Run sparse_tanh with vectorization.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/
D139958
pm.addNestedPass<func::FuncOp>(createConvertMathToLLVMPass());
pm.addPass(createConvertMathToLibmPass());
pm.addPass(createConvertComplexToLibmPass());
+ // Repeat convert-vector-to-llvm.
+ pm.addPass(createConvertVectorToLLVMPass(options.lowerVectorToLLVMOptions()));
pm.addPass(createConvertComplexToLLVMPass());
pm.addPass(createConvertFuncToLLVMPass());
pm.addPass(createReconcileUnrealizedCastsPass());
// Do the same run, but now with direct IR generation.
// REDEFINE: %{option} = enable-runtime-library=false
// RUN: %{command}
+//
+// Do the same run, but now with direct IR generation and vectorization.
+// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
+// RUN: %{command}
#SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>