NFC: Attribute cleanup (remove references of attributes) (#286)
* Define krnl.permute op. * Support krnl.permute operation. * Properly remove loop references. * Re-push, Github was down. * Need to debug interpretOp error. * Fix lowering bug by erasing ops after full krnl IR interpretation is done, and clean up & comment code. * Introduce permute, unroll operations. * More debug. * Remove std::set. * krnl.terminate fails to be converted. * Pass all tests, need to add legal ops as well as part of the conversion target. * Change test format to new permute spec. * Bug fix for nested iterate op lowering. * Simplify error reporting. * Fix compilation error. * Increase comments coverage. * Remove unnecessary imports. * Re-trigger Jenkins * Add permute/unroll tests. * Retrigger Jenkins * remove & (ref) for Attributes Co-authored-by: Tian Jin <tjingrant@gmail.com>
This commit is contained in:
Alexandre Eichenberger
GitHub
parent
8bfde7de4b
commit
c1262c184e
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@ -111,7 +111,7 @@ private:
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}
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mlir::NamedAttribute convertOnnxAttributeProtoToMlirNamedAttribute(
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onnx::AttributeProto &attr) {
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onnx::AttributeProto attr) {
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mlir::Attribute mlirAttr;
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switch (attr.type()) {
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case onnx::AttributeProto::FLOAT:
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@ -25,7 +25,7 @@ namespace {
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/// Compute the combined permute pattern from a pair of permute patterns.
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ArrayAttr CombinedTransposePattern(PatternRewriter &rewriter,
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ArrayAttr &firstPermAttr, ArrayAttr &secondPermAttr) {
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ArrayAttr firstPermAttr, ArrayAttr secondPermAttr) {
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// Read first permute vectors.
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SmallVector<int64_t, 4> initialPerm;
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for (auto firstPermVal : firstPermAttr.getValue())
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@ -44,7 +44,7 @@ ArrayAttr CombinedTransposePattern(PatternRewriter &rewriter,
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/// Test if the permute pattern correspond to an identity pattern.
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/// Identity patterns are {0, 1, 2, ... , rank -1}.
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bool IsIdentityPermuteVector(ArrayAttr &permAttr) {
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bool IsIdentityPermuteVector(ArrayAttr permAttr) {
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int64_t currentIndex = 0;
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for (auto permVal : permAttr.getValue())
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if (permVal.cast<IntegerAttr>().getInt() != currentIndex++)
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@ -59,14 +59,14 @@ namespace {
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template <typename OP>
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Attribute ComputeConstPropElementwiseBinary(PatternRewriter &rewriter,
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Type elementType, Attribute &lhsAttr, Attribute &secondAttr) {
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Type elementType, Attribute lhsAttr, Attribute secondAttr) {
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llvm_unreachable("unkonwn operation");
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}
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template <>
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Attribute ComputeConstPropElementwiseBinary<ONNXAddOp>(
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PatternRewriter &rewriter, Type elementType, Attribute &lhsAttr,
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Attribute &secondAttr) {
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PatternRewriter &rewriter, Type elementType, Attribute lhsAttr,
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Attribute secondAttr) {
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if (elementType.isa<FloatType>()) {
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double lhsVal = lhsAttr.cast<FloatAttr>().getValueAsDouble();
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double rhsVal = secondAttr.cast<FloatAttr>().getValueAsDouble();
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@ -86,8 +86,8 @@ Attribute ComputeConstPropElementwiseBinary<ONNXAddOp>(
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template <>
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Attribute ComputeConstPropElementwiseBinary<ONNXSubOp>(
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PatternRewriter &rewriter, Type elementType, Attribute &lhsAttr,
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Attribute &secondAttr) {
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PatternRewriter &rewriter, Type elementType, Attribute lhsAttr,
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Attribute secondAttr) {
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if (elementType.isa<FloatType>()) {
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double lhsVal = lhsAttr.cast<FloatAttr>().getValueAsDouble();
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double rhsVal = secondAttr.cast<FloatAttr>().getValueAsDouble();
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@ -105,8 +105,8 @@ Attribute ComputeConstPropElementwiseBinary<ONNXSubOp>(
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template <>
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Attribute ComputeConstPropElementwiseBinary<ONNXMulOp>(
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PatternRewriter &rewriter, Type elementType, Attribute &lhsAttr,
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Attribute &secondAttr) {
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PatternRewriter &rewriter, Type elementType, Attribute lhsAttr,
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Attribute secondAttr) {
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if (elementType.isa<FloatType>()) {
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double lhsVal = lhsAttr.cast<FloatAttr>().getValueAsDouble();
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double rhsVal = secondAttr.cast<FloatAttr>().getValueAsDouble();
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@ -124,8 +124,8 @@ Attribute ComputeConstPropElementwiseBinary<ONNXMulOp>(
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template <>
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Attribute ComputeConstPropElementwiseBinary<ONNXDivOp>(
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PatternRewriter &rewriter, Type elementType, Attribute &lhsAttr,
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Attribute &secondAttr) {
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PatternRewriter &rewriter, Type elementType, Attribute lhsAttr,
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Attribute secondAttr) {
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if (elementType.isa<FloatType>()) {
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double lhsVal = lhsAttr.cast<FloatAttr>().getValueAsDouble();
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double rhsVal = secondAttr.cast<FloatAttr>().getValueAsDouble();
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@ -154,8 +154,8 @@ Attribute ComputeConstPropElementwiseBinary<ONNXDivOp>(
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template <typename ElementwiseBinaryOp>
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void RecurseConstPropElementwiseBinary(PatternRewriter &rewriter,
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std::vector<Attribute> &resVector, DenseElementsAttr &lhsAttr,
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DenseElementsAttr &rhsAttr, SmallVector<uint64_t, 4> &lhsIndices,
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std::vector<Attribute> &resVector, DenseElementsAttr lhsAttr,
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DenseElementsAttr rhsAttr, SmallVector<uint64_t, 4> &lhsIndices,
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SmallVector<uint64_t, 4> &rhsIndices, int lhsFreeRank, int rhsFreeRank) {
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if (lhsFreeRank == 0) {
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// Fully defined ranks.
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@ -222,7 +222,7 @@ void RecurseConstPropElementwiseBinary(PatternRewriter &rewriter,
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// generate the new constant operation.
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template <typename ElementwiseBinaryOp>
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DenseElementsAttr ConstPropElementwiseBinary(PatternRewriter &rewriter,
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Value resOperand, Attribute &lhsAttr, Attribute &rhsAttr) {
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Value resOperand, Attribute lhsAttr, Attribute rhsAttr) {
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DenseElementsAttr lhsDenseAttr =
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lhsAttr.dyn_cast_or_null<mlir::DenseElementsAttr>();
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DenseElementsAttr rhsDenseAttr =
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@ -248,13 +248,13 @@ DenseElementsAttr ConstPropElementwiseBinary(PatternRewriter &rewriter,
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template <typename OP>
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Attribute ComputeConstPropElementwiseUnary(
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PatternRewriter &rewriter, Type elementType, Attribute &attr) {
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PatternRewriter &rewriter, Type elementType, Attribute attr) {
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llvm_unreachable("unkonwn operation");
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}
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template <>
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Attribute ComputeConstPropElementwiseUnary<ONNXNegOp>(
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PatternRewriter &rewriter, Type elementType, Attribute &attr) {
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PatternRewriter &rewriter, Type elementType, Attribute attr) {
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if (elementType.isa<FloatType>()) {
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double val = attr.cast<FloatAttr>().getValueAsDouble();
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double res = -val;
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@ -270,7 +270,7 @@ Attribute ComputeConstPropElementwiseUnary<ONNXNegOp>(
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template <>
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Attribute ComputeConstPropElementwiseUnary<ONNXSqrtOp>(
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PatternRewriter &rewriter, Type elementType, Attribute &attr) {
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PatternRewriter &rewriter, Type elementType, Attribute attr) {
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if (elementType.isa<FloatType>()) {
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double val = attr.cast<FloatAttr>().getValueAsDouble();
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double res = sqrt(val);
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@ -281,7 +281,7 @@ Attribute ComputeConstPropElementwiseUnary<ONNXSqrtOp>(
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template <typename ElementwiseUnaryOp>
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void RecurseConstPropElementwiseUnary(PatternRewriter &rewriter,
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std::vector<Attribute> &resVector, DenseElementsAttr &attr,
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std::vector<Attribute> &resVector, DenseElementsAttr attr,
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SmallVector<uint64_t, 4> &indices, int freeRank) {
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if (freeRank == 0) {
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// Fully defined ranks.
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@ -308,7 +308,7 @@ void RecurseConstPropElementwiseUnary(PatternRewriter &rewriter,
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// generate the new constant operation.
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template <typename ElementwiseUnaryOp>
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DenseElementsAttr ConstPropElementwiseUnary(
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PatternRewriter &rewriter, Value resOperand, Attribute &attr) {
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PatternRewriter &rewriter, Value resOperand, Attribute attr) {
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DenseElementsAttr denseAttr =
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attr.dyn_cast_or_null<mlir::DenseElementsAttr>();
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assert(denseAttr && "expected dense attribute");
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@ -329,7 +329,7 @@ DenseElementsAttr ConstPropElementwiseUnary(
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//===----------------------------------------------------------------------===//
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void RecurseConstPropTranspose(PatternRewriter &rewriter,
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std::vector<Attribute> &resVector, DenseElementsAttr &attr,
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std::vector<Attribute> &resVector, DenseElementsAttr attr,
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SmallVector<uint64_t, 4> &indices, SmallVector<uint64_t, 4> &perm,
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int freeRank) {
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if (freeRank == 0) {
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@ -351,7 +351,7 @@ void RecurseConstPropTranspose(PatternRewriter &rewriter,
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}
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DenseElementsAttr ConstPropTranspose(PatternRewriter &rewriter,
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Value resOperand, Attribute &attr, ArrayAttr &permAttr) {
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Value resOperand, Attribute attr, ArrayAttr permAttr) {
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// Read dense attribute, the constant tensor we are transforming.
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DenseElementsAttr denseAttr =
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attr.dyn_cast_or_null<mlir::DenseElementsAttr>();
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@ -378,7 +378,7 @@ DenseElementsAttr ConstPropTranspose(PatternRewriter &rewriter,
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//===----------------------------------------------------------------------===//
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DenseElementsAttr ConstPropUnsqueeze(
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PatternRewriter &rewriter, Value resOperand, Attribute &attr) {
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PatternRewriter &rewriter, Value resOperand, Attribute attr) {
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// Read dense attribute, the constant tensor we are transforming.
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DenseElementsAttr denseAttr =
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attr.dyn_cast_or_null<mlir::DenseElementsAttr>();
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