fce6f30d8d25ace5a544a57b219fe61f5a092f8","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/52058204d6759d435988db10247ccd3383657634"},{"sha":"d35f365ad578110e10afce56574e2d00bf59e727","author":{"name":"Adam Paszke","email":"71faef99c0ae9d81958d0035c1ce72f9c3888cfe@gmail.com"},"message":"Remove all cuDNN specific inputs to RNN functions (#10581)\n\nSummary:\nThis is still not the final PR, but it removes all blockers for actually using the RNN functions directly in the JIT. Next patch should be final, and will actually remove the symbolic_override code, and change it to proper symbolics for those ATen functions. Turns out the symbolic code can be also cleaned up a bit, and I'll do that too.\n\nzdevito ezyang\ncolesbury (for minor DispatchStub.h) changes\n\nThere was no way to handle those in the JIT for now, and they turned\nout to be completely unnecessary. It should make the Python and C++\nmodule code much simpler too, since all the logic is now centralized\nin the native functions.\n\nThe downside is that RNN modules no longer own their dropout buffers,\nwhich are shared per-device instead (with appropriate locking and\nsynchronization). This might appear as a perf regression at first, but\nin reality it's highly unlikely that anyone will want to run cuDNN RNNs\non the same GPU in parallel.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10581\n\nReviewed By: colesbury\n\nDifferential Revision: D9365541\n\nPulled By: apaszke\n\nfbshipit-source-id: 3ef8677ee5481bae60c74a9117a2508665b476b5","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/d35f365ad578110e10afce56574e2d00bf59e727"},{"sha":"f3ac619764e520454852602ca2b54cf742a64595","author":{"name":"Keren Zhou","email":"797389e2dbe7a2c02a4bbf84dfb7e500af731c5d@fb.com"},"message":"Add fusion support for batchnorm and convolution without bias\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10595\n\nReviewed By: bwasti\n\nDifferential Revision: D9110099\n\nfbshipit-source-id: e1ed66c7d82b2f9987b7eb9c7f98877a6dbeb902","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/f3ac619764e520454852602ca2b54cf742a64595"},{"sha":"86c9856d9c878631e611de0e138bc409228bbfef","author":{"name":"Richard Zou","email":"32cb0331e7af743fc44515966c14887fb6c0bc3c@gmail.com"},"message":"Fuse tensor-scalar ops when scalar is constant (#10511)\n\nSummary:\nThis is on the way to resolving #9940.\n\nFixes #10501\n\nThis PR modifies graph fuser to fuse operations that have constant\nscalar arguments. These constant scalar arguments are directly inlined\ninto the kernel body.\n\nThe context for this is that LSTM backward (in particular, sigmoid\nbackward) has many add(x, 1.) operations. This PR should be sufficient for\nLSTM backward to get fused by the graph fuser.\n\ncc apaszke zdevito\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10511\n\nDifferential Revision: D9378896\n\nPulled By: zou3519\n\nfbshipit-source-id: 6a7a2987f5b6e8edaaf4b599cd200df33361650f","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/86c9856d9c878631e611de0e138bc409228bbfef"},{"sha":"c5c1c051cac7a120a1aeecaf3f6fb418d9a989d6","author":{"name":"Tongzhou Wang","email":"96b5c3d5a7a36c8be47478427b2e4d4231204fe0@gmail.com"},"message":"Fix dropout fused kernel applied in eval mode (#10621)\n\nSummary:\nfixes https://github.com/pytorch/pytorch/issues/10584\n\ncc apaszke\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10621\n\nDifferential Revision: D9379397\n\nPulled By: SsnL\n\nfbshipit-source-id: 5ff2939ba794af082ce597ef289a09ee757636dc","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/c5c1c051cac7a120a1aeecaf3f6fb418d9a989d6"},{"sha":"b62b378022520f8ba35d0d8835131f11fb23e2e5","author":{"name":"Jesse Hellemn","email":"36a619e0a65e414b979fcef8f80e55b1a41df598@fb.com"},"message":"Adding torch support for CMAKE_ARGS env\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10635\n\nReviewed By: ml7\n\nDifferential Revision: D9383845\n\nPulled By: pjh5\n\nfbshipit-source-id: fb21bda12e88053eec738974e6e419388c5038d9","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/b62b378022520f8ba35d0d8835131f11fb23e2e5"},{"sha":"65b93081281f39362bb6a532ff4ff683073ebedf","author":{"name":"Peter Goldsborough","email":"887f44f8e6d2ec27368b0275bb31f402fb8ca659@fb.com"},"message":"Basic infrastructure for C++ documentation (#10569)\n\nSummary:\nAdds the folder structure, Doxyfile, sphinx setup and Makefile to build C++ docs.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10569\n\nDifferential Revision: D9386744\n\nPulled By: goldsborough\n\nfbshipit-source-id: 0a7c581dcf0a5f7b01ba19d317b493cf95935134","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/65b93081281f39362bb6a532ff4ff683073ebedf"},{"sha":"7c55d11ba56aaa5ef687cb996b85a46d144c2a1e","author":{"name":"Yinghai Lu","email":"0674548f4d596393408a51d6287a76ebba2f42aa@fb.com"},"message":"Make sure we don't relocate the weight name buffer (#10630)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10630\n\n`onnxTensorDescriptorV1.name` points to the string buffer. We use a vector of strings to serve as the storage. This means we cannot reallocate the vector because that may invalidate the `onnxTensorDescriptorV1.name` pointers. Solution is to reserve a large enough vector so that it won't reallocate.\n\nReviewed By: bddppq, houseroad\n\nDifferential Revision: D9381838\n\nfbshipit-source-id: f49c5719aafcc0829c79f95a2a39a175bcad7bfe","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/7c55d11ba56aaa5ef687cb996b85a46d144c2a1e"},{"sha":"e29b5a1ea8a8564550537f5db2ea0d4c8c45476d","author":{"name":"Richard Zou","email":"32cb0331e7af743fc44515966c14887fb6c0bc3c@gmail.com"},"message":"graph fuser inserts explicit expands where necessary (#10325)\n\nSummary:\nFixes #10096\n\nIf the only thing preventing a simple mappable operator from being fused\ninto a fusion group is that its Tensor inputs are not of the same shape as the\noutput, then the graph fuser inserts explicit expand nodes for those\ninputs.\nThis helps the graph fuser not miss out on any fusion opportunities\ninvolving simple mappable operations that have Tensor inputs. This PR\ndoesn't do anything for the scalar case; that can be addressed later.\n\nTest Plan\n- Simple expect test case\n- Added expect tests for a raw LSTMCell. The expands help speed up the\n  forwards pass by allowing more operations to be fused into the LSTMCell's single\n  FusionGroup.\n\ncc apaszke zdevito\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10325\n\nDifferential Revision: D9379308\n\nPulled By: zou3519\n\nfbshipit-source-id: 86d2202eb97e9bb16e511667b7fe177aeaf88245","distinct":false,"url":"https://api.github.com/repos/bddppq/pytorch/commits/e29b5a1ea8a8564550537f5db2ea0d4c8c45476d"}]}
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