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// RUN: mlir-opt %s -convert-scf-to-std \
// RUN: -convert-vector-to-llvm='reassociate-fp-reductions' \
// RUN: -convert-std-to-llvm | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s
func @entry() {
// Construct test vector, numerically very stable.
%f1 = constant 1.0: f64
%f2 = constant 2.0: f64
%f3 = constant 3.0: f64
%v0 = vector.broadcast %f1 : f64 to vector<64xf64>
%v1 = vector.insert %f2, %v0[11] : f64 into vector<64xf64>
%v2 = vector.insert %f3, %v1[52] : f64 into vector<64xf64>
vector.print %v2 : vector<64xf64>
//
// test vector:
//
// CHECK: ( 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 )
// Various vector reductions. Not full functional unit tests, but
// a simple integration test to see if the code runs end-to-end.
%0 = vector.reduction "add", %v2 : vector<64xf64> into f64
vector.print %0 : f64
// CHECK: 67
%1 = vector.reduction "mul", %v2 : vector<64xf64> into f64
vector.print %1 : f64
// CHECK: 6
%2 = vector.reduction "min", %v2 : vector<64xf64> into f64
vector.print %2 : f64
// CHECK: 1
%3 = vector.reduction "max", %v2 : vector<64xf64> into f64
vector.print %3 : f64
// CHECK: 3
return
}
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