[Mlir-commits] [mlir] [mlir][spirv] Add support for SPV_ARM_tensors (PR #144667)

[Davide Grohmann]

================
@@ -477,6 +479,37 @@ class MatrixType : public Type::TypeBase<MatrixType, CompositeType,
                        std::optional<StorageClass> storage = std::nullopt);
 };
 
+// SPIR-V TensorARM Type
+class TensorArmType
+    : public Type::TypeBase<TensorArmType, CompositeType,
+                            detail::TensorArmTypeStorage, ShapedType::Trait> {
+public:
+  using Base::Base;
+
+  static constexpr StringLiteral name = "spirv.arm.tensor";
+
+  // TensorArm supports minimum rank of 1, hence an empty shape here means
+  // unranked.
+  static TensorArmType get(ArrayRef<int64_t> shape, Type elementType);
+  TensorArmType cloneWith(std::optional<ArrayRef<int64_t>> shape,
+                          Type elementType) const;
+
+  static LogicalResult
+  verifyInvariants(function_ref<InFlightDiagnostic()> emitError,
+                   ArrayRef<int64_t> shape, Type elementType);
+
+  Type getElementType() const;
+  ArrayRef<int64_t> getShape() const;
+  unsigned getNumElements() const;
----------------
davidegrohmann wrote:

It should probably fail if the tensor is unranked or has dynamic shapes. What is the best way to make `TensorArmType` implement the `ShapeType` trait?

Should I do something similar to `RankedTensorType`?
```
  using ShapedType::Trait<RankedTensorType>::getElementTypeBitWidth;
  using ShapedType::Trait<RankedTensorType>::getRank;
  using ShapedType::Trait<RankedTensorType>::getNumElements;
  using ShapedType::Trait<RankedTensorType>::isDynamicDim;
  using ShapedType::Trait<RankedTensorType>::hasStaticShape;
  using ShapedType::Trait<RankedTensorType>::getNumDynamicDims;
  using ShapedType::Trait<RankedTensorType>::getDimSize;
  using ShapedType::Trait<RankedTensorType>::getDynamicDimIndex;
```

https://github.com/llvm/llvm-project/pull/144667