| Commit message (Collapse) | Author | Age | Files | Lines |
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properly value-typed.
Summary: These were temporary methods used to simplify the transition.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D72548
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ValuePtr was a temporary typedef during the transition to a value-typed Value.
PiperOrigin-RevId: 286945714
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PiperOrigin-RevId: 286906740
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Value being value-typed.
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
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* Fixes use of anonymous namespace for static methods.
* Uses explicit qualifiers(mlir::) instead of wrapping the definition with the namespace.
PiperOrigin-RevId: 286222654
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in `mlir` namespace.
Aside from being cleaner, this also makes the codebase more consistent.
PiperOrigin-RevId: 286206974
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Closes tensorflow/mlir#177
PiperOrigin-RevId: 275692653
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PiperOrigin-RevId: 272851237
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Switch to C++14 standard method as llvm::make_unique has been removed (
https://reviews.llvm.org/D66259). Also mark some targets as c++14 to ease next
integrates.
PiperOrigin-RevId: 263953918
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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
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into the mlir namespace.
Now that Locations are attributes, they have direct access to the MLIR context. This allows for simplifying error emission by removing unnecessary context lookups.
PiperOrigin-RevId: 255112791
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--
PiperOrigin-RevId: 250939301
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--
PiperOrigin-RevId: 249986120
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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
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PiperOrigin-RevId: 249167690
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This upstreams the config and constraints for a reference quantization scheme based on the FxpMathOps dialect.
There are probably two more CLs to get the rest: one with the passes/tests, and one with the tool main() itself.
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PiperOrigin-RevId: 248817505
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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
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PiperOrigin-RevId: 248476449
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This adds some additional core types and utilities, notably the constraint analysis graph (CAG) structures, associated metadata and configuration policy object base class.
The CAG is not particularly memory efficient as it stands now. I had started some work to turn it into a form that could be better managed by a bump pointer allocator but abandoned that for now in favor of having something that does semantically what I was going for as a starting point.
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PiperOrigin-RevId: 248413133
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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.
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PiperOrigin-RevId: 248259895
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