106 lines
3.7 KiB
MLIR
106 lines
3.7 KiB
MLIR
// RUN: mlir-opt %s --test-transform-dialect-interpreter -allow-unregistered-dialect --split-input-file --verify-diagnostics | FileCheck %s
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// CHECK-LABEL: func @successful_pass_application(
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// CHECK: %[[c5:.*]] = arith.constant 5 : index
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// CHECK: return %[[c5]]
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func.func @successful_pass_application(%t: tensor<5xf32>) -> index {
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%c0 = arith.constant 0 : index
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%dim = tensor.dim %t, %c0 : tensor<5xf32>
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return %dim : index
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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transform.apply_registered_pass "canonicalize" to %1 : (!transform.any_op) -> !transform.any_op
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}
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// -----
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// CHECK-LABEL: func @pass_pipeline(
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func.func @pass_pipeline() {
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return
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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// This pipeline does not do anything. Just make sure that the pipeline is
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// found and no error is produced.
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transform.apply_registered_pass "test-options-pass-pipeline" to %1 : (!transform.any_op) -> !transform.any_op
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}
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// -----
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func.func @invalid_pass_name() {
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return
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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// expected-error @below {{unknown pass or pass pipeline: non-existing-pass}}
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transform.apply_registered_pass "non-existing-pass" to %1 : (!transform.any_op) -> !transform.any_op
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}
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// -----
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func.func @not_isolated_from_above(%t: tensor<5xf32>) -> index {
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%c0 = arith.constant 0 : index
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// expected-note @below {{target op}}
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// expected-error @below {{trying to schedule a pass on an operation not marked as 'IsolatedFromAbove'}}
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%dim = tensor.dim %t, %c0 : tensor<5xf32>
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return %dim : index
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["tensor.dim"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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// expected-error @below {{pass pipeline failed}}
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transform.apply_registered_pass "canonicalize" to %1 : (!transform.any_op) -> !transform.any_op
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}
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// -----
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func.func @invalid_pass_option() {
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return
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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// expected-error @below {{failed to add pass or pass pipeline to pipeline: canonicalize}}
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transform.apply_registered_pass "canonicalize" to %1 {options = "invalid-option=1"} : (!transform.any_op) -> !transform.any_op
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}
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// -----
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// CHECK-LABEL: func @valid_pass_option()
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func.func @valid_pass_option() {
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return
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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transform.apply_registered_pass "canonicalize" to %1 {options = "top-down=false"} : (!transform.any_op) -> !transform.any_op
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}
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// -----
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module {
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// expected-error @below {{trying to schedule a pass on an unsupported operation}}
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// expected-note @below {{target op}}
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func.func @invalid_target_op_type() {
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return
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}
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transform.sequence failures(propagate) {
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^bb1(%arg1: !transform.any_op):
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%1 = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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// func-bufferize can be applied only to ModuleOps.
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// expected-error @below {{pass pipeline failed}}
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transform.apply_registered_pass "func-bufferize" to %1 : (!transform.any_op) -> !transform.any_op
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}
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}
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