llvm-project/mlir/test/Dialect/Linalg/transform-op-split-reductio...

36 lines
1.5 KiB
MLIR

// RUN: mlir-opt --test-transform-dialect-interpreter %s | FileCheck %s
// CHECK-LABEL: func.func @matmul_split
func.func @matmul_split(%A : tensor<?x256xf32>, %B: tensor<256x32xf32>, %C: tensor<?x32xf32>) -> tensor<?x32xf32> {
// CHECK: linalg.generic
// CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "reduction"]
// CHECK-SAME: ins(%{{[a-zA-Z0-9]*}}, %{{[a-zA-Z0-9]*}}, %{{[a-zA-Z0-9]*}} : tensor<?x256xf32>, tensor<256x32xf32>, tensor<64x4xi1>)
// CHECK-SAME: outs(%{{[a-zA-Z0-9]*}} : tensor<?x32x64xf32>) {
// CHECK: linalg.generic
// CHECK-SAME: iterator_types = ["parallel", "parallel", "reduction"]
// CHECK-SAME: ins(%{{[a-zA-Z0-9]*}} : tensor<?x32x64xf32>)
// CHECK-SAME: outs(%{{[a-zA-Z0-9]*}} : tensor<?x32xf32>) {
%0 = linalg.matmul ins(%A, %B: tensor<?x256xf32>, tensor<256x32xf32>)
outs(%C: tensor<?x32xf32>) -> tensor<?x32xf32>
return %0: tensor<?x32xf32>
}
transform.with_pdl_patterns {
^bb0(%arg0: !pdl.operation):
pdl.pattern @pdl_target : benefit(1) {
%args = operands
%results = types
%0 = pdl.operation "linalg.matmul"(%args : !pdl.range<value>) -> (%results : !pdl.range<type>)
// TODO: we don't want this, but it is the required terminator for pdl.pattern
rewrite %0 with "transform.dialect"
}
transform.sequence %arg0 {
^bb1(%arg1: !pdl.operation):
%0 = pdl_match @pdl_target in %arg1
%1:3 = transform.structured.split_reduction_by_scaling %0 { split_factor = 4, insert_split_dimension = 2}
}
}