Integrate LLVM at llvm/llvm-project@1b97cdf885
Updates LLVM usage to match [1b97cdf885d6](https://github.com/llvm/llvm-project/commit/1b97cdf885d6) PiperOrigin-RevId: 348587513
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@ -15,9 +15,9 @@
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load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
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load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
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LLVM_COMMIT = "511cfe9441955f20a8b93573fb9b62433b053550"
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LLVM_COMMIT = "1b97cdf885d6455841280b8da858835e641ee941"
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LLVM_SHA256 = "57626cf2eb850c717b712e43774cad308f19cd9161db9ed286844ba8f42abd70"
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LLVM_SHA256 = "80d5036ba734fcb700a5699e2f99e5a0de5808dde01a1df3c4fae04510bc8e23"
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LLVM_BAZEL_TAG = "llvm-project-{commit}".format(commit = LLVM_COMMIT)
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LLVM_BAZEL_TAG = "llvm-project-{commit}".format(commit = LLVM_COMMIT)
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@ -1,2 +1,2 @@
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511cfe9441955f20a8b93573fb9b62433b053550
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1b97cdf885d6455841280b8da858835e641ee941
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@ -202,7 +202,7 @@ LogicalResult BroadcastCompareOp::inferReturnTypeComponents(
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MLIRContext* context, Optional<Location> location, ValueRange operands,
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MLIRContext* context, Optional<Location> location, ValueRange operands,
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DictionaryAttr attributes, RegionRange regions,
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DictionaryAttr attributes, RegionRange regions,
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SmallVectorImpl<ShapedTypeComponents>& inferedReturnShapes) {
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SmallVectorImpl<ShapedTypeComponents>& inferedReturnShapes) {
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Type element_type = IntegerType::get(1, context);
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Type element_type = IntegerType::get(context, 1);
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return InferBroadcastBinaryOpReturnTypeComponents(context, location, operands,
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return InferBroadcastBinaryOpReturnTypeComponents(context, location, operands,
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attributes, element_type,
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attributes, element_type,
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inferedReturnShapes);
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inferedReturnShapes);
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@ -621,7 +621,7 @@ OpFoldResult GetTupleElementOp::fold(ArrayRef<Attribute> operands) {
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static LogicalResult Verify(TupleOp op) {
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static LogicalResult Verify(TupleOp op) {
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SmallVector<Type, 8> operandTypes = {op.operand_type_begin(),
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SmallVector<Type, 8> operandTypes = {op.operand_type_begin(),
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op.operand_type_end()};
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op.operand_type_end()};
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auto expectedType = TupleType::get(operandTypes, op.getContext());
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auto expectedType = TupleType::get(op.getContext(), operandTypes);
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if (op.getType() != expectedType) {
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if (op.getType() != expectedType) {
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return op.emitOpError(llvm::formatv("has return type {0}, but expected {1}",
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return op.emitOpError(llvm::formatv("has return type {0}, but expected {1}",
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op.getType(), expectedType));
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op.getType(), expectedType));
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@ -1967,7 +1967,7 @@ LogicalResult ReplicaIdOp::inferReturnTypes(
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MLIRContext* context, Optional<Location>, ValueRange operands,
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MLIRContext* context, Optional<Location>, ValueRange operands,
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DictionaryAttr, RegionRange, SmallVectorImpl<Type>& inferredReturnTypes) {
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DictionaryAttr, RegionRange, SmallVectorImpl<Type>& inferredReturnTypes) {
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inferredReturnTypes.push_back(RankedTensorType::get(
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inferredReturnTypes.push_back(RankedTensorType::get(
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/*shape=*/{}, IntegerType::get(32, IntegerType::Unsigned, context)));
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/*shape=*/{}, IntegerType::get(context, 32, IntegerType::Unsigned)));
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return success();
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return success();
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}
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}
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@ -145,7 +145,7 @@ class ConvertIotaOp : public OpRewritePattern<mhlo::IotaOp> {
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auto int_shape_type = RankedTensorType::get(
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auto int_shape_type = RankedTensorType::get(
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output_type.getShape(),
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output_type.getShape(),
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IntegerType::get(bitwidth, rewriter.getContext()));
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IntegerType::get(rewriter.getContext(), bitwidth));
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auto loc = op.getLoc();
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auto loc = op.getLoc();
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auto integer_const = rewriter.create<mlir::ConstantOp>(
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auto integer_const = rewriter.create<mlir::ConstantOp>(
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loc, DenseIntElementsAttr::get(int_shape_type, values));
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loc, DenseIntElementsAttr::get(int_shape_type, values));
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