| Commit message (Collapse) | Author | Age | Files | Lines |
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PiperOrigin-RevId: 286906740
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Closes tensorflow/mlir#175
PiperOrigin-RevId: 275726876
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These don't add any value, and some are even more restrictive than the respective static 'get' method.
PiperOrigin-RevId: 275391240
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Sdd support in deserializer for OpMemberName instruction. For now
the name is just processed and not associated with the
spirv::StructType being built. That needs an enhancement to
spirv::StructTypes itself.
Add tests to check for errors reported during deserialization with
some refactoring to common out some utility functions.
PiperOrigin-RevId: 270794524
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This fixes a problem with current save-restore pattern of diagnostics handlers, as there may be a thread race between when the previous handler is destroyed. For example, this occurs when using multiple ParallelDiagnosticHandlers asynchronously:
Handler A
Handler B | - LifeTime - | Restore A here.
Handler C | --- LifeTime ---| Restore B after it has been destroyed.
The new design allows for multiple handlers to be registered in a stack like fashion. Handlers can return success() to signal that they have fully processed a diagnostic, or failure to propagate otherwise.
PiperOrigin-RevId: 270720625
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MLIR follows the LLVM convention of passing by reference instead of by pointer.
PiperOrigin-RevId: 270396945
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Each basic block in SPIR-V must start with an OpLabel instruction.
We don't support control flow yet, so this CL just makes sure that
the entry block follows this rule and is valid.
PiperOrigin-RevId: 265718841
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Add Block decoration for top-level spv.struct.
Closes tensorflow/mlir#102
PiperOrigin-RevId: 265716241
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We are relying on serializer to construct positive cases to drive
the test for deserializer. This leaves negative cases untested.
This CL adds a basic test fixture for covering the negative
corner cases to enforce a more robust deserializer.
Refactored common SPIR-V building methods out of serializer to
share it with the deserialization test.
PiperOrigin-RevId: 260742733
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DenseElementsAttr.
PiperOrigin-RevId: 253910543
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being a separate Attribute type. DenseElementsAttr provides a better internal representation for splat values as well as better API for accessing elements.
PiperOrigin-RevId: 253138287
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DenseFPElementsAttr in favor of just one DenseElementsAttr. Now that attribute has the ability to define 'classof(Attribute attr)' methods, these derived classes can just be specializations of the main attribute class.
PiperOrigin-RevId: 251948820
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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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Adding the additional layer of directory was discussed offline and matches the Target/ tree. The names match the defacto convention we seem to be following where the C++ namespace is ^(.+)Ops/$ matched against the directory name.
This is in preparation for patching the Quantizer into this tree, which would have been confusing without moving the Quantization dialect to its more proper home. It is left to others to move other dialects if desired.
Tested:
ninja check-mlir
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PiperOrigin-RevId: 248171982
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* Add initial version of build files;
* Update README with instructions to download and build MLIR from github;
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PiperOrigin-RevId: 241102092
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This is a more efficient way than returning SmallVector directly.
PiperOrigin-RevId: 239407024
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So that we can use this function to deduce broadcasted shapes elsewhere.
Also added support for unknown dimensions, by following TensorFlow behavior.
PiperOrigin-RevId: 237846065
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