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// RUN: mlir-opt %s --test-transform-dialect-interpreter -allow-unregistered-dialect --split-input-file --verify-diagnostics
func.func @bar() {
// expected-remark @below {{matched op name}}
// expected-remark @below {{matched attr name}}
%0 = arith.constant {my_attr} 0: i32
// expected-remark @below {{matched op name}}
%1 = arith.constant 1 : i32
return
}
transform.sequence failures(propagate) {
^bb1(%arg1: !transform.any_op):
%match_name = transform.structured.match ops{["arith.constant"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.test_print_remark_at_operand %match_name, "matched op name" : !transform.any_op
transform.test_consume_operand %match_name : !transform.any_op
%match_attr = transform.structured.match ops{["arith.constant"]} attributes{my_attr} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.test_print_remark_at_operand %match_attr, "matched attr name" : !transform.any_op
transform.test_consume_operand %match_attr : !transform.any_op
}
// -----
func.func @by_type() {
%0 = arith.constant 0: i32
// expected-remark @below {{matched op name}}
%1 = arith.constant 1.0 : f32
return
}
transform.sequence failures(propagate) {
^bb1(%arg1: !transform.any_op):
%match_name = transform.structured.match
ops{["arith.constant"]} filter_result_type = f32 in %arg1 : (!transform.any_op) -> !transform.any_op
transform.test_print_remark_at_operand %match_name, "matched op name" : !transform.any_op
transform.test_consume_operand %match_name : !transform.any_op
}
// -----
#map0 = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
#map1 = affine_map<(d0, d1, d2) -> (d1, d0, d2)>
func.func @match_complex_attribute(%arg0: tensor<12x128x32xf32>)
-> tensor<128x12x32xf32> {
%0 = tensor.empty() : tensor<128x12x32xf32>
// expected-remark @below {{matched complex attr}}
%1 = linalg.generic {indexing_maps = [#map0, #map1],
iterator_types = ["parallel", "parallel", "parallel"]}
ins(%arg0 : tensor<12x128x32xf32>)
outs(%0 : tensor<128x12x32xf32>) {
^bb0(%arg1: f32, %arg2: f32):
linalg.yield %arg1 : f32
} -> tensor<128x12x32xf32>
return %1 : tensor<128x12x32xf32>
}
transform.sequence failures(propagate) {
^bb1(%arg1: !transform.any_op):
%match_attr = transform.structured.match
ops{["linalg.generic"]}
attributes{iterator_types = [
#linalg.iterator_type<parallel>,
#linalg.iterator_type<parallel>,
#linalg.iterator_type<parallel>]}
in %arg1 : (!transform.any_op) -> !transform.any_op
transform.test_print_remark_at_operand %match_attr, "matched complex attr" : !transform.any_op
transform.test_consume_operand %match_attr : !transform.any_op
%no_match = transform.structured.match
attributes{iterator_types = [
#linalg.iterator_type<parallel>,
#linalg.iterator_type<parallel>,
#linalg.iterator_type<reduction>]}
in %arg1 : (!transform.any_op) -> !transform.any_op
// expected-remark @below {{0}}
transform.test_print_number_of_associated_payload_ir_ops %no_match : !transform.any_op
}
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