forked from OSchip/llvm-project
Add support to constant sparse tensor / vector attribute
The SparseElementsAttr uses (COO) Coordinate List encoding to represents a sparse tensor / vector. Specifically, the coordinates and values are stored as two dense elements attributes. The first dense elements attribute is a 2-D attribute with shape [N, ndims], which contains the indices of the elements with nonzero values in the constant vector/tensor. The second elements attribute is a 1-D attribute list with shape [N], which supplies the values for each element in the first elements attribute. ndims is the rank of the vector/tensor and N is the total nonzero elements. The syntax is: `sparse<` (tensor-type | vector-type)`, ` indices-attribute-list, values-attribute-list `>` Example: a sparse tensor sparse<vector<3x4xi32>, [[0, 0], [1, 2]], [1, 2]> represents the dense tensor [[1, 0, 0, 0] [0, 0, 2, 0] [0, 0, 0, 0]] PiperOrigin-RevId: 217764319
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@ -48,8 +48,9 @@ public:
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SplatElements,
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DenseIntElements,
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DenseFPElements,
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SparseElements,
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FIRST_ELEMENTS_ATTR = SplatElements,
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LAST_ELEMENTS_ATTR = DenseFPElements,
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LAST_ELEMENTS_ATTR = SparseElements,
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};
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/// Return the classification for this attribute.
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@ -271,7 +272,7 @@ private:
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/// meaning all of the elements have the same value.
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class SplatElementsAttr : public ElementsAttr {
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public:
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static ElementsAttr *get(VectorOrTensorType *type, Attribute *elt);
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static SplatElementsAttr *get(VectorOrTensorType *type, Attribute *elt);
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Attribute *getValue() const { return elt; }
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/// Method for support type inquiry through isa, cast and dyn_cast.
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@ -333,7 +334,7 @@ public:
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// TODO: returns APInts instead of IntegerAttr.
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void getValues(SmallVectorImpl<Attribute *> &values) const;
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APInt getValue(ArrayRef<int> indices) const;
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APInt getValue(ArrayRef<unsigned> indices) const;
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/// Writes the lowest `bitWidth` bits of `value` to the bit position `bitPos`
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/// in array `rawData`.
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@ -366,7 +367,7 @@ public:
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// TODO: returns APFPs instead of FloatAttr.
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void getValues(SmallVectorImpl<Attribute *> &values) const;
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APFloat getValue(ArrayRef<int> indices) const;
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APFloat getValue(ArrayRef<unsigned> indices) const;
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/// Method for support type inquiry through isa, cast and dyn_cast.
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static bool classof(const Attribute *attr) {
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@ -376,6 +377,50 @@ public:
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private:
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~DenseFPElementsAttr() = delete;
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};
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/// An attribute represents a reference to a sparse vector or tensor object.
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///
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/// This class uses COO (coordinate list) encoding to represent the sparse
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/// elements in an element attribute. Specifically, the sparse vector/tensor
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/// stores the indices and values as two separate dense elements attributes. The
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/// dense elements attribute indices is a 2-D tensor with shape [N, ndims],
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/// which specifies the indices of the elements in the sparse tensor that
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/// contains nonzero values. The dense elements attribute values is a 1-D tensor
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/// with shape [N], and it supplies the corresponding values for the indices.
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///
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/// For example,
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/// `sparse<tensor<3x4xi32>, [[0, 0], [1, 2]], [1, 5]>` represents tensor
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/// [[1, 0, 0, 0],
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/// [0, 0, 5, 0],
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/// [0, 0, 0, 0]].
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class SparseElementsAttr : public ElementsAttr {
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public:
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static SparseElementsAttr *get(VectorOrTensorType *type,
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DenseIntElementsAttr *indices,
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DenseElementsAttr *values);
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DenseIntElementsAttr *getIndices() const { return indices; }
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DenseElementsAttr *getValues() const { return values; }
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/// Return the value at the given index.
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Attribute *getValue(ArrayRef<unsigned> index) const;
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/// Method for support type inquiry through isa, cast and dyn_cast.
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static bool classof(const Attribute *attr) {
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return attr->getKind() == Kind::SparseElements;
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}
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private:
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SparseElementsAttr(VectorOrTensorType *type, DenseIntElementsAttr *indices,
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DenseElementsAttr *values)
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: ElementsAttr(Kind::SparseElements, type), indices(indices),
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values(values) {}
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~SparseElementsAttr() = delete;
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DenseIntElementsAttr *const indices;
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DenseElementsAttr *const values;
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};
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} // end namespace mlir.
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#endif
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@ -44,6 +44,8 @@ class TypeAttr;
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class ArrayAttr;
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class FunctionAttr;
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class ElementsAttr;
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class DenseElementsAttr;
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class DenseIntElementsAttr;
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class AffineMapAttr;
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class AffineMap;
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@ -102,6 +104,9 @@ public:
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ElementsAttr *getSplatElementsAttr(VectorOrTensorType *type, Attribute *elt);
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ElementsAttr *getDenseElementsAttr(VectorOrTensorType *type,
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ArrayRef<char> data);
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ElementsAttr *getSparseElementsAttr(VectorOrTensorType *type,
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DenseIntElementsAttr *indicies,
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DenseElementsAttr *values);
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// Affine expressions and affine maps.
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AffineExpr getAffineDimExpr(unsigned position);
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@ -264,8 +269,7 @@ public:
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}
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private:
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template <typename T>
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T *insertTerminator(T *term) {
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template <typename T> T *insertTerminator(T *term) {
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block->setTerminator(term);
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return term;
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}
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@ -477,6 +477,17 @@ void ModulePrinter::printAttribute(const Attribute *attr) {
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os << '>';
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break;
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}
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case Attribute::Kind::SparseElements: {
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auto *elementsAttr = cast<SparseElementsAttr>(attr);
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os << "sparse<";
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printType(elementsAttr->getType());
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os << ", ";
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printDenseElementsAttr(elementsAttr->getIndices());
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os << ", ";
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printDenseElementsAttr(elementsAttr->getValues());
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os << '>';
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break;
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}
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}
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}
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@ -154,6 +154,12 @@ ElementsAttr *Builder::getDenseElementsAttr(VectorOrTensorType *type,
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return DenseElementsAttr::get(type, data);
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}
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ElementsAttr *Builder::getSparseElementsAttr(VectorOrTensorType *type,
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DenseIntElementsAttr *indicies,
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DenseElementsAttr *values) {
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return SparseElementsAttr::get(type, indicies, values);
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}
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//===----------------------------------------------------------------------===//
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// Affine Expressions, Affine Maps, and Integet Sets.
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//===----------------------------------------------------------------------===//
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@ -297,6 +297,9 @@ public:
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using DenseElementsAttrSet =
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DenseSet<DenseElementsAttr *, DenseElementsAttrInfo>;
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DenseElementsAttrSet denseElementsAttrs;
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DenseMap<std::tuple<Type *, DenseElementsAttr *, DenseElementsAttr *>,
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SparseElementsAttr *>
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sparseElementsAttrs;
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public:
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MLIRContextImpl() : filenames(locationAllocator), identifiers(allocator) {}
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@ -951,7 +954,8 @@ void DenseFPElementsAttr::getValues(
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}
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}
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ElementsAttr *SplatElementsAttr::get(VectorOrTensorType *type, Attribute *elt) {
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SplatElementsAttr *SplatElementsAttr::get(VectorOrTensorType *type,
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Attribute *elt) {
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auto &impl = type->getContext()->getImpl();
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// Look to see if we already have this.
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@ -968,6 +972,26 @@ ElementsAttr *SplatElementsAttr::get(VectorOrTensorType *type, Attribute *elt) {
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return result;
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}
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SparseElementsAttr *SparseElementsAttr::get(VectorOrTensorType *type,
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DenseIntElementsAttr *indices,
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DenseElementsAttr *values) {
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auto &impl = type->getContext()->getImpl();
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// Look to see if we already have this.
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auto key = std::make_tuple(type, indices, values);
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auto *&result = impl.sparseElementsAttrs[key];
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// If we already have it, return that value.
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if (result)
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return result;
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// Otherwise, allocate them into the bump pointer.
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result = impl.allocator.Allocate<SparseElementsAttr>();
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new (result) SparseElementsAttr(type, indices, values);
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return result;
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}
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//===----------------------------------------------------------------------===//
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// AffineMap and AffineExpr uniquing
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//===----------------------------------------------------------------------===//
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@ -200,6 +200,7 @@ public:
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Function *resolveFunctionReference(StringRef nameStr, SMLoc nameLoc,
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FunctionType *type);
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Attribute *parseAttribute();
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ParseResult parseAttributeDict(SmallVectorImpl<NamedAttribute> &attributes);
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// Polyhedral structures.
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@ -207,7 +208,8 @@ public:
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AffineMap parseAffineMapReference();
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IntegerSet parseIntegerSetInline();
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IntegerSet parseIntegerSetReference();
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ElementsAttr *parseDenseElementsAttr(VectorOrTensorType *type);
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DenseElementsAttr *parseDenseElementsAttr(VectorOrTensorType *type);
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DenseElementsAttr *parseDenseElementsAttr(Type *eltType, bool isVector);
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VectorOrTensorType *parseVectorOrTensorType();
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private:
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@ -803,6 +805,8 @@ Function *Parser::resolveFunctionReference(StringRef nameStr, SMLoc nameLoc,
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/// | function-id `:` function-type
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/// | (`splat<` | `dense<`) (tensor-type | vector-type)`,`
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/// attribute-value `>`
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/// | `sparse<` (tensor-type | vector-type)`,`
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/// attribute-value`, ` attribute-value `>`
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///
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Attribute *Parser::parseAttribute() {
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switch (getToken().getKind()) {
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@ -905,7 +909,6 @@ Attribute *Parser::parseAttribute() {
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auto *type = parseVectorOrTensorType();
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if (!type)
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return nullptr;
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switch (getToken().getKind()) {
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case Token::floatliteral:
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case Token::integer:
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@ -942,6 +945,64 @@ Attribute *Parser::parseAttribute() {
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return (emitError("expected '[' to start dense tensor literal"), nullptr);
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}
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}
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case Token::kw_sparse: {
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consumeToken(Token::kw_sparse);
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if (parseToken(Token::less, "Expected '<' after 'sparse'"))
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return nullptr;
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auto *type = parseVectorOrTensorType();
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if (!type)
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return nullptr;
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switch (getToken().getKind()) {
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case Token::l_square: {
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/// Parse indices
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auto *indicesEltType = builder.getIntegerType(32);
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auto *indices =
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parseDenseElementsAttr(indicesEltType, isa<VectorType>(type));
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if (parseToken(Token::comma, "expected ','"))
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return nullptr;
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/// Parse values.
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auto *valuesEltType = type->getElementType();
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auto *values =
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parseDenseElementsAttr(valuesEltType, isa<VectorType>(type));
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/// Sanity check.
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auto *indicesType = indices->getType();
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auto *valuesType = values->getType();
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auto sameShape = (indicesType->getRank() == 1) ||
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(type->getRank() == indicesType->getDimSize(1));
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auto sameElementNum =
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indicesType->getDimSize(0) == valuesType->getDimSize(0);
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if (!sameShape || !sameElementNum) {
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std::string str;
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llvm::raw_string_ostream s(str);
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s << "expected shape ([";
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interleaveComma(type->getShape(), s);
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s << "]); inferred shape of indices literal ([";
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interleaveComma(indicesType->getShape(), s);
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s << "]); inferred shape of values literal ([";
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interleaveComma(valuesType->getShape(), s);
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s << "])";
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return (emitError(s.str()), nullptr);
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}
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if (parseToken(Token::greater, "expected '>'"))
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return nullptr;
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// Build the sparse elements attribute by the indices and values.
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return builder.getSparseElementsAttr(
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type, cast<DenseIntElementsAttr>(indices), values);
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}
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default:
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return (emitError("expected '[' to start sparse tensor literal"),
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nullptr);
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}
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return (emitError("expected elements literal has a tensor or vector type"),
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nullptr);
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}
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default: {
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if (Type *type = parseType())
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return builder.getTypeAttr(type);
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}
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}
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ElementsAttr *Parser::parseDenseElementsAttr(VectorOrTensorType *type) {
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/// Dense elements attribute.
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///
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/// dense-attr-list ::= `[` attribute-value `]`
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/// attribute-value ::= integer-literal
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/// | float-literal
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/// | `[` (attribute-value (`,` attribute-value)*)? `]`
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///
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/// This method returns a constructed dense elements attribute with the shape
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/// from the parsing result.
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DenseElementsAttr *Parser::parseDenseElementsAttr(Type *eltType,
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bool isVector) {
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TensorLiteralParser literalParser(*this, eltType);
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if (literalParser.parse())
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return nullptr;
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VectorOrTensorType *type;
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if (isVector) {
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type = builder.getVectorType(literalParser.getShape(), eltType);
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} else {
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type = builder.getTensorType(literalParser.getShape(), eltType);
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}
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return (DenseElementsAttr *)builder.getDenseElementsAttr(
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type, literalParser.getValues());
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}
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/// Dense elements attribute.
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///
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/// dense-attr-list ::= `[` attribute-value `]`
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/// attribute-value ::= integer-literal
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/// | float-literal
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/// | `[` (attribute-value (`,` attribute-value)*)? `]`
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///
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/// This method compares the shapes from the parsing result and that from the
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/// input argument. It returns a constructed dense elements attribute if both
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/// match.
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DenseElementsAttr *Parser::parseDenseElementsAttr(VectorOrTensorType *type) {
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auto *eltTy = type->getElementType();
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TensorLiteralParser literalParser(*this, eltTy);
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if (literalParser.parse())
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s << "])";
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return (emitError(s.str()), nullptr);
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}
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return builder.getDenseElementsAttr(type, literalParser.getValues());
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return (DenseElementsAttr *)builder.getDenseElementsAttr(
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type, literalParser.getValues());
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}
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/// Vector or tensor type for elements attribute.
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///
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/// vector-or-tensor-type ::= vector-type | tensor-type
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///
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/// This method also checks the type has static shape and ranked.
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VectorOrTensorType *Parser::parseVectorOrTensorType() {
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auto *type = dyn_cast<VectorOrTensorType>(parseType());
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if (!type) {
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return (emitError("tensor literals must be ranked and have static shape"),
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nullptr);
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}
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return type;
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}
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@ -123,6 +123,7 @@ TOK_KEYWORD(tf_string)
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TOK_KEYWORD(tf_f32ref)
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TOK_KEYWORD(to)
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TOK_KEYWORD(true)
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TOK_KEYWORD(sparse)
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TOK_KEYWORD(vector)
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#undef TOK_MARKER
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@ -590,4 +590,60 @@ bb0:
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// CHECK: "float64"() {bar: dense<vector<2x1x4xf64>, {{\[\[\[}}-5.000000e+00, 6.000000e+00, 1.000000e+00, 2.000000e+00]], {{\[\[}}7.000000e+00, -8.000000e+00, 3.000000e+00, 4.000000e+00]]]>} : () -> ()
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"float64"(){bar: dense<vector<2x1x4xf64>, [[[-5.0, 6.0, 1.0, 2.0]], [[7.0, -8.0, 3.0, 4.0]]]>} : () -> ()
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return
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}
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// CHECK-LABEL: cfgfunc @sparsetensorattr
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cfgfunc @sparsetensorattr() -> () {
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bb0:
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// NOTE: The {{\[\[}} syntax is because "[[" confuses FileCheck.
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// CHECK: "fooi8"() {bar: sparse<tensor<1x1x1xi8>, {{\[\[}}0, 0, 0]], {{\[}}-2]>} : () -> ()
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"fooi8"(){bar: sparse<tensor<1x1x1xi8>, [[0, 0, 0]], [-2]>} : () -> ()
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// CHECK: "fooi16"() {bar: sparse<tensor<2x2x2xi16>, {{\[\[}}1, 1, 0], {{\[}}0, 1, 0], {{\[}}0, 0, 1]], {{\[}}2, -1, 5]>} : () -> ()
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"fooi16"(){bar: sparse<tensor<2x2x2xi16>, [[1, 1, 0], [0, 1, 0], [0, 0, 1]], [2, -1, 5]>} : () -> ()
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// CHECK: "fooi32"() {bar: sparse<tensor<1x1xi32>, {{\[}}], {{\[}}]>} : () -> ()
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"fooi32"(){bar: sparse<tensor<1x1xi32>, [], []>} : () -> ()
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// CHECK: "fooi64"() {bar: sparse<tensor<1xi64>, {{\[\[}}0]], {{\[}}-1]>} : () -> ()
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"fooi64"(){bar: sparse<tensor<1xi64>, [[0]], [-1]>} : () -> ()
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// CHECK: "foo2"() {bar: sparse<tensor<0xi32>, {{\[}}], {{\[}}]>} : () -> ()
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"foo2"(){bar: sparse<tensor<0 x i32>, [], []>} : () -> ()
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// CHECK: "foof16"() {bar: sparse<tensor<1x1x1xf16>, {{\[\[}}0, 0, 0]], {{\[}}-2.000000e+00]>} : () -> ()
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"foof16"(){bar: sparse<tensor<1x1x1xf16>, [[0, 0, 0]], [-2.0]>} : () -> ()
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// CHECK: "foobf16"() {bar: sparse<tensor<2x2x2xbf16>, {{\[\[}}1, 1, 0], {{\[}}0, 1, 0], {{\[}}0, 0, 1]], {{\[}}2.000000e+00, -1.000000e+00, 5.000000e+00]>} : () -> ()
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"foobf16"(){bar: sparse<tensor<2x2x2xbf16>, [[1, 1, 0], [0, 1, 0], [0, 0, 1]], [2.0, -1.0, 5.0]>} : () -> ()
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// CHECK: "foof32"() {bar: sparse<tensor<1x1xf32>, {{\[}}], {{\[}}]>} : () -> ()
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"foof32"(){bar: sparse<tensor<1x0x1xf32>, [], []>} : () -> ()
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// CHECK: "foof64"() {bar: sparse<tensor<1xf64>, {{\[\[}}0]], {{\[}}-1.000000e+00]>} : () -> ()
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"foof64"(){bar: sparse<tensor<1xf64>, [[0]], [-1.0]>} : () -> ()
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// CHECK: "foof320"() {bar: sparse<tensor<0xf32>, {{\[}}], {{\[}}]>} : () -> ()
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"foof320"(){bar: sparse<tensor<0 x f32>, [], []>} : () -> ()
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return
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}
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// CHECK-LABEL: cfgfunc @sparsevectorattr
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cfgfunc @sparsevectorattr() -> () {
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bb0:
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// NOTE: The {{\[\[}} syntax is because "[[" confuses FileCheck.
|
||||
// CHECK: "fooi8"() {bar: sparse<vector<1x1x1xi8>, {{\[\[}}0, 0, 0]], {{\[}}-2]>} : () -> ()
|
||||
"fooi8"(){bar: sparse<vector<1x1x1xi8>, [[0, 0, 0]], [-2]>} : () -> ()
|
||||
// CHECK: "fooi16"() {bar: sparse<vector<2x2x2xi16>, {{\[\[}}1, 1, 0], {{\[}}0, 1, 0], {{\[}}0, 0, 1]], {{\[}}2, -1, 5]>} : () -> ()
|
||||
"fooi16"(){bar: sparse<vector<2x2x2xi16>, [[1, 1, 0], [0, 1, 0], [0, 0, 1]], [2, -1, 5]>} : () -> ()
|
||||
// CHECK: "fooi32"() {bar: sparse<vector<1x1xi32>, {{\[}}], {{\[}}]>} : () -> ()
|
||||
"fooi32"(){bar: sparse<vector<1x1xi32>, [], []>} : () -> ()
|
||||
// CHECK: "fooi64"() {bar: sparse<vector<1xi64>, {{\[\[}}0]], {{\[}}-1]>} : () -> ()
|
||||
"fooi64"(){bar: sparse<vector<1xi64>, [[0]], [-1]>} : () -> ()
|
||||
// CHECK: "foo2"() {bar: sparse<vector<0xi32>, {{\[}}], {{\[}}]>} : () -> ()
|
||||
"foo2"(){bar: sparse<vector<0 x i32>, [], []>} : () -> ()
|
||||
|
||||
// CHECK: "foof16"() {bar: sparse<vector<1x1x1xf16>, {{\[\[}}0, 0, 0]], {{\[}}-2.000000e+00]>} : () -> ()
|
||||
"foof16"(){bar: sparse<vector<1x1x1xf16>, [[0, 0, 0]], [-2.0]>} : () -> ()
|
||||
// CHECK: "foobf16"() {bar: sparse<vector<2x2x2xbf16>, {{\[\[}}1, 1, 0], {{\[}}0, 1, 0], {{\[}}0, 0, 1]], {{\[}}2.000000e+00, -1.000000e+00, 5.000000e+00]>} : () -> ()
|
||||
"foobf16"(){bar: sparse<vector<2x2x2xbf16>, [[1, 1, 0], [0, 1, 0], [0, 0, 1]], [2.0, -1.0, 5.0]>} : () -> ()
|
||||
// CHECK: "foof32"() {bar: sparse<vector<1x1xf32>, {{\[}}], {{\[}}]>} : () -> ()
|
||||
"foof32"(){bar: sparse<vector<1x0x1xf32>, [], []>} : () -> ()
|
||||
// CHECK: "foof64"() {bar: sparse<vector<1xf64>, {{\[\[}}0]], {{\[}}-1.000000e+00]>} : () -> ()
|
||||
"foof64"(){bar: sparse<vector<1xf64>, [[0]], [-1.0]>} : () -> ()
|
||||
// CHECK: "foof320"() {bar: sparse<vector<0xf32>, {{\[}}], {{\[}}]>} : () -> ()
|
||||
"foof320"(){bar: sparse<vector<0 x f32>, [], []>} : () -> ()
|
||||
return
|
||||
}
|
Loading…
Reference in New Issue