{"push_id":2759495922,"size":82,"distinct_size":6,"ref":"refs/heads/export-D8814669","head":"453b1b874f6e4f87d5b903ed9a52b7e0107f3c3a","before":"4fb5d202fdb2c9b01b658dc09ecc3e2f5bdb6a48","commits":[{"sha":"e39c8043dc97950318ff83eb8502c52f8f4b63d9","author":{"name":"Adam Paszke","email":"71faef99c0ae9d81958d0035c1ce72f9c3888cfe@gmail.com"},"message":"Make GraphExecutors work on Stacks instead of variable_tensor_lists (#9763)\n\nSummary:\nThis is blocking the IR operator unification, because I need to be able to pass scalars to backward functions.\n\nzdevito\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9763\n\nReviewed By: zou3519\n\nDifferential Revision: D8978457\n\nPulled By: apaszke\n\nfbshipit-source-id: 570b4c3409322459cb0f2592069730a7d586ab20","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/e39c8043dc97950318ff83eb8502c52f8f4b63d9"},{"sha":"0c84a5c27e37406190e447565c5b5f69aba3a228","author":{"name":"Junjie Bai","email":"7c824f2e1c4d8e5c9445dd7ded4e96febed020f7@in.tum.de"},"message":"Pass shape infos to ONNX -> Caffe2 C++ conversion backend (#9870)\n\nSummary:\nAnd let Gemm conversion to inspect the input `C` to try converting to FC.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9870\n\nReviewed By: houseroad\n\nDifferential Revision: D9013198\n\nPulled By: bddppq\n\nfbshipit-source-id: b4c509cfccca238262e1c406b004e66cef256321","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/0c84a5c27e37406190e447565c5b5f69aba3a228"},{"sha":"1dc708493e0b164d2fd7c577415e1cc5345d739b","author":{"name":"zou3519","email":"32cb0331e7af743fc44515966c14887fb6c0bc3c@gmail.com"},"message":"Add html-stable target to docs Makefile (#9884)\n\nSummary:\nThis lets one build docs for the release easier. All of the unstable\nwarnings are removed in `make html-stable`.\n\ncc soumith SsnL\n\nSample build:\n![image](https://user-images.githubusercontent.com/5652049/43277115-05e2f720-90d5-11e8-9977-b0b4a6ee4b8e.png)\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9884\n\nReviewed By: SsnL\n\nDifferential Revision: D9016001\n\nPulled By: zou3519\n\nfbshipit-source-id: 5cf2dfbf886de993242db28cdac5d0c5fadbdc4d","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/1dc708493e0b164d2fd7c577415e1cc5345d739b"},{"sha":"456f41301ccaa6240155a6ecd7f5df82dedad7a6","author":{"name":"Junjie Bai","email":"7c824f2e1c4d8e5c9445dd7ded4e96febed020f7@in.tum.de"},"message":"Disable unique ops test on rocm (#9892)\n\nSummary:\nSomehow we have Unique operator tests in two places test_unqiue_ops.py and hypothesis_test.py\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9892\n\nReviewed By: houseroad\n\nDifferential Revision: D9017631\n\nPulled By: bddppq\n\nfbshipit-source-id: 1f9e40e4953afca26141ef4581202b9b9fce0ae9","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/456f41301ccaa6240155a6ecd7f5df82dedad7a6"},{"sha":"969b62f2763647fe32dbe76aa358f00873edbf4e","author":{"name":"Jerry Zhang","email":"210765c83ad755402ff54425bf352bae661dc900@fb.com"},"message":"Revert D8121878: Remove template parameter from Tensor\n\nDifferential Revision:\nD8121878\n\nOriginal commit changeset: 4a5e9a677ba4\n\nfbshipit-source-id: d8e2c0bb145b52fbcca323b22d1d3346f0b3249e","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/969b62f2763647fe32dbe76aa358f00873edbf4e"},{"sha":"18a6541b82ff92ddeae29aeade87e465068696da","author":{"name":"Norman Mu","email":"63e37a0d1d51b8efd953de2fcdb71ed70eedafcd@fb.com"},"message":"Create IDEEP fallback operators for ctc decoder ops (#9847)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9847\n\nCTCBeamSearchDecoder and CTCGreedyDecoder do not currently support IDEEP\nexecution. Add fallback operators to allow IDEEP execution of models that use\nthese operators.\n\nReviewed By: yinghai\n\nDifferential Revision: D9006234\n\nfbshipit-source-id: fc539ba67b07d1f960d28564d8adde0be8690649","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/18a6541b82ff92ddeae29aeade87e465068696da"},{"sha":"d1260d26fe4ef11c1831a4eab34508eff4ad95ff","author":{"name":"Fei Sun","email":"47de1c22bd57c9cb89623ce880105f688d961c10@fb.com"},"message":"Sleep before run (#9891)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9891\n\nAdd an argument to benchmark binary to specify the seconds to sleep before the run and after the warmup.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9880\n\nReviewed By: llyfacebook\n\nDifferential Revision: D9014254\n\nPulled By: sf-wind\n\nfbshipit-source-id: d5566186c8ed768f1e170e9266c5f2d6077391e0","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/d1260d26fe4ef11c1831a4eab34508eff4ad95ff"},{"sha":"d65c667f2895ed71081d0b16fbfdf27054d5fd4d","author":{"name":"Gregory Chanan","email":"405a4c10dc10d9753e4d637a51ebfa857b6fcbb3@fb.com"},"message":"Avoid divide-by-zero when hamming_window window length is 0.\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9896\n\nReviewed By: ezyang\n\nDifferential Revision: D9018572\n\nPulled By: gchanan\n\nfbshipit-source-id: fa314687973124165bffb3084932d8ab6d872a93","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/d65c667f2895ed71081d0b16fbfdf27054d5fd4d"},{"sha":"9df9c46992d596cdbc74ef94ead6d628c8e54c08","author":{"name":"Ailing Zhang","email":"1b6840d5aad3f67904e2d5dd1e336090078ee11e@fb.com"},"message":"fix loading 1dim tensor from 0.3.* to 0dim tensor (#9781)\n\nSummary:\nThis PR fixes #9743 .\n\nAdding backward support when loading a checkpoint from 0.3.* with 1dim tensor, they are now 0 dim tensor in 0.4+.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9781\n\nDifferential Revision: D8988196\n\nPulled By: ailzhang\n\nfbshipit-source-id: a7a1bc771d597394208430575d5a4d23b9653fef","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/9df9c46992d596cdbc74ef94ead6d628c8e54c08"},{"sha":"b7b61a8eb4402129710df7f18a16b1931eff9c84","author":{"name":"Wanchao Liang","email":"cec3728d98a9425a5de254a15f6461e93e451168@users.noreply.github.com"},"message":"Change expect, cast on Type to return shared pointers, make isSubtypeOf accept TypePtr (#9786)\n\nSummary:\nFollow up task of #9584.\n\nCommit 1:\n\n- change expect/cast to return shared pointers instead of raw pointer\n- isSubtypeOf accept TypePtr instead. Use `x->isSubtypeOf(NumberType::get())` rather than `x->isSubtypeOf(*NumberType::get())`\n\nCommit 2:\n\n- to address enable_shared_from_this pitfalls, we make the constructor private and expose the factory method to make sure user can only create it using our factory method.\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9786\n\nReviewed By: zdevito\n\nDifferential Revision: D8980441\n\nPulled By: wanchaol\n\nfbshipit-source-id: e5c923fc57a701014310e77cf29985b43bb25364","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/b7b61a8eb4402129710df7f18a16b1931eff9c84"},{"sha":"e7ab093d93c968158430ad02cf52a22f829a0816","author":{"name":"Jongsoo Park","email":"9a3e35cef3c98d8190c15db076afab6069cc7549@fb.com"},"message":"Simplify order switch operators (#9581)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9581\n\nMostly to simplify code. Should also improve performance but order switch ops\ndon't take much time anyway.\n\nReviewed By: viswanathgs\n\nDifferential Revision: D8909766\n\nfbshipit-source-id: 17a302d5bf4aba2755d88223fc01a41fd72c5919","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/e7ab093d93c968158430ad02cf52a22f829a0816"},{"sha":"c045e969b67e232165c47fdf3507429ce7d2f432","author":{"name":"Sam Gross","email":"48245c485a3f0765c7face6e57b9f7e40c8624a4@fb.com"},"message":"Use qualified name at::Half in Dispatch.h (#9848)\n\nSummary:\nThis makes AT_DISPATCH_ALL_TYPES_AND_HALF valid outside of the at\nnamespace.\n\nSee https://github.com/pytorch/extension-cpp/issues/15\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9848\n\nDifferential Revision: D9006921\n\nPulled By: colesbury\n\nfbshipit-source-id: a6e4f097a9d6fb85c921e1c9b9ea25d0f2db06dc","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/c045e969b67e232165c47fdf3507429ce7d2f432"},{"sha":"dfa0af093d6ff03460a2a7167eed8deed99aca72","author":{"name":"Yi Cheng","email":"cf8d6e16fb635c334cfdb6e855b555a2bfe2b963@fb.com"},"message":"Move predictor into caffe2/caffe2/predictor (#9548)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9548\n\nPull Request resolved: https://github.com/pytorch/translate/pull/157\n\nOne part of refactor predictor. Move all the files into predictor dir.\n\nReviewed By: highker\n\nDifferential Revision: D8845276\n\nfbshipit-source-id: 1e917464b0c8a042f025128a082c784eaa3b7013","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/dfa0af093d6ff03460a2a7167eed8deed99aca72"},{"sha":"a841006353b3b460965832d91443a8e982c12e0f","author":{"name":"Owen Anderson","email":"24a74c757816385a523b6755e302643f8b781853@oculus.com"},"message":"Simplify some code by directly constructing unordered_set from nodes.\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9675\n\nDifferential Revision: D8952196\n\nPulled By: resistor\n\nfbshipit-source-id: 5ef2308fed9f702021f650cf2d241a83d880d359","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/a841006353b3b460965832d91443a8e982c12e0f"},{"sha":"e41eb4332783ce32d26fdf3418688a583a5cc478","author":{"name":"Vishwak Srinivasan","email":"7d9dbaf6fdbe0bc4465fbe69a9c17ceb70dc8fb9@iith.ac.in"},"message":"Remove deprecated masked_copy (#9819)\n\nSummary:\nNo tests are affected by this removal.\n\nCloses https://github.com/pytorch/pytorch/issues/1885 and closes #9817\n\nWhile I was at it, I also fixed #9876 .\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9819\n\nDifferential Revision: D9018126\n\nPulled By: SsnL\n\nfbshipit-source-id: a9142bf4e2403bef05779a097f61fa8b7db04b71","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/e41eb4332783ce32d26fdf3418688a583a5cc478"},{"sha":"eb338878162c9306f2fa473ad4a365733b5356ec","author":{"name":"David Brownell","email":"6ee1517813b24b5d3fcdc766ee7fc479ca389ead@microsoft.com"},"message":"Addressed issue identified by static code analysis: potential buffer … (#9889)\n\nSummary:\n…overrun\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9889\n\nDifferential Revision: D9026278\n\nPulled By: soumith\n\nfbshipit-source-id: ee2ee255f34731ddc581261984c3caf56faa0e12","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/eb338878162c9306f2fa473ad4a365733b5356ec"},{"sha":"aa671ddefacee4abb471e851d5214f508d64f235","author":{"name":"James Sun","email":"de25a7db69865856e53f0c93615999a5b187310f@fb.com"},"message":"Support production models with predictor benchmark (#9855)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9855\n\nSupport production models with predictor benchmark\nTwo new flags are added:\n`--update_prod`: pull production data (netdef, input types, input dims) from Hive and store locally\n`--use_prod`: run benchmark with local production data with the same workload as in production.\nBy default, 300 models will be loaded.\n\nproduction vs benchmark\navg net run time:\n(collected by prod: https://fburl.com/scuba/6lb91zfx and bench: https://fburl.com/ngjj1dc8)\n**prod: `408us` vs bench: `543us`**\n(With prod data distribution, this should be even closer)\n\nframework overhead (as of 2018-07-22):\nprod:\n```\n9.111%    BlackBoxPredictor::Run\n4.602%    SimpleNet::Run\n2.377%    Operator::Run\n1.786%    BlackBoxPredictor::AllocateMemory\n1.372%    Observable::StartAllObservers\n1.358%    Observable::StartObserver\n1.206%    Blob::GetMutable\n```\n\nbench:\n```\n8.577%    BlackBoxPredictor::operator()\n3.276%    SimpleNet::Run\n1.954%    Operator::Run\n1.697%    BlackBoxPredictor::AllocateMemory\n1.477%    Tensor::ShareData\n1.230%    Blob::GetMutable\n1.034%    Observable::StartObserver\n```\n\nReviewed By: yinghai\n\nDifferential Revision: D8942996\n\nfbshipit-source-id: 27355d7bb5a9fd8d0a40195261d13a97fa24ce17","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/aa671ddefacee4abb471e851d5214f508d64f235"},{"sha":"2c1d9e09b89e3094c24eb770f35db09a45b4a877","author":{"name":"Vignesh Ramanathan","email":"d9be9ca3f1b2d450305e034a370ae798faff7dfb@fb.com"},"message":"Support UINT8 for addition data in ImageInputOp (#9901)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9901\n\nAdded support for UINT8 datatype for additional data (prefetching and\noutput) by ImageInputOp\n\nReviewed By: ashwinb\n\nDifferential Revision: D9018964\n\nfbshipit-source-id: f938a8a072c15c0ee521b2f16788c024b08cd37f","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/2c1d9e09b89e3094c24eb770f35db09a45b4a877"},{"sha":"8cb1eef7b9e512b3f2b4f89a5ca58f171fdde87f","author":{"name":"Adam Paszke","email":"71faef99c0ae9d81958d0035c1ce72f9c3888cfe@gmail.com"},"message":"Unify IR operator representation (stop using attributes in the JIT) (#9807)\n\nSummary:\nBased on top of #9763 (first 3 commits belong to that PR). The first commits from this PR are \"Stop using attributes ...\"\n\nI tried to separate the changes into fairly meaningful commits. I can't split them up into smaller PRs, because everything starts working and all tests pass only after the whole sequence, but hopefully this will make reviewing somewhat easier.\n\nKnown issues/regressions/future tasks:\n- `aten::lerp` and `aten::clamp` are no longer fusable\n- `CreateAutodiffSubgraphs` needs a rewrite\n  - It is much more strict now, and will miss a lot of opportunities, especially when viewing ops are involved. Our previous approach was \"ignore the assumption on shape availability in gradient formulas to determine differentiability, and hope that shape prop will be robust enough to actually deliver them before we differentiate\", which obviously doesn't scale well to more complex cases. We should either work on reducing the size dependency of grad formulas (feasible e.g. for `view`/`reshape`, unfeasible for `squeeze`/`unsqueeze`), or make `CreateAutodiffSubgraphs` integrate some kind of \"I could integrate this node into an AD subgraph, but will I be able to infer the shape of its input\" reasoning (kind of like a limited shape prop, that doesn't infer anything, and only tells if it *could* infer something).\n  - It sometimes creates constant-only (or constants + one node) graphs, which is useless\n- Broken `aten::add` in auto-batching, because it gained a non-tensor input. I changed the test for pointwise operations to use `aten::mul` instead, but I needed to disable the LSTM cell test. I'm not sure how scalar constants should be implemented in this case, because I don't fully understand our format. cc: ChunliF\n- Graph import does some hacks to recover type of constants. This code should be removed once we'll gain the ability to export the IR along with value types.\n- There's still a fair amount of dead code that can be removed. I didn't want to make this diff any bigger, and removing it is an easy task.\n- Graph fuser could be improved to use signature matching (possibly using `OperatorSet`) instead of basing on node kinds.\n- Manual constant propagation for the `ListConstruct` node in `torch/onnx/utils.py` should be replaced with a proper constant propagation pass (or we should ensure that the one we have handles at least this case before we remove this code).\n\nzdevito\nPull Request resolved: https://github.com/pytorch/pytorch/pull/9807\n\nReviewed By: ezyang\n\nDifferential Revision: D9004285\n\nPulled By: apaszke\n\nfbshipit-source-id: fe88026a765f6b687354add034c86402362508b7","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/8cb1eef7b9e512b3f2b4f89a5ca58f171fdde87f"},{"sha":"4a192bcc3d297d5934dce2dc46cc11ff6b4baf2c","author":{"name":"Junjie Bai","email":"7c824f2e1c4d8e5c9445dd7ded4e96febed020f7@in.tum.de"},"message":"Rename onnx integration tests file to avoid confusion\n\nSummary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9913\n\nDifferential Revision: D9026787\n\nPulled By: bddppq\n\nfbshipit-source-id: a3e7e79973abc4f5fe163f3e86b24382a1efd082","distinct":false,"url":"https://api.github.com/repos/smessmer/pytorch/commits/4a192bcc3d297d5934dce2dc46cc11ff6b4baf2c"}]}
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