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path: root/tensorflow/compiler/xla/service/transpose_folding_test.cc
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* [TF:XLA] Define DefaultPrecisionConfig in HloTestBase and delete multiple ↵Gravatar Dimitris Vardoulakis2018-09-05
| | | | | | duplicate definitions. PiperOrigin-RevId: 211662523
* [XLA] Make kConvolution, kDot HLO attributes mandatoryGravatar David Majnemer2018-09-04
| | | | | | | | HLO transformations would forget to propagate the feature depth attribute. Making these attributes mandatory, while slightly less convenient for tests, makes HLO transformations more robust. PiperOrigin-RevId: 211490160
* [XLA] This is a step to incrementally move client/xla_client/* to client/.Gravatar A. Unique TensorFlower2018-07-25
| | | | PiperOrigin-RevId: 206111380
* [TF:XLA] Split literal_util into {literal, literal_util}.Gravatar Kay Zhu2018-07-03
| | | | | | | | | Currently Literal classes sits in literal_util.{h,cc} instead of literal.{h,cc}. It also contains helper functions that are better fit to be their own separate class/namespace. This change starts this process by moving most static factory methods to LiteralUtil namespace. PiperOrigin-RevId: 203217065
* [XLA] Sanitize HloComputation and HloInstruction names.Gravatar A. Unique TensorFlower2018-06-11
| | | | PiperOrigin-RevId: 200110003
* [XLA] Move xla/tools/parser/* into xla/service.Gravatar Justin Lebar2018-06-01
| | | | | | | | Now that we're using the parser inside of xla/service, it's awkward for it to live inside of xla/tools, because everything else in there is a standalone tool. We've already had one person be confused by this. PiperOrigin-RevId: 198935921
* Remove uses of the kTransposeDot fusionGravatar Sanjoy Das2018-05-07
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | I didn't remove the enum itself, but after this change removing the enum should be a simple NFC change (famous last words!). This will make it easier to implement BatchDot on CPU. The change removes usages of kTransposeDot by: - Teaching TransposeFolding to "fuse" transposes into dots by flipping the lhs_contracting_dims/rhs_contracting_dims fields. - Replacing the notion of transpose_lhs/transpose_rhs in the IR emitters with "has a non-canonical LHS contraction dimension"/"has a non-canonical RHS contraction dimension" where the canonical LHS and RHS contraction dims [0] are 1 and 0. Some tests were getting away with creating Dot instructions with their dimensions numbers unset. I've fixed these to create canonical dot operations instead. It is possible (but hard to tell without trying) that some of the IR emission logic and Eigen runtime calls can now be simplified further. For instance, instead of passing in a `transpose_lhs` and `transpose_rhs` to the Eigen GEMM routines, we could instead pass in the LHS and RHS contraction dimensions directly. [0] See HloInstruction::CreateCanonicalDot. PiperOrigin-RevId: 195514907
* [XLA] Redesign: deprecate ComputationBuilder.Gravatar A. Unique TensorFlower2018-05-04
| | | | PiperOrigin-RevId: 195335330
* [TF:XLA]Gravatar Dimitris Vardoulakis2018-04-28
| | | | | | | - Require a module config when creating an HloModule. - All tests using HloTestBase create a module using CreateNewModule. PiperOrigin-RevId: 194684585
* [XLA] Adds Dot with DotDimensionNumbers proto for specifying arbitrary ↵Gravatar A. Unique TensorFlower2017-11-30
| | | | | | contracting and batch dimensions. PiperOrigin-RevId: 177481231
* [XLA] Support transposing the spatial dimensions of a convolution's activationsGravatar David Majnemer2017-11-28
| | | | PiperOrigin-RevId: 177260886
* [XLA] Separate input and output spatial dimensions for convolutionGravatar David Majnemer2017-11-27
| | | | | | This lets us reason about input spatial dimensions as distinct from output spatial dimensions. By doing this, it opens up more opportunities for assigning more interesting, different, layouts for the activations and the output. PiperOrigin-RevId: 177117140
* [XLA] Teach transpose folding how to transpose the LHS of convolutionsGravatar David Majnemer2017-10-19
| | | | | | | This is now possible now that we have added the required fields to ConvolutionDimensionNumbers. PiperOrigin-RevId: 172807540
* [XLA] Make HloComputation::instructions() return a view of HloInstruction*s.Gravatar Justin Lebar2017-09-28
| | | | | | | | Currently it returns a view of unique_ptr<HloInstruction>s. But the fact that these are unique_ptrs is an implementation detail, and it's ugly to leak it everywhere. PiperOrigin-RevId: 170445375
* Use xla/tests:xla_internal_test_main for all tests under tf/compiler/xlaGravatar Mark Heffernan2017-09-12
| | | | | | | and remove any main() definitions in tests. This enables use of flags in all tests. PiperOrigin-RevId: 168424796
* Add flag parsing to more tests in xla/service specifically those which buildGravatar Mark Heffernan2017-09-12
| | | | | | | | HLO graphs. This enables, for example, dumping of the graphs with --xla_generate_hlo_graph. Also remove some superfluous tensorflow test_main dependencies. PiperOrigin-RevId: 168406746
* Remove class xla::LiteralUtil. NFC (mind-numbingly so).Gravatar A. Unique TensorFlower2017-06-19
| | | | | | This patch removes class xla::LiteralUtil and rewrites every call to use class xla::Literal instead. PiperOrigin-RevId: 159446373
* [XLA] Run transpose_folding on nested computationsGravatar David Majnemer2017-04-26
| | | | | | | We only ran the pass on the entry computation which would make us lose out on optimization opportunities. Visit all computations to find any potential transpose folding opportunities. Change: 154343660
* Using GMock matchers in XLA tests.Gravatar A. Unique TensorFlower2017-04-11
| | | | Change: 152823724
* [XLA] Add support for folding transpose into convolutionGravatar David Majnemer2017-04-08
| | | | Change: 152581336
* Initial open-source release of XLA: Accelerated Linear Algebra.Gravatar Peter Hawkins2017-01-09
XLA is a compiler-based linear algebra execution engine that targets CPUs, GPUs and custom accelerators. XLA is still experimental; we are releasing it early to get the community involved. Change: 143990941
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