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path: root/tensorflow/python/kernel_tests/matrix_inverse_op_test.py
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* Add tf.BenchmarkConfig that returns a session config appropriate for ↵Gravatar A. Unique TensorFlower2018-10-08
| | | | | | benchmarking. At the moment, it returns a default config with only Grappler dependency optimizer disabled. Many benchmarks wrap the subgraph they want to time in control_flow_ops.group() to avoid including the overhead of copying the output back to the Python client in the measurement. In the graph, this only adds a control dependency between the subgraph output and the fetch node, which in turn (often) causes the dependency optimizer to turn all nodes in the graph into no-ops. PiperOrigin-RevId: 216242463
* Move from deprecated self.test_session() to self.cached_session().Gravatar A. Unique TensorFlower2018-09-13
| | | | | | | | self.test_session() has been deprecated in 9962eb5e84b15e309410071b06c2ed2d6148ed44 as its name confuses readers of the test. Moving to cached_session() instead which is more explicit about: * the fact that the session may be reused. * the session is not closed even when doing a "with self.test_session()" statement. PiperOrigin-RevId: 212766976
* * Add mechanism to CudaSolver for capturing references to temporary tensors. ↵Gravatar A. Unique TensorFlower2017-09-29
| | | | | | | | | | | | This way users of the class don't have to remember to capture each one manually to avoid premature deallocation and memory races for asynchronous op kernels. * Add simple tests that run multiple ops concurrently for linalg ops that use CudaSolver. * Put a lock around the calls to cusolverDn*getrs and cusolverDn*gesvd, which appear not to be threadsafe. * Misc. cleanup in linalg GPU kernels. I ran all the related tests 1000 times without failure. Before this change, tests for matrix_solve and svd would fail or hang occasionally. PiperOrigin-RevId: 170557380
* Fix linear algebra benchmarks.Gravatar A. Unique TensorFlower2017-08-17
| | | | PiperOrigin-RevId: 165653891
* Speed up GPU version of tf.matrix_inverse by using LU factorization kernels ↵Gravatar A. Unique TensorFlower2017-08-08
| | | | | | | | | | | | | | | | | | | | | | | | | from cuSolver and a hand-written matrix identity kernel, instead of the batched LU factorization from cuBlas, which is only suitable for small matrices. Speedup measured on Titan X (Maxwell): Shape adjoint Before After Speedup ------------------------------------------------------ (4, 4) noadjoint 0.000204 0.000193 5.3% (16, 16) noadjoint 0.000360 0.000186 48.3% (256, 256) noadjoint 0.013830 0.003852 72.1% (1024, 1024) noadjoint 0.647639 0.015075 97.6% (513, 4, 4) noadjoint 0.000219 0.000192 12.3% (513, 16, 16) noadjoint 0.000293 0.000195 33.4% (513, 256, 256) noadjoint 0.120573 0.120175 0.3% (4, 4) adjoint 0.000201 0.000193 3.9% (16, 16) adjoint 0.000282 0.000185 34.4% (256, 256) adjoint 0.013028 0.003391 73.9% (1024, 1024) adjoint 0.647752 0.014341 97.7% (513, 4, 4) adjoint 0.000221 0.000197 10.8% (513, 16, 16) adjoint 0.000384 0.000205 46.6% (513, 256, 256) adjoint 0.131402 0.130616 0.6% PiperOrigin-RevId: 164623298
* Add benchmarks for matrix_inverse and determinant.Gravatar A. Unique TensorFlower2017-08-04
| | | | | | Add missing op grouping in Cholesky benchmark. PiperOrigin-RevId: 164281947
* Allow complex valued inputs for matrix inverse.Gravatar A. Unique TensorFlower2017-05-23
| | | | PiperOrigin-RevId: 156908010
* * Wrap cuBlas high-level solvers into CudaSolver.Gravatar A. Unique TensorFlower2017-05-10
| | | | | | | | * Use cuBlas calls to implement a GPU version of the matrix_inverse op. * Refactor CudaSolver to make all the kernel launches asynchronous, and add a public interface "RegisterLapackInfoCheckerCallback", which registers a callback to be invoked when the statuses of one or more solver kernels passed to it have been copied back to the host. * Refactor CholeskyOpGpu to use the updated API and make that kernel async too. PiperOrigin-RevId: 155418113
* Remove hourglass imports from kernel_testsGravatar Justine Tunney2016-12-14
| | | | Change: 142080137
* Deprecate tf.batch_matmul and replace with equivalent calls to tf.matmul ↵Gravatar A. Unique TensorFlower2016-11-21
| | | | | | | | | | | | that now supports adjoint and batch matmul. CL created by: replace_string \ batch_matmul\\\( \ matmul\( plus some manual edits, mostly s/adj_x/adjoint_a/ s/adj_y/adjoint_b/. Change: 139821372
* Replace most linear algebra ops with their batch versions and deprecateGravatar A. Unique TensorFlower2016-09-09
| | | | | | | | | | | | | | | | | | BatchCholesky BatchCholeskyGrad BatchMatrixDeterminant BatchMatrixInverse BatchMatrixSolve BatchMatrixSolveLs BatchMatrixTriangularSolve BatchSelfAdjointEig BatchSelfAdjointEigV2 BatchSvd At this point, the non-batch versions were identical to the batch versions except for a check during shape inference restricting the matrix inputs to be rank 2. NOTICE: This is a non-backwards compatible API change. Change: 132692980
* Update copyright for 3p/tf/python.Gravatar A. Unique TensorFlower2016-06-02
| | | | Change: 123900456
* Adds adjoint attribute to matrix inverse to make it possible to compute the ↵Gravatar A. Unique TensorFlower2016-04-15
| | | | | | | inverse of the adjoint of a matrix. This is convenient in various gradient computations where it also saves an explicit transpose op. Implements gradients for batch_matrix_determinant and optimizes implementation of gradient for matrix_determinant. Change: 119990836
* Get rid of some import cruft.Gravatar Josh Levenberg2016-02-10
| | | | Change: 114374558
* TensorFlow: Improve performance of AlexnetGravatar Manjunath Kudlur2015-11-20
| | | | | | | | | | | | | | | | | | | | | | Changes: * error message that refers to removed `DefaultSession` method. * -Wnull-conversion warnings * the "_start_time" attr for recvs when the flag "--brain_enable_scheduling_for_recvs" is set. * typo in tutorial data download progress message. * a typo ("however their installing"=>"however installing"). * typo, rename "TensorFlow Mechanics" to "How To" to be consistent with the website. * a typo ("subtact"=>"subtract"). * protobuf examples in comments in tensorflow::Example.proto. * formula formatting in MNIST beginner tutorial * negative fraction-of-queue-full stats * protobuf inclusion path so that Android demo will build under Blaze. * small typo (moderatly > moderately) * Session.run() to check that tensor arguments come from the session's graph. * another six import * seq2seq typo in bazel command Base CL: 108349164
* TensorFlow: conv improvements, label_image example, andGravatar Vijay Vasudevan2015-11-16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | a few other changes. Changes: - Some improvements to convolution by using 32-bit indices by @benoitsteiner. Not all calls converted yet. Also some improvements to pooling as well by @benoitsteiner. - Improvements to sparse matmul CPU implementation by Ashish - Some fixes to warnings by @vrv - Doc fixes to padding by @Yangqing - Some improvements to Tensor wrappers by Eider - Speed up of matrix inverse on CPU by Rasmus - Add an example of doing image inference from a pre-trained model by @petewarden. - fixed formula in mnist example by nodir - Updates to event accumulator by Cassandra - Slight changes to tensor c api by @mrry - Handling of strings in listdiff by Phil - Fix negative fraction-of-queue-full stats by Frank - Type-checking improvement to importer by Yaroslav - logdir recursive search for Tensorboard by @danmane - Session.run() checks for empty graph by Manoj Base CL: 108013706
* TensorFlow: upstream changes from the afternoon.Gravatar Vijay Vasudevan2015-11-11
| | | | | | | | | | | | | | | | | | | | | | | | | | Changes: - futurize --stage2 changes for Python 3 compatibility by @girving. - Small updates to documentation by @vrv, schuster and others - Account for failure of std::thread::hardware_concurrency by @ebrevdo. - More changes for backwards-compatibility tests by Josh - Updates to python op doc generation by Josh - Added support for using the best-fit allocator via ConfigProto by @vrv. - Rename LocalSession to DirectSession, since local was a bad name for it. - Enable tf.nn.moments() to work with tensors of unknown shape by @mrry. GITHUB_ISSUE: 139 - Changes for Android build by Andrew. Base CL: 107645181
* TensorFlow: Initial commit of TensorFlow library.Gravatar Manjunath Kudlur2015-11-06
TensorFlow is an open source software library for numerical computation using data flow graphs. Base CL: 107276108
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