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* Adjust License.txt file to use the LLVM licenseMehdi Amini2019-12-231-13/+4
| | | | PiperOrigin-RevId: 286906740
* NFC: Cleanup non-conforming usages of namespaces.River Riddle2019-12-181-7/+2
| | | | | | | * Fixes use of anonymous namespace for static methods. * Uses explicit qualifiers(mlir::) instead of wrapping the definition with the namespace. PiperOrigin-RevId: 286222654
* NFC: Remove unnecessary 'llvm::' prefix from uses of llvm symbols declared ↵River Riddle2019-12-181-8/+8
| | | | | | | | in `mlir` namespace. Aside from being cleaner, this also makes the codebase more consistent. PiperOrigin-RevId: 286206974
* Refactor ElementsAttr::getValue and DenseElementsAttr::getSplatValue.River Riddle2019-08-141-4/+2
| | | | | | All 'getValue' variants now require that the index is valid, queryable via 'isValidIndex'. 'getSplatValue' now requires that the attribute is a proper splat. This allows for querying these methods on DenseElementAttr with all possible value types; e.g. float, int, APInt, etc. This also allows for removing unnecessary conversions to Attribute that really want the underlying value. PiperOrigin-RevId: 263437337
* Upstream the Quantizer tool (part 4).Stella Laurenzo2019-06-011-1/+1
| | | | | | | | | | | | This adds the basic passes needed and ties them into mlir-opt. Also adds two specific unit tests that exercise them. Next step is a standalone quantizer tool and additional cleanup. Tested: ninja check-mlir -- PiperOrigin-RevId: 249167690
* Rename VectorOrTensorType to ShapedTypeGeoffrey Martin-Noble2019-05-201-6/+6
| | | | | | | | | | | | This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be useful to be able to use these same utilities for them. This CL should not change any semantics and only change variables, types, string literals, and comments. In follow-up CLs I will prepare all callers to handle MemRef types or remove their dependence on ShapedType. Discussion/Rationale in https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/cHLoyfGu8y8 -- PiperOrigin-RevId: 248476449
* Start to introduce the "Quantizer" tool, which is responsible for ↵Stella Laurenzo2019-05-201-0/+111
transforming a computation expressed in floating point to one operating in terms of quantized types (where possible), either using quant-aware-training hints where available or post-training statistics. This is being integrated from an experimental side repository piece by piece over the course of several patches and will ultimately include full build support, documentation and e2e tests. -- PiperOrigin-RevId: 248259895
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