xref: /llvm-project/mlir/test/Dialect/SparseTensor/transform-ops.mlir (revision 2798b72ae7e5caad793169b77cbac47fe2362d0f)
1// RUN: mlir-opt %s --transform-interpreter --verify-diagnostics --split-input-file
2
3module attributes { transform.with_named_sequence } {
4  transform.named_sequence @match_sparse_structured(%arg0: !transform.any_op {transform.readonly}) -> !transform.any_op {
5    %0 = transform.match.structured %arg0 : (!transform.any_op) -> !transform.any_op {
6    ^bb0(%struct: !transform.any_op):
7      %sp_kernel = transform.sparse_tensor.match.sparse_inout %struct
8          : (!transform.any_op) -> !transform.any_op
9      transform.match.structured.yield %sp_kernel : !transform.any_op
10    }
11    transform.yield %0 : !transform.any_op
12  }
13
14  transform.named_sequence @print_sparse_structured(%arg0: !transform.any_op {transform.readonly}) {
15    transform.debug.emit_remark_at %arg0, "sparse_kernel" : !transform.any_op
16    transform.yield
17  }
18
19  // Entry point. Match any structured sparse operation and emit at remark.
20  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.consumed}) {
21    transform.foreach_match in %arg0
22        @match_sparse_structured -> @print_sparse_structured
23        : (!transform.any_op) -> !transform.any_op
24    transform.yield
25  }
26}
27
28#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
29
30func.func @payload(%lhs: tensor<10x20xf16>,
31                   %sp_lhs: tensor<10x20xf16, #CSR>,
32                   %rhs: tensor<20x15xf32>) -> tensor<10x15xf64>{
33  %cst = arith.constant 0.0 : f64
34  %empty = tensor.empty() : tensor<10x15xf64>
35  %fill = linalg.fill ins(%cst : f64) outs(%empty : tensor<10x15xf64>) -> tensor<10x15xf64>
36
37  %result = linalg.matmul ins(%lhs, %rhs: tensor<10x20xf16>, tensor<20x15xf32>)
38                         outs(%fill: tensor<10x15xf64>) -> tensor<10x15xf64>
39  // expected-remark @below {{sparse_kernel}}
40  %sp_in = linalg.matmul ins(%sp_lhs, %rhs: tensor<10x20xf16, #CSR>, tensor<20x15xf32>)
41                        outs(%fill: tensor<10x15xf64>) -> tensor<10x15xf64>
42
43  %sp_empty = tensor.empty() : tensor<10x15xf64, #CSR>
44  // expected-remark @below {{sparse_kernel}}
45  %sp_out = linalg.matmul ins(%lhs, %rhs: tensor<10x20xf16>, tensor<20x15xf32>)
46                         outs(%sp_empty: tensor<10x15xf64, #CSR>) -> tensor<10x15xf64, #CSR>
47  return %result : tensor<10x15xf64>
48}
49