{"push_id":2701743076,"size":43,"distinct_size":43,"ref":"refs/heads/master","head":"3a8b3f585b0562a9f4913373a12b0e92cddf1589","before":"b2fe2a874bade4782aaca5c44bf29e7ff6c39200","commits":[{"sha":"a1810b42ea479ac1cee638a8507d52fc5dc61a3c","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Go: Update generated wrapper functions for TensorFlow ops.\nPiperOrigin-RevId: 203195767","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/a1810b42ea479ac1cee638a8507d52fc5dc61a3c"},{"sha":"1737b824dad3af5681adb76585235ca96c2d57e2","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Add distributed model GetStepSequenceAsync implementation to\ndistributed_runtiume/RpcCollectiveExecutorMgr.\n\nIn a distributed environment WorkerInterface is going to call this\nmethod at the group leader when fielding a GetStepSequence request\nfrom one of the other workers.\n\nPiperOrigin-RevId: 203196543","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/1737b824dad3af5681adb76585235ca96c2d57e2"},{"sha":"bd94b1022074d90a73917f3cd15c0866d79c224d","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Move InterpreterBuilder's destructor to the .cc file.\n\nPiperOrigin-RevId: 203200781","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/bd94b1022074d90a73917f3cd15c0866d79c224d"},{"sha":"fb58f1d287e7210bebc22e0946b969c2ec0303e7","author":{"name":"Brennan Saeta","email":"1d801d19c50290787f73edfa1e666fbb5d8c5b42@google.com"},"message":"[tf.data / Bigtable] Log mutation_status errors.\n\nSome errors returned from the Bigtable client are not proper utf8 strings. As a result, when we construct the errors::Unknown error to return to the client, the resulting error message gets suppressed. In order to ensure that some useful context is always available to users, we log the error message in addition to returning it.\n\nPiperOrigin-RevId: 203203543","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/fb58f1d287e7210bebc22e0946b969c2ec0303e7"},{"sha":"fc61f063cf57c72e11e67d29562c4ed6b87d5145","author":{"name":"Akshay Agrawal","email":"33610bb6aa6c101e6f1b83ab8c32114ae74dc27b@google.com"},"message":"Make sure that that nodes connected by reference/resource edges are colocated.\n\nThe Placer is supposed to guarantee that nodes connected by reference/resource edges are colocated. Prior to this change, this constraint was not enforced for ops that had among their inputs at least two resource/reference tensors with different requested devices.\n\nNote that we might in the near future want to relax this constraint in order to allow, e.g., function call ops to be agnostic to where their DT_RESOURCE inputs live.\n\nPiperOrigin-RevId: 203203579","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/fc61f063cf57c72e11e67d29562c4ed6b87d5145"},{"sha":"774a01fa39cb1f31d4484d9cb82a700d0f70c4e3","author":{"name":"Michael Kuperstein","email":"01c6895c4d26b7d7a9023f68ea4ac54ceb842cb4@google.com"},"message":"Internal change\n\nPiperOrigin-RevId: 203210840","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/774a01fa39cb1f31d4484d9cb82a700d0f70c4e3"},{"sha":"ae5cdb7028df3215d04bdb84c4e87b79f2b62b97","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Automated g4 rollback of changelist 203171335\n\nPiperOrigin-RevId: 203211687","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/ae5cdb7028df3215d04bdb84c4e87b79f2b62b97"},{"sha":"58a61c0a09a9dffbf9d2946d8bacd2adce446f26","author":{"name":"Anjali Sridhar","email":"e035aad70dbec41ad62c90d0166c020b123cb99e@google.com"},"message":"tf.keras sync 2.2.0\n\nPiperOrigin-RevId: 203212643","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/58a61c0a09a9dffbf9d2946d8bacd2adce446f26"},{"sha":"1e7dde8791c535bd09bda9f9ecbe8594aed4f4c6","author":{"name":"Anna R","email":"ea79b6e1b24599611d5cbebff445e3f8620f2c85@google.com"},"message":"I think this should fix the following failure with see in MacOS build:\nerror: no type named 'type' in 'std::__1::enable_if<false, void>'; 'enable_if' cannot be used to disable this declaration\n                 ,typename enable_if<is_convertible<const _U1&, _T1>::value &&\n\nPiperOrigin-RevId: 203216967","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/1e7dde8791c535bd09bda9f9ecbe8594aed4f4c6"},{"sha":"8779f768a3c0fa8d48c25f71d65513c208c77432","author":{"name":"Kay Zhu","email":"d9712593e76dfbf57a93e3247dfb56b03d69ce9f@google.com"},"message":"[TF:XLA] Split literal_util into {literal, literal_util}.\n\nCurrently Literal classes sits in literal_util.{h,cc} instead of literal.{h,cc}.\nIt also contains helper functions that are better fit to be their own separate\nclass/namespace. This change starts this process by moving most static factory\nmethods to LiteralUtil namespace.\n\nPiperOrigin-RevId: 203217065","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/8779f768a3c0fa8d48c25f71d65513c208c77432"},{"sha":"6578bad00e6125f13722ab322658c8569ad3595d","author":{"name":"Asim Shankar","email":"353f486bccb994414888bc877b93c9c72986cfb3@google.com"},"message":"[Java]: Release 1.9.0-rc2\n\nPiperOrigin-RevId: 203218006","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/6578bad00e6125f13722ab322658c8569ad3595d"},{"sha":"3661a14ddfccc3aad48c2aaf1484d84bed3e7261","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Exclude importing tensorflow.contrib.cloud on Windows (internal)\n\nPiperOrigin-RevId: 203232381","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/3661a14ddfccc3aad48c2aaf1484d84bed3e7261"},{"sha":"cead016fe01e8f0ff732a080203b29990d475c98","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Minor performance improvement for ComputeReachability\n\nWe have two versions of HloReachabilityMap::SetReachabilityToUnion where\none of them is slightly more efficient by not returning if the\nreachability have been changed or not. This change migrates the users\nnot caring about the return value to the faster variant.\n\nPiperOrigin-RevId: 203256625","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/cead016fe01e8f0ff732a080203b29990d475c98"},{"sha":"51061e1eae6fdbe1f7af78e1c1952cbce318099a","author":{"name":"Adrian Kuegel","email":"576389c0b07786a91efdf2778233c297d15750c4@google.com"},"message":"Profile SequentialThunks if they represent one HloInstruction.\n\nSequentialThunks are used in two different ways: sometimes as a sequence of\nindividual thunks for different HloInstructions, and sometimes for one\nHloInstruction which consists of several thunks. For the latter, we want\nto measure the total time taken by the HloInstruction. Previously, we would\ninstead measure the time of the last thunk from the SequentialThunk.\n\nPiperOrigin-RevId: 203258617","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/51061e1eae6fdbe1f7af78e1c1952cbce318099a"},{"sha":"014422b97c485253b49d7e99d9e917a5a8cb5fb2","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Begin introducing NUMA support for CPU threads and memory\nby extending the core/platform API with some basic functionality.\nThe new functions allow:\n 1. Determining how many NUMA nodes are available.\n 2. Setting the executing thread to be bound to a particular node,\n    or not bound at all.\n 3. Allocating memory affiliated with a particular node.\n\nThis change introduces the API only, there is not yet a real\nimplementation.\n\nPiperOrigin-RevId: 203283392","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/014422b97c485253b49d7e99d9e917a5a8cb5fb2"},{"sha":"8737cd1ef4f689c34ab37ac88eeb850516059f0e","author":{"name":"Justin Lebar","email":"631d11d9fe908fc8f04b5865032c3043cb48fdfb@google.com"},"message":"[XLA] Make ShapeUtil::PermuteDimensions() properly permute layouts.\n\nAlthough there was no API comment explaining what PermuteDimensions()\nintended to do with layouts, the intent seems to be that if the input\nshape has a layout, then\n\n  TransposeIsBitcast(input_shape, PermuteDimensions(input_shape, perm),\n                     InversePermutation(perm))\n\nis true.\n\nThis was not previously correct.  (I can't really say what the old\nbehavior was, although maybe there's some clever interpretation of what\nit used to do.)\n\nPiperOrigin-RevId: 203290794","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/8737cd1ef4f689c34ab37ac88eeb850516059f0e"},{"sha":"548601aee34f3eb0e6857b5ce6df25db1b50a4b4","author":{"name":"A. Unique TensorFlower","email":"746aced590a184ef4169166e753f7c211e32e5fc@tensorflow.org"},"message":"Automated g4 rollback of changelist 203283392\n\nPiperOrigin-RevId: 203302131","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/548601aee34f3eb0e6857b5ce6df25db1b50a4b4"},{"sha":"eb8a110e52a8e8ed7b9db48e01115d3110e918c2","author":{"name":"Bixia Zheng","email":"4733e76aa05f451fa375889c85b599266aa9962f@google.com"},"message":"[XLA:GPU] Enhance the tiled 0-2-1 transpose algorithm to handle fusion.\n\nAdd class TiledParameterInfo to provide information for FusedIrEmitter to read\nthe content of a tiled parameter from the tile buffer instead of the original\ninput memory.\n\nReimplement the tiled 0-2-1 transpose algorithm for copy instructions only in a\nmore general way so that it can handle both fusion instructions and copy\ninstructions.\n\nThe original tiled 0-2-1 transpose implementation incorrectly used\n(tile_size+1) rows for a tile buffer to reduce share memory bank conflicts while\nit should be (tile_size+1) column instead. This is a performance issue and is\nfixed in the new implementation.\n\nThe original tiled 0-2-1 transpose implementation did not generate LLVM alias\nmeta data for the loads and stores of the tensors. This was due to a bug where\nfunction IrArray::CastToShape miss copying meta data to the new IrArray\nobject. This is also a performance issue and is fixed in this change.\n\nModified KernelSupportLibrary to support emitting an if-stmt with a given\nbranch name prefix.\n\nAdd test cases to test the new implementation.\n\nPiperOrigin-RevId: 203310403","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/eb8a110e52a8e8ed7b9db48e01115d3110e918c2"},{"sha":"9103612c1d30a9e77bd1af83a8bc036dcee84b60","author":{"name":"Brennan Saeta","email":"1d801d19c50290787f73edfa1e666fbb5d8c5b42@google.com"},"message":"[tf.data / Bigtable] Refactor BUILD file\n\nPiperOrigin-RevId: 203319567","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/9103612c1d30a9e77bd1af83a8bc036dcee84b60"},{"sha":"2c130a0d252741d2c0ce1e0d815ac1d87d53d6e3","author":{"name":"Derek Murray","email":"d38751ee48a144dccd4949c37af26aa95befa279@google.com"},"message":"Improve the latency of small `tf.concat()` operations.\n\nAvoid copying each input `Tensor` object from the `OpInputList`, and\ninstead take a const reference. This avoids the need to run the\n`Tensor` destructor at the end of each iteration.\n\nPiperOrigin-RevId: 203326683","distinct":true,"url":"https://api.github.com/repos/mypopydev/tensorflow/commits/2c130a0d252741d2c0ce1e0d815ac1d87d53d6e3"}]}
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