{"push_id":2996199130,"size":390,"distinct_size":390,"ref":"refs/heads/master","head":"b01237716484a92b6f11e9efedc72da6bb8dddb8","before":"d072caf1a3ef767e0ebd3617d5a9ec99f6fc7e37","commits":[{"sha":"7acb1458934abd3c44aa6d494cf5a29b0ff37e86","author":{"name":"Laura Gustafson","email":"2d8f4cf52f1d6c58b0854d71d31d6a12079d482f@fb.com"},"message":"Fixed print issue for TensorTypeId (#12402)\n\nSummary:\nFixed printing issue for TensorTypeID. It used to print a hex of the ID, e.g.\n   /x1\nNow it prints the ID as a string, e.g.\n  1\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12402\n\nReviewed By: ezyang\n\nDifferential Revision: D10224026\n\nPulled By: lauragustafson\n\nfbshipit-source-id: a9ca841d08c546fccbb948a17f06a29fea66f3fb","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/7acb1458934abd3c44aa6d494cf5a29b0ff37e86"},{"sha":"cee19eb31cb661a0f7fb44b31ef5cc8fc9fabf15","author":{"name":"Orion Reblitz-Richardson","email":"e68e608cba1189ad338a33f5a502b06d361894c6@fb.com"},"message":"Back out \"[c10][NFCI] Move jit/type, function_schema, and utils/functional to ATen/core\" (#12568)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12568\n\nSecond attempt at D10324615\n\nOriginal commit changeset: b71eeec98dfe\nOriginal commit changeset #2: 1af6400ae0c1\n\nReviewed By: bwasti\n\nDifferential Revision: D10338168\n\nfbshipit-source-id: 04cb443a89a9cd1a174df6d5ac1a86c3d423d56b","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/cee19eb31cb661a0f7fb44b31ef5cc8fc9fabf15"},{"sha":"8482ea877441600129a32d703864e6f604be02d7","author":{"name":"Junjie Bai","email":"7c824f2e1c4d8e5c9445dd7ded4e96febed020f7@in.tum.de"},"message":"Update develop install command in onnx scripts\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/12561\n\nDifferential Revision: D10340194\n\nPulled By: bddppq\n\nfbshipit-source-id: 10fb7261028d56f73111e2ca39d4eb2ab930812a","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/8482ea877441600129a32d703864e6f604be02d7"},{"sha":"a4120fa132849028d2c84dee684b3dda1ef4e8b2","author":{"name":"James Reed","email":"f6111144b37277d4771706e14416c5fc33d0fdf4@fb.com"},"message":"Get rid of emitApplyIdent (#12504)\n\nSummary:\nAnd reroute builtin/CompilationUnit function resolution through one resolution pathway\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12504\n\nDifferential Revision: D10319920\n\nPulled By: jamesr66a\n\nfbshipit-source-id: 3ab9877664dd32b97136a7625d0688e1adc0c022","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/a4120fa132849028d2c84dee684b3dda1ef4e8b2"},{"sha":"eef083e4774c52161148883c53ce5a1f081e64ca","author":{"name":"Will Feng","email":"1afd6515b09d0b3eb7e8e4008edd2316b575fbe3@fb.com"},"message":"CircleCI: add timestamp to build log, clean up unused jobs, print docker image name\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/12556\n\nDifferential Revision: D10343032\n\nPulled By: yf225\n\nfbshipit-source-id: fd2dcba18a5cb037fdc448dba64bf9d747dc3761","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/eef083e4774c52161148883c53ce5a1f081e64ca"},{"sha":"666bebc7d2ec196f91c639710c36ab85b4114aaa","author":{"name":"Wei Wen","email":"547ba58dbfd1a1cdbc0c391baff4160b91f741b4@fb.com"},"message":"adapting caffe2 operator docs generator to pytorch url\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10801\n\nDifferential Revision: D9472991\n\nPulled By: ezyang\n\nfbshipit-source-id: 1b8ba77b8255b7e900b6528bd93b3b870f9ba0d4","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/666bebc7d2ec196f91c639710c36ab85b4114aaa"},{"sha":"033e00cd3f1f89152c95e3f8e5474f7520484ffd","author":{"name":"wuhuikx","email":"0675fbf1ee839d874a13d10b44d9c042b4723e11@intel.com"},"message":"Fix bug in caffe_translator tool (#10056)\n\nSummary:\n1. Fix BN translator\n    IntelCaffe and NVCaffe fuse BN+Scale, and the \"BatchNorm\" op contains 5 params including (scale and bias)\n\n2. Fix Scale translator\n   the translated outputs of scale have the same names with those of Conv.\n   All their names are output + '_w' and output + '_b'\nPull Request resolved: https://github.com/pytorch/pytorch/pull/10056\n\nDifferential Revision: D10099205\n\nPulled By: yinghai\n\nfbshipit-source-id: 73a73868e3e16c495e8b233fdb1d373d556a9537","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/033e00cd3f1f89152c95e3f8e5474f7520484ffd"},{"sha":"7b0f5d6631321c9758a853dd3ac2c95ebf326d53","author":{"name":"Orion Reblitz-Richardson","email":"e68e608cba1189ad338a33f5a502b06d361894c6@gmail.com"},"message":"Support USE_CUDNN for Windows (#12518)\n\nSummary:\nFixes https://github.com/pytorch/pytorch/issues/12495\n\ncc peterjc123 mingzhe09088\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12518\n\nReviewed By: mingzhe09088\n\nDifferential Revision: D10338792\n\nPulled By: orionr\n\nfbshipit-source-id: b465c42ea6d5fe9dbc2a4e1f973d952365d0af07","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/7b0f5d6631321c9758a853dd3ac2c95ebf326d53"},{"sha":"0f9807ee619a47ec0b39e5549c227d15b3db475d","author":{"name":"James Reed","email":"f6111144b37277d4771706e14416c5fc33d0fdf4@fb.com"},"message":"Enable addmm fusion for ONNX export only (#12538)\n\nSummary:\nThere's some action at a distance issues and not having this is disabling quantization in C2 for prod use cases\n\nref T34831022\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12538\n\nDifferential Revision: D10302931\n\nPulled By: jamesr66a\n\nfbshipit-source-id: 700dc8c5c4297e942171992266ffb67b815be754","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/0f9807ee619a47ec0b39e5549c227d15b3db475d"},{"sha":"0ee2e7c398167a17b0b86797a8a353fae8e95f97","author":{"name":"Yinghai Lu","email":"0674548f4d596393408a51d6287a76ebba2f42aa@fb.com"},"message":"Relax the locking of running_mutex_ in async_scheduling net (#12544)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12544\n\n`running_mutex_` inside async_scheduling net is used to guard access to the `running_` variable. So we don't need to acquire that lock when we are actually running the net. This will help us prevent potential double locking situation when we decide to run the root nodes inline.\n\nReviewed By: ilia-cher\n\nDifferential Revision: D10304745\n\nfbshipit-source-id: 5f701b2c22b06ff5bee7f2c37ac634326748f579","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/0ee2e7c398167a17b0b86797a8a353fae8e95f97"},{"sha":"a1487bf8746d1b13d7930d3a522aa2ef2f5b1702","author":{"name":"Richard Zou","email":"32cb0331e7af743fc44515966c14887fb6c0bc3c@gmail.com"},"message":"Smarter differentiable subgraph slicing (#12175)\n\nSummary:\nIf any inputs require_grad then the graph executor does differential subgraph slicing. The existing algorithm combines adjacent differentiable Node*.\n\nThere are two major motivations. The first is improving fusion opportunities: the graph fusion pass runs after differential subgraph slicing. This means that only nodes that are a part of the same differential subgraph may be considered for fusion. If something like the following happens,\n```\ny = f(x)\nk = not_differentiable_op(m)\nz = g(y)\n```\nand f and g are both fusible and differentiable operations, then they will be inserted into different differential subgraphs and not fused together.\n\nThe second is to enable JIT optimizations on backward passes for things like an (automatically) unrolled LSTM. Right now, in an unrolled LSTM, we see something like the following:\n```\nlstm_cell()\nnon_differentiable_list_op()\nlstm_cell()\nnon_differentiable_list_op()\nlstm_cell()\nnon_differentiable_list_op()\n```\nEach lstm_cell itself is differentiable and gets put into a separate differential subgraph. During the backwards pass, each prim::DifferentiableSubgraph has its own graph executor: these graph executors cannot talk to each other. It is better if we combined all of the lstm_cells (where applicable) into one differential subgraph so their backward passes are combined into one graph executor that can perform better optimizations than several separate graph executors.\n\nThink about the computation graph as a DAG where edges are data dependencies and vertices are operations (the nodes). Each vertex is either black or red; a vertex is colored black if it is differentiable and red otherwise. The goal is to contract edges (merge nodes) to have the fewest black vertices remaining such that the graph is still a DAG.\n\nThe algorithm is the following:\n- Take the Graph& and create a shadow \"DynamicDAG\" object to wrap Node* and edges. Each Vertex holds multiple Node* (but starts out holding one Node*) and each edge is a data dependency.\n- Greedily contract vertices in the DynamicDAG if they are \"differentiable\". This operation is unrelated to the Graph&.\n  - A Vertex is \"differentiable\" if all the nodes it holds is differentiable.\n  - When contracting vertices, combine their Node* contents.\n  - The DynamicDAG keeps its vertices in topological order and complains if the contraction is invalid so everything is good.\n- Take the DynamicDAG: reorder the nodes in the Graph& to match the topological order in the DynamicDAG.\n- Finally, go through each Vertex in the DynamicDAG: if it contains multiple Node* then merge all of them into a prim::DifferentiableGraph.\n\nThe DynamicDAG is based off of the dynamic top sort algorithm in [this paper](https://www.doc.ic.ac.uk/~phjk/Publications/DynamicTopoSortAlg-JEA-07.pdf) by Pearce and Kelly.\n\nEach contractEdge(producer, consumer) call is `O(|AR| log |AR| * min(|out_edges(producer)|, |in_edges(consumer)|)` where `AR` is the \"affected region\" (defined as the set of nodes that, in topological order, are between producer and consumer). By only considering contractions such that `|ord(producer) - ord(consumer)| < threshold1` and `|out_edges(producer)| < threshold2` we can make each contractEdge(producer, consumer) call take constant time. The resulting algorithm is linear in the number of nodes.\n\nAdded a lot of small test cases.\n\nLooking for suggestions on the following:\n- what big computation graphs should I run this on to test how fast or slow it is?\n- what things other than correctness should I be thinking about when I test this?\n\ncc apaszke zdevito\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12175\n\nDifferential Revision: D10302564\n\nPulled By: zou3519\n\nfbshipit-source-id: 8a94d130d82f8a1713cc28483afef9a72d83d61a","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/a1487bf8746d1b13d7930d3a522aa2ef2f5b1702"},{"sha":"5973312abcb4926d54e85fc596419393c126b3fa","author":{"name":"Junjie Bai","email":"7c824f2e1c4d8e5c9445dd7ded4e96febed020f7@in.tum.de"},"message":"Add clang 6 docker images\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/12581\n\nDifferential Revision: D10349785\n\nPulled By: bddppq\n\nfbshipit-source-id: 638641d369be0898dd6232737ebaa9d9a8c2e557","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/5973312abcb4926d54e85fc596419393c126b3fa"},{"sha":"d9eff4054673341acb0defefcda376cc52e88417","author":{"name":"Cong Chen","email":"377d8eee9d814d187cd26cb0c5a88f0391100a98@fb.com"},"message":"Revert D10209620: Use SFINAE instead of macros for 'long' hack\n\nDifferential Revision:\nD10209620\n\nOriginal commit changeset: 68f09339e279\n\nfbshipit-source-id: e33927e92e34efc40917d97cd8ba80996a875dff","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/d9eff4054673341acb0defefcda376cc52e88417"},{"sha":"8ac8b823c2312ec575518453f49a0ec0914cd720","author":{"name":"Xiaolong Wang","email":"bb7cadc341f752e4e71a201cf300d65ecac2cb13@fb.com"},"message":"Allow use substitute ops for LayerNorm (#12177)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12177\n\nas titled\n\nReviewed By: Wakeupbuddy\n\nDifferential Revision: D9218047\n\nfbshipit-source-id: 8d68861472c99d587e678c3d76ac43abc9c8fe6d","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/8ac8b823c2312ec575518453f49a0ec0914cd720"},{"sha":"93a4b76114e44444a278c572aaf7e55932e74cf0","author":{"name":"Xiaolong Wang","email":"bb7cadc341f752e4e71a201cf300d65ecac2cb13@fb.com"},"message":"Enable alternative LayerNorm impl in FisherGan (#12178)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12178\n\nFisher GAN calls processor_util.add_mlp, which inject the layer norm through the\nnormalizer. We allow to use alternative impl for LayerNorn in the normalizer.\n\nReviewed By: Wakeupbuddy\n\nDifferential Revision: D9235528\n\nfbshipit-source-id: 88c126c658102926613242ef84a481f6de1676ed","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/93a4b76114e44444a278c572aaf7e55932e74cf0"},{"sha":"957142a4fe0983df0d929751864aa8770fba95d0","author":{"name":"Johannes M Dieterich","email":"77f0bd067ad47450966011ebf1d7514e05735095@amd.com"},"message":"switch ROCm CI targets to white rabbit release (#12577)\n\nSummary:\n* switches docker files over to white rabbit release - removed custom package installs\n* skips five tests that regressed in that release\n* fixes some case-sensitivity issues in ROCm supplied cmake files by sed'ing them in the docker\n* includes first changes to the infrastructure to support upcoming hip-clang compiler\n* prints ROCm library versions as part of the build (as discussed w/ ezyang )\n* explicitly searches for miopengemm\n* installs the new hip-thrust package to be able to remove the explicit Thrust checkout in a future revision\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12577\n\nDifferential Revision: D10350165\n\nPulled By: bddppq\n\nfbshipit-source-id: 60f9c9caf04a48cfa90f4c37e242d944a175ab31","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/957142a4fe0983df0d929751864aa8770fba95d0"},{"sha":"97bee5cd80f9e2710e32421ce187bf4288aea551","author":{"name":"Syed Tousif Ahmed","email":"d3090ae36cb92131b89bf8d402596f4b9b6a26bd@gmail.com"},"message":"Adds max plan number for CUDA 10 cufft plan cache array (#12553)\n\nSummary:\nSsnL As per your review in https://github.com/pytorch/pytorch/pull/12017/, I added a max plan number for CUDA 10 path. Our internal cuFFT team couldn't suggest a number since the limit depends on host/device memory. That is, a plan allocates some buffers on the device and also creates objects for the plans on the host side. I raised this number to 4x arbitrarily per you suggestion.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12553\n\nDifferential Revision: D10320832\n\nPulled By: SsnL\n\nfbshipit-source-id: 3148d45cd280dffb2039756e2f6a74fbc7aa086d","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/97bee5cd80f9e2710e32421ce187bf4288aea551"},{"sha":"eb5fdc5fb572c4b663a16955d10df8787dae45e0","author":{"name":"David Riazati","email":"ff36620a3ee63bd6d8ae92408cbddaf6f4dc951a@fb.com"},"message":"Add default values in script (#12345)\n\nSummary:\nAdd support for default values on script functions and Modules\n\nFollowup to #11962\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12345\n\nReviewed By: michaelsuo\n\nDifferential Revision: D10263613\n\nPulled By: driazati\n\nfbshipit-source-id: 9b380d8c3f8c4abb2d24c33b23c00ec5896ca372","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/eb5fdc5fb572c4b663a16955d10df8787dae45e0"},{"sha":"01cb90adf1f4946625d4230aee193f0a59427d03","author":{"name":"Lu Fang","email":"6e6bc3b7f607f5d674fb8a406040e26b26ffec27@fb.com"},"message":"fix the ONNX test_operator test (#12591)\n\nSummary:\nupdate the expect file\nPull Request resolved: https://github.com/pytorch/pytorch/pull/12591\n\nDifferential Revision: D10355620\n\nPulled By: houseroad\n\nfbshipit-source-id: 5acdbf2406d322378025631808108a2d795be916","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/01cb90adf1f4946625d4230aee193f0a59427d03"},{"sha":"fa99ed9b303b86a6369ee51e43f3d55fc8f16a80","author":{"name":"Giuseppe Ottaviano","email":"326ed324dd4422d207643d5a7419ea85379f1b4e@fb.com"},"message":"Emit warning about optimization passes only once\n\nReviewed By: ajtulloch\n\nDifferential Revision: D9584925\n\nfbshipit-source-id: 191035eaefe3ab3980e46598f2ebf34b2b704a9b","distinct":true,"url":"https://api.github.com/repos/Swetko/pytorch/commits/fa99ed9b303b86a6369ee51e43f3d55fc8f16a80"}]}
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