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* Clean up the build_xla_ops to use the generated C++ TF op wrappers.Gravatar Sanjoy Das2018-10-01
| | | | | | | | | | | | | | | | | | | | | This cleanup will make the future CL implementing lazy compilation simpler. Includes some supporting changes: - Teach NewInternalScope to create a scope that doesn't do shape inference. We need this because we don't have a ShapeRefiner that has been run over the entire graph available in the build_xla_ops pass. - Add a WithAssignedDevice modifier to tensorflow::Scope. - Make cc_op_gen write out an Operation field for nodes which may not necessarily have any outputs. We already did this in most cases, but we weren't doing it for nodes that have possibly-empty list outputs. - Minor change renaming ops/xla_jit_op.cc to ops/xla_jit_ops.cc, now that we have more than one XLA JIT op. PiperOrigin-RevId: 215293817
* fix the comparison error when building a CPP API applicationGravatar Sangjung Woo2018-09-03
| | | | | | | | | | | | When building a CPP API application with "-Wall -Werror" option , `error: comparison between signed and unsigned integer expressions' occurs since return type of num_elements() is 'int64' instead of 'size_t' in ops.h to express -1. This patch fixes this bug by explicit type casting. * related issue: https://github.com/tensorflow/tensorflow/issues/20428 Signed-off-by: Sangjung Woo <sangjung.woo@samsung.com>
* Removed redundant std::string -> string conversions.Gravatar A. Unique TensorFlower2018-08-28
| | | | PiperOrigin-RevId: 210596417
* Move FindInputArg() for ApiDef::Arg to op_def_util.cc and cleanup Python/c++ ↵Gravatar Nick Kreeger2018-08-17
| | | | | | | | references. This method is currently duplicated in Python code and will be used for TypeScript generation. PiperOrigin-RevId: 209207139
* Handle NaN results when verifying gradients.Gravatar A. Unique TensorFlower2018-08-06
| | | | | | | | This change returns NaN as the maximum error if any gradient entry is NaN. This avoids masking gradient implementation errors in tests that don't expect to see NaN results. PiperOrigin-RevId: 207551265
* Merge pull request #21021 from kbsriram:tf-image-gradGravatar TensorFlower Gardener2018-08-03
|\ | | | | | | PiperOrigin-RevId: 207350813
| * Add C++ gradients for some image operators.Gravatar KB Sriram2018-07-21
|/ | | | | | | | | | | | Added gradients and tests for - ResizeBilinear - ResizeBicubic - ResizeNearestNeighbor Note: Some of the tests are for the operator itself rather than the gradient, paralleling existing tests in image_grad.py See https://github.com/tensorflow/tensorflow/issues/21019
* [C API]: Bugfix for TF_AddGradients.Gravatar Asim Shankar2018-06-26
| | | | | | | | | | | | | | | | | | | | TF_AddGradients could create nodes in the graph with names that conflicted with other nodes in the graph. This would most clearly happen if TF_AddGradients() was called twice on the same graph, and could also happen if there were other nodes in the graph that happened to have "gradients" as a prefix of their name. Fix that. The added test in c_api_test.cc would fail in the call to TF_SessionRun() with Node 'gradients/OnesLike' is not unique without the changes to c_api.cc and c_api_internal.h While at it, also fixed a possible name collision bug when using the C++ API to constructor graphs (using Scope). Thanks @karllessard for pointing this out. PiperOrigin-RevId: 202087996
* Fix 'cc_op_gen' to use static storage for constant arrays.Gravatar Ilya Biryukov2018-06-11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | Previously, the generate would emit code like this: struct Attrs { ArraySlice<int> dilations_ = {1, 1, 1, 1}; }; This code is incorrect, since the array slice references a temporary object that dies after initialization finishes. After this change change the generator will produce static functions to initialize the values: struct Attrs { ArraySlice<int> dilations_ = Default_dilations(); private: ArraySlice<int> Default_dilations() { static int kStorage[] = {1, 1, 1, 1}; return ArraySlice<int>(kStorage); } }; Presumably, it used to work because all compilers chose to use static storage in those cases anyway. However, new versions of clang tend to miscompile this code, causing test failures. (This error was found when trying to upgrade our clang revision from r328903 to r331746). PiperOrigin-RevId: 200110952
* Replaced calls to tensorflow::StringPiece::ToString with std::string ↵Gravatar A. Unique TensorFlower2018-05-02
| | | | | | | | | | conversions. That is, instances of sp.ToString() are replaced with std::string(sp). This will allow tensorflow::StringPiece::ToString to be removed, which is necessary before it can be replaced with absl::string_view. PiperOrigin-RevId: 195188185
* Replaced calls to deprecated tensorflow::StringPiece methods with theirGravatar A. Unique TensorFlower2018-03-27
| | | | | | | | tensorflow::str_util equivalents. This will allow the deprecated methods to be removed. PiperOrigin-RevId: 190650553
* Automated g4 rollback of changelist 189110935Gravatar A. Unique TensorFlower2018-03-15
| | | | PiperOrigin-RevId: 189224522
* Automated g4 rollback of changelist 189060958Gravatar A. Unique TensorFlower2018-03-14
| | | | PiperOrigin-RevId: 189110935
* Move StringPieceHasher from stringpiece.h to hash.h (where there is already ↵Gravatar A. Unique TensorFlower2018-03-14
| | | | | | a hash<StringPiece>). PiperOrigin-RevId: 189060958
* Avoid capturing unused variables in lambda functionsGravatar Benoit Steiner2018-03-12
| | | | PiperOrigin-RevId: 188747641
* Correct op::Attr usage in C++ gradient implementations.Gravatar A. Unique TensorFlower2018-03-05
| | | | | | | | | Also enabled TF_MUST_USE_RESULT for the generated Attr API, so we can catch any new errors early. Fixes #17360 PiperOrigin-RevId: 187925761
* Remove THIRD_PARTY_ from #include guardsGravatar Sanjoy Das2018-01-24
| | | | | | They don't make sense in the open source repository. PiperOrigin-RevId: 183140889
* Removing op_gen_overrides.proto and references. Overrides in ↵Gravatar Anna R2018-01-09
| | | | | | op_gen_overrides.pbtxt are a part of tensorflow/core/api_def/base_api/. PiperOrigin-RevId: 181386873
* Remove using directives. Test appertaining to ops have been moved into ↵Gravatar A. Unique TensorFlower2018-01-02
| | | | | | | | namespace tensorflow::ops; all other tests now use explicit using-declarations. Some tests are now using unnamed namespaces more aggressively to make as many names internal as possible. PiperOrigin-RevId: 180564422
* Automated g4 rollback of changelist 175593063Gravatar A. Unique TensorFlower2017-11-20
| | | | PiperOrigin-RevId: 176445215
* Remove unused inclusionsGravatar A. Unique TensorFlower2017-11-20
| | | | PiperOrigin-RevId: 176423279
* Provide an option to use ApiDef instead of OpGenOverrides when generating ↵Gravatar Anna R2017-11-17
| | | | | | C++ API. Also, updating UpdateDocs method to ApiDef to replace names in docs. PiperOrigin-RevId: 176167953
* Automated g4 rollback of changelist 175563786Gravatar A. Unique TensorFlower2017-11-13
| | | | PiperOrigin-RevId: 175593063
* Moved tensorflow::StringPiece::Hasher out of tensorflow::StringPiece and ↵Gravatar A. Unique TensorFlower2017-11-13
| | | | | | renamed it tensorflow::StringPieceHasher. This allows tensorflow::StringPiece to be more easily replaced with absl::string_view (which does not contain a Hasher struct). PiperOrigin-RevId: 175563786
* Fix c++ gradients issue where multiple dependent outputs result in incorrect ↵Gravatar Suharsh Sivakumar2017-10-04
| | | | | | | | | | answer. The issue is that we incorrectly calculate the pending num_expected_backprops for outputs nodes when one output transitively depends on another. this is because we use output nodes as an indicator of when we need to end our traversal. Instead we should only use output nodes that don't transitively get consumed by other output nodes as end indicators for our traversal. This change implements that fix. Fixes #13190 PiperOrigin-RevId: 170971937
* C++ while loop gradient cleanupGravatar Skye Wanderman-Milne2017-09-28
| | | | PiperOrigin-RevId: 170390543
* Basic while loop gradient functionality in C++Gravatar Skye Wanderman-Milne2017-09-27
| | | | | | | | | | | | This change introduces the basic framework to create the gradient graph of a while loop using the C++ API. This supports building the gradient graph as long as the body function of the while loop contains no ops whose gradient function requires a stack. In other words, it doesn't support gradient functions that use the input values to the op (e.g. add will work, but multiply will not). It also doesn't support nested while loops, and doesn't detect all error cases. PiperOrigin-RevId: 170243281
* Merge changes from github.Gravatar Shanqing Cai2017-09-25
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | END_PUBLIC --- Commit 1e1b3d902 authored by Pete Warden<pete@petewarden.com> Committed by gunan<gunan@google.com>: Changed output directory for Pi CI build to fix permissions problem with nightlies (#13257) * Fix for RTLD_GLOBAL breakage of Pi builds, and removed Eigen version change for Pi that's no longer needed * Fixed Pi Zero OpenBLAS build problems and tidied up directories used * More robust checks in Pi build script * Changed output directory for Pi CI build to fix permissions problem --- Commit fe3a2e65c authored by Yan Facai (???)<facai.yan@gmail.com> Committed by drpngx<drpngx@users.noreply.github.com>: check invalid string type for dest_nodes in extract_sub_graph (#13057) * BUG: check str type * TST: add unit test * CLN: remove list check * CLN: use warning * CLN: 2 indent * CLN: raise TypeError if not list * CLN: check string only --- Commit 225ab7629 authored by Jean Wanka<jm.wanka@gmail.com> Committed by Jean Wanka<jm.wanka@gmail.com>: Fix polynomial decay with cycle for global step=0 For polynomial decay with cycle=True the learning rate at step 0 becomes NaN, because in the process of calculating it we devide by 0. This change should fix it, by setting the multiplier for the decay steps to one for global_step=0. --- Commit 286f57061 authored by Bjarke Hammersholt Roune<broune@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Make Service::TransferToClient not attempt to manipulate the literal when the transfer failed, preventing a crash and allowing the caller to see the reason for the failed transfer. PiperOrigin-RevId: 169770126 --- Commit e0501bc4d authored by Yong Tang<yong.tang.github@outlook.com> Committed by Shanqing Cai<cais@google.com>: Fix GRUBlockCell parameter naming inconsistency (#13153) * Fix GRUBlockCell parameter naming inconsistency This fix tries to fix the issue in 13137 where parameter `cell_size` is used instead of `num_units`. This is inconsistent with other RNN cells. This fix adds support of `num_units` while at the same time maintains backward compatiblility for `cell_size`. This fix fixes 13137. Signed-off-by: Yong Tang <yong.tang.github@outlook.com> * Add `@deprecated_args` for 'cell_size' in `GRUBlockCell` This commit adds `@deprecated_args` for 'cell_size' in `GRUBlockCell` Signed-off-by: Yong Tang <yong.tang.github@outlook.com> * Address review comment Signed-off-by: Yong Tang <yong.tang.github@outlook.com> --- Commit 02a2eba05 authored by Pete Warden<pete@petewarden.com> Committed by gunan<gunan@google.com>: Fix for RTLD_GLOBAL breakage of Pi builds, and removed Eigen version change that's no longer needed (#13251) * Fix for RTLD_GLOBAL breakage of Pi builds, and removed Eigen version change for Pi that's no longer needed * Fixed Pi Zero OpenBLAS build problems and tidied up directories used * More robust checks in Pi build script --- Commit 8ef722253 authored by Sanjoy Das<sanjoy@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Remove a redundant setName. The EmitComputation should have emitted a function with the right name, so use a CHECK instead. PiperOrigin-RevId: 169764856 --- Commit 1b94147dc authored by Neal Wu<wun@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Fix broken GitHub links in tensorflow and tensorflow_models resulting from The Great Models Move (a.k.a. the research subfolder) PiperOrigin-RevId: 169763373 --- Commit b1ada5f0c authored by Justine Tunney<jart@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Fix TensorBoard python -m invoke in docs PiperOrigin-RevId: 169758752 --- Commit 2957cd894 authored by Mustafa Ispir<ispir@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Local run option of estimator training. PiperOrigin-RevId: 169756384 --- Commit 1dc2fe7ac authored by Gunhan Gulsoy<gunan@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: BEGIN_PUBLIC Automated g4 rollback of changelist 166264198 PiperOrigin-RevId: 169998124
* Fix tensorflow::Scope documentation: angle brackets in comments don't play ↵Gravatar Max Galkin2017-09-22
| | | | | | | well with HTML docs. See: https://www.tensorflow.org/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope_1a726021aa3104fec02353e8713f1e5b63 PiperOrigin-RevId: 169718650
* Extend c++ gradient_checker to complex types.Gravatar A. Unique TensorFlower2017-09-12
| | | | PiperOrigin-RevId: 168392949
* Merge changes from github.Gravatar A. Unique TensorFlower2017-09-06
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | END_PUBLIC --- Commit 607816029 authored by Eugene Brevdo<ebrevdo@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Extended ScratchSpace to expose its underlying scratch tensor object. PiperOrigin-RevId: 167649551 --- Commit db43fe68e authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Add fast math attributes to all generated methods when fast math enabled. RELNOTES: n/a PiperOrigin-RevId: 167646637 --- Commit aebe8cc6f authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Call HloComputation.Accept instead of HloInstruction.Accept to get all instructions profiled. RELNOTES: n/a PiperOrigin-RevId: 167640259 --- Commit 0ab137cd8 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: BEGIN_PUBLIC Automated g4 rollback of changelist 167604306 PiperOrigin-RevId: 167800256
* Introduce C++ API while loop builder methodGravatar Skye Wanderman-Milne2017-08-29
| | | | | | | | | | | | | | | | | | This change adds a new function, BuildWhileLoop(), that constructs a while loop. BuildWhileLoop() takes functions that build the cond and body graphs, similar to the Python while_loop function. It also switches the C API to use this new function in order to reduce code duplication. This is in preparation for while loop gradients, which are also implemented in the C++ API (along with the other gradient code). I didn't write unit tests for BuildWhileLoop, instead relying on the current C API while loop tests. This change also disables while loop creation on Android to avoid pulling in extra C++ dependencies. PiperOrigin-RevId: 166849829
* C++ API: run shape inference as nodes are constructedGravatar Skye Wanderman-Milne2017-08-15
| | | | | | | | | | | | | | | | | | | | | | | | Here's an example of the new generated code: AddN::AddN(const ::tensorflow::Scope& scope, ::tensorflow::InputList inputs) { if (!scope.ok()) return; auto _inputs = ::tensorflow::ops::AsNodeOutList(scope, inputs); if (!scope.ok()) return; ::tensorflow::Node* ret; const auto unique_name = scope.GetUniqueNameForOp("AddN"); auto builder = ::tensorflow::NodeBuilder(unique_name, "AddN") .Input(_inputs) ; scope.UpdateBuilder(&builder); scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); if (!scope.ok()) return; scope.UpdateStatus(scope.DoShapeInference(ret)); this->sum = Output(ret, 0); } Enabling shape inference unfortunately broke many tests. I fixed some of them, but for others I introduced a Scope::DisabledShapeInferenceScope() static method that returns a scope that doesn't perform shape inference. Eventually we should fix the tests that use this and remove it. PiperOrigin-RevId: 165378429
* C++ API: move Scope::Impl to internal header fileGravatar Skye Wanderman-Milne2017-08-03
| | | | | | | | This is in preparation to expose internal state to internal code that needs it, e.g. the scope's name and shape refiner. There are no code changes besides the move. PiperOrigin-RevId: 164202927
* Minor tweaks to avoid unnecessary copiesGravatar A. Unique TensorFlower2017-07-25
| | | | PiperOrigin-RevId: 163101160
* Fix bug in C++ gradient computation where multi-output nodes may not have ↵Gravatar Skye Wanderman-Milne2017-07-20
| | | | | | | | | | | | | | | | been processed. If a subset of the outputs of a multi-output node were included in the 'inputs' argument to AddSymbolicGradients(), they would not be populated in 'grad_outputs'. This is because the pending count of the multi-output node would never go to zero (unless the backprop traversal happened to visit all the output edges, even though not all were explicitly requested). This change fixes the bug by processing any remaining requested edges after finishing the traversal. PiperOrigin-RevId: 162653892
* Merge changes from github.Gravatar Jonathan Hseu2017-07-19
| | | | | | | | | | | | | | | | | END_PUBLIC --- Commit daa67ad17 authored by Jonathan Hseu<vomjom@vomjom.net> Committed by Frank Chen<frankchn@gmail.com>: Remove unittest import (#11596) --- Commit 491beb74c authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: BEGIN_PUBLIC Automated g4 rollback of changelist 162423171 PiperOrigin-RevId: 162541442
* Merge changes from github.Gravatar Shanqing Cai2017-07-10
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | END_PUBLIC --- Commit d0f53f77f authored by Penghao Cen<scorpiocph@gmail.com> Committed by Shanqing Cai<cais@google.com>: Minor fix typo (#11323) --- Commit 02fcf564e authored by Chris Song<sjhshy@gmail.com> Committed by Chris Song<sjhshy@gmail.com>: Fix misspells. --- Commit 764c9b6b4 authored by Louis Tiao<ltiao@users.noreply.github.com> Committed by GitHub<noreply@github.com>: Fixed typo in docstring --- Commit f8cd1283e authored by Shanqing Cai<cais@google.com> Committed by Shanqing Cai<cais@google.com>: Chaser --- Commit 01383b946 authored by Shanqing Cai<cais@google.com> Committed by Shanqing Cai<cais@google.com>: Adapt TensorFlowTestCase.setUp() to new reset_default_graph() semantics Avoid calling reset_default_graph() directly to prevent exceptions in cases where test methods error out from within nested graph contexts, which can leave _default_graph_stack non-empty in certain Python versions. --- Commit 0ffc37890 authored by Amit Patankar<amitpatankar@google.com> Committed by Amit Patankar<amitpatankar@google.com>: Removing second declaration of functions. --- Commit f9c9cacb0 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Refactor ElementalIrEmitter's slice index finding code into IrArray::Index::SourceIndexOfSlice(). PiperOrigin-RevId: 161140653 --- Commit ba297aec9 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Update ops-related pbtxt files. PiperOrigin-RevId: 161138258 --- Commit 68d666737 authored by Alexandre Passos<apassos@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Fixes a reentrant lock issue with tensors using ndarray memory which uses tensor memory. PiperOrigin-RevId: 161137788 --- Commit a2ee8bca3 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Add support for int8 x int8 -> int32 matrix multiplication via cublasGemmEx to stream_executor. PiperOrigin-RevId: 161137741 --- Commit 755fa7b50 authored by Mark Daoust<markdaoust@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Block generate_test, and docs generating from running in python3. - Doc generation is currently unsupported in python3 - These both end in errors in python 3.5.1+ PiperOrigin-RevId: 161137467 --- Commit 97cbcac45 authored by Peter Hawkins<phawkins@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: [TF:XLA] Fix failure in functionalize_control_flow rewrite for Enter nodes that are unused. Make sure we ignore such nodes without producing an error. PiperOrigin-RevId: 161136545 --- Commit dabcb60bc authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: [XLA] Add reasonable error messages to Builder::Build for bad parameter numbers. PiperOrigin-RevId: 161136262 --- Commit 0cbd249e8 authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Add complex tensors support to `matrix_determinant`. PiperOrigin-RevId: 161132422 --- Commit 335f1f14d authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Extend static shape inference for SparseTensors with dense_shapes constructed using slicing. PiperOrigin-RevId: 161132391 --- Commit 53604916e authored by Jianwei Xie<xiejw@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Fixed the missing labels test in TPUEstimator. PiperOrigin-RevId: 161131282 --- Commit 9f57dc8dd authored by Bruno Rosa<bruno.rosa@eldorado.org.br> Committed by Bruno Rosa<bruno.rosa@eldorado.org.br>: Use mcpu instead of march for ppc64le march is not support by gcc on ppc64le --- Commit 7d5c74a9c authored by Skye Wanderman-Milne<skyewm@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Move duplicate detection logic from Graph to FunctionLibraryDefinition Turns out this is more useful, since there are many function libraries that don't belong to a graph. This will be used in a future change. Note that this maintains the current behavior of Graph. In addition, updates FunctionDefsEqual() to handle unset attr entries (I ran into this when using this in said future change). PiperOrigin-RevId: 161126628 --- Commit 2caec3af1 authored by Shanqing Cai<cais@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Disable more timeseries py tests failing in OSS PIP GPU builds PiperOrigin-RevId: 161124799 --- Commit 0b5cce367 authored by Eugene Brevdo<ebrevdo@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Get TopK op working on GPU again. Extend using cub's radix sort. 1. Undo rollback of Andreas Kirsch's initial implementation. 2. Use cub segmented radix sort if Andreas' heap-based impl for large k and small num_cols (thresholds of k=100, n=1000 determined empirically). 3. Use cub segmented radix sort if k == num_cols (this case is always faster). 4. Added benchmarks. Benchmarks show that the GPU implementation is up to 3x slower for small k but can be 10x faster for large num_cols and k. Benchmarks: Benchmark: m_128_n_10_k_5_use_gpu_False wall_time: 0.000166 s Throughput: 0.0077 GB/s Benchmark: m_128_n_10_k_5_use_gpu_True wall_time: 0.000796 s Throughput: 0.00161 GB/s Benchmark: m_128_n_10_k_9_use_gpu_False wall_time: 0.00017 s Throughput: 0.00751 GB/s Benchmark: m_128_n_10_k_9_use_gpu_True wall_time: 0.000796 s Throughput: 0.00161 GB/s Benchmark: m_128_n_10_k_10_use_gpu_False wall_time: 0.00017 s Throughput: 0.00753 GB/s Benchmark: m_128_n_10_k_10_use_gpu_True wall_time: 0.000775 s Throughput: 0.00165 GB/s Benchmark: m_128_n_100_k_1_use_gpu_False wall_time: 0.000155 s Throughput: 0.0826 GB/s Benchmark: m_128_n_100_k_1_use_gpu_True wall_time: 0.000796 s Throughput: 0.0161 GB/s Benchmark: m_128_n_100_k_50_use_gpu_False wall_time: 0.000247 s Throughput: 0.0519 GB/s Benchmark: m_128_n_100_k_50_use_gpu_True wall_time: 0.0008 s Throughput: 0.016 GB/s Benchmark: m_128_n_100_k_99_use_gpu_False wall_time: 0.000261 s Throughput: 0.049 GB/s Benchmark: m_128_n_100_k_99_use_gpu_True wall_time: 0.000794 s Throughput: 0.0161 GB/s Benchmark: m_128_n_100_k_100_use_gpu_False wall_time: 0.000239 s Throughput: 0.0536 GB/s Benchmark: m_128_n_100_k_100_use_gpu_True wall_time: 0.000777 s Throughput: 0.0165 GB/s Benchmark: m_128_n_1000_k_1_use_gpu_False wall_time: 0.000324 s Throughput: 0.395 GB/s Benchmark: m_128_n_1000_k_1_use_gpu_True wall_time: 0.000916 s Throughput: 0.14 GB/s Benchmark: m_128_n_1000_k_10_use_gpu_False wall_time: 0.00042 s Throughput: 0.305 GB/s Benchmark: m_128_n_1000_k_10_use_gpu_True wall_time: 0.000902 s Throughput: 0.142 GB/s Benchmark: m_128_n_1000_k_500_use_gpu_False wall_time: 0.0011 s Throughput: 0.116 GB/s Benchmark: m_128_n_1000_k_500_use_gpu_True wall_time: 0.00097 s Throughput: 0.132 GB/s Benchmark: m_128_n_1000_k_990_use_gpu_False wall_time: 0.00133 s Throughput: 0.0962 GB/s Benchmark: m_128_n_1000_k_990_use_gpu_True wall_time: 0.000993 s Throughput: 0.129 GB/s Benchmark: m_128_n_1000_k_1000_use_gpu_False wall_time: 0.00102 s Throughput: 0.126 GB/s Benchmark: m_128_n_1000_k_1000_use_gpu_True wall_time: 0.000964 s Throughput: 0.133 GB/s Benchmark: m_128_n_10000_k_10_use_gpu_False wall_time: 0.002 s Throughput: 0.64 GB/s Benchmark: m_128_n_10000_k_10_use_gpu_True wall_time: 0.00288 s Throughput: 0.445 GB/s Benchmark: m_128_n_10000_k_100_use_gpu_False wall_time: 0.00233 s Throughput: 0.549 GB/s Benchmark: m_128_n_10000_k_100_use_gpu_True wall_time: 0.00325 s Throughput: 0.394 GB/s Benchmark: m_128_n_10000_k_5000_use_gpu_False wall_time: 0.0127 s Throughput: 0.101 GB/s Benchmark: m_128_n_10000_k_5000_use_gpu_True wall_time: 0.00381 s Throughput: 0.336 GB/s Benchmark: m_128_n_10000_k_9900_use_gpu_False wall_time: 0.015 s Throughput: 0.0853 GB/s Benchmark: m_128_n_10000_k_9900_use_gpu_True wall_time: 0.00438 s Throughput: 0.292 GB/s Benchmark: m_128_n_10000_k_10000_use_gpu_False wall_time: 0.0104 s Throughput: 0.123 GB/s Benchmark: m_128_n_10000_k_10000_use_gpu_True wall_time: 0.00427 s Throughput: 0.3 GB/s Benchmark: m_128_n_100000_k_100_use_gpu_False wall_time: 0.0148 s Throughput: 0.865 GB/s Benchmark: m_128_n_100000_k_100_use_gpu_True wall_time: 0.0262 s Throughput: 0.488 GB/s Benchmark: m_128_n_100000_k_1000_use_gpu_False wall_time: 0.0201 s Throughput: 0.636 GB/s Benchmark: m_128_n_100000_k_1000_use_gpu_True wall_time: 0.0263 s Throughput: 0.486 GB/s Benchmark: m_128_n_100000_k_50000_use_gpu_False wall_time: 0.214 s Throughput: 0.0599 GB/s Benchmark: m_128_n_100000_k_50000_use_gpu_True wall_time: 0.0322 s Throughput: 0.398 GB/s Benchmark: m_128_n_100000_k_99000_use_gpu_False wall_time: 0.262 s Throughput: 0.0489 GB/s Benchmark: m_128_n_100000_k_99000_use_gpu_True wall_time: 0.0377 s Throughput: 0.34 GB/s Benchmark: m_128_n_100000_k_100000_use_gpu_False wall_time: 0.118 s Throughput: 0.108 GB/s Benchmark: m_128_n_100000_k_100000_use_gpu_True wall_time: 0.0365 s Throughput: 0.351 GB/s END_PUBLIC BEGIN_PUBLIC BEGIN_PUBLIC Automated g4 rollback of changelist 157169178 PiperOrigin-RevId: 161476569
* Prepare to remove a bunch of proto.h includes from tensorflow/core headersGravatar Geoffrey Irving2017-06-29
| | | | | | | | | | | | The goal is to make kernels mostly independent of proto headers, which will let us lock down our .so imports. This CL does not remove any actual headers, but changes a bunch of files so that header removal is possible in a followup CL. It also marks the headers that will be removed with // TODO(b/62899350): Remove RELNOTES: n/a PiperOrigin-RevId: 160552878
* Minor cleanup: remove some unused inclusions and dependencies, clean up ↵Gravatar A. Unique TensorFlower2017-06-12
| | | | | | parameters and arguments PiperOrigin-RevId: 158712904
* Change function parameters to references to avoid copying, or otherwise move ↵Gravatar A. Unique TensorFlower2017-06-02
| | | | | | from function parameters when moving reduces the amount of copying. PiperOrigin-RevId: 157867333
* Preallocate vector storage when the ultimate vector size is known in advanceGravatar A. Unique TensorFlower2017-06-01
| | | | PiperOrigin-RevId: 157724431
* Merge changes from github.Gravatar A. Unique TensorFlower2017-05-18
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | END_PUBLIC --- Commit c2b8927f2 authored by Dandelion Man?<dandelion@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Fix another d3v4 regression in the graph visualizer. PiperOrigin-RevId: 156343038 --- Commit 170f0b350 authored by Peter Hawkins<phawkins@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: [TF:XLA] Add XLA implementation of ResourceStridedSliceAssign. PiperOrigin-RevId: 156341053 --- Commit 1390dd68f authored by Vijay Vasudevan<vrv@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: When Op Type is not registered, log the hostname of the machine that it is running on in the error message, since the message could be routed back during a failure on a remote binary, and it is hard to tell which machine it came from. Ideally, we'd somehow log the name of the binary running instead, but we don't have a function to get that right now. PiperOrigin-RevId: 156337679 --- Commit 9ca8a151b authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Internal change. PiperOrigin-RevId: 156335942 --- Commit 40255434c authored by Martin Wicke<wicke@google.com> Committed by TensorFlower Gardener<gardener@tensorflow.org>: Deprecate contrib/learn/dataframe. To be removed June 15. PiperOrigin-RevId: 156333930 --- Commit 7f71b7fbe authored by A. Unique TensorFlower<gardener@tensorflow.org> Committed by TensorFlower Gardener<gardener@tensorflow.org>: BEGIN_PUBLIC Automated g4 rollback of changelist 156123287 PiperOrigin-RevId: 156503903
* Automated g4 rollback of changelist 156251356Gravatar Geoffrey Irving2017-05-17
| | | | PiperOrigin-RevId: 156315860
* Automated g4 rollback of changelist 156244933Gravatar Geoffrey Irving2017-05-16
| | | | PiperOrigin-RevId: 156251356
* Reduce direct references to NodeDef in favor of Node and AttrSliceGravatar Geoffrey Irving2017-05-16
| | | | | | | | This is one step towards replacing in-memory use of NodeDef with a customized NodeInfo class. There are still quite a few Node::def() references, but far fewer than before. Those remaining require more work, either because they are part of kernel registration (which is a bunch of functions), copy and modify the NodeDef, etc. Follow-on CLs will remove more. RELNOTES: n/a PiperOrigin-RevId: 156244933
* Remove unnecessary copies of value parameters.Gravatar Peter Hawkins2017-05-10
| | | | PiperOrigin-RevId: 155511618
* Remove all 64/32 bit warnings in tensorflow/ccGravatar Suharsh Sivakumar2017-04-19
| | | | Change: 153637886
* Add C++ gradients to c_api.Gravatar Suharsh Sivakumar2017-04-13
| | | | | | | | | | | #6268 This CL does the following: (1) Adds TF_AddGradients function to C_API which adds gradient nodes for the specified inputs. (2) Adds internal constructor for Scope, need to create a scope from an existing graph in the c_api. (3) Adds constructor for AddSymbolicGradients that assumes OnesLike when grad_inputs aren't provided. (4) Improves error message when gradients aren't provided. Change: 153092774
* Change Placeholder to support partial shapes and enforce scalar shapes.Gravatar Vijay Vasudevan2017-04-10
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Adds tests; testScalar failed before with the original placeholder because it treated [] as "?" instead of scalar. Now you can actually specify [] and it means 'scalar'. Added a backwards compatibility test using a graph_def generated from a previous tf version. RELNOTES: tf.placeholder can represent scalar shapes and partially known shapes accurately. Note, this change can break already buggy programs because it makes placeholder shape handling more consistent across graph serializations. Note: There are some buggy cases where this change can break a buggy pipeline: namely those that serialize a graph using an unknown shape (e.g., [None, 10] in a tf.placeholder, but then reload the graph using import_graph_def and feed it a different shape. Prior to this change, serializing the graph_def loses the [None, 10] shape requirement, so you can feed anything you want. This change makes it so that you serialize the graph with [None, 10], and so when you reload it, it would fail if you fed it a different shape. In these cases, the fix is to correct the original placeholder shape to match what you feed it, which is not a bug in TF but in the user's program. Note 2: A python user that did tf.placeholder(shape=[]) would get scalar checking in the same process due to python shape inference code. However, a C++ user that did Placeholder(shape=[]) would not have gotten scalar shape checking; a C++ program that passed Placeholder(shape=[]) that expects to interpret this as "UnknownShape" would break -- however, that user could have already used an {unknown_shape: true} proto, and should not have expected the legacy behavior. Backwards compatibility: Old graphs that have shape = {} in the proto will also have a graph_def_version <= 21, so the default value of shape prior to this change will be interpreted by new binaries as "UnknownShape" just as before. Forwards compatibility: new graphs will produce, by default, shape={ unknown rank: true}; old binaries will use PartialTensorShape's parsing code to parse that proto into an object whose shape.dims() <= 0, and so these binaries will continue to interpret the default shape as "unknown shape" without crashing and without producing new errors. Fixes #9103 Change: 152751019
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