// RUN: mlir-opt %s -allow-unregistered-dialect \ // RUN: -transform-interpreter -canonicalize \ // RUN: -split-input-file -verify-diagnostics | FileCheck %s // This is a test case where "high" padding depends on the IV. // CHECK: #[[$map:.*]] = affine_map<()[s0, s1] -> (s0 - s1)> // CHECK: #[[$map1:.*]] = affine_map<(d0)[s0, s1] -> (-d0 + s0 + s1 + 5)> // CHECK-LABEL: func @make_pad_loop_independent_1( // CHECK-SAME: %[[lb:.*]]: index, %[[ub:.*]]: index, %[[step:.*]]: index, // CHECK-SAME: %[[t:.*]]: tensor func.func @make_pad_loop_independent_1(%lb: index, %ub: index, %step: index, %t: tensor, %f: f32) { // CHECK: scf.for %[[iv:.*]] = %[[lb]] to %[[ub]] scf.for %i = %lb to %ub step %step { // CHECK: %[[high:.*]] = affine.apply #[[$map]]()[%[[ub]], %[[lb]]] // CHECK: %[[padded:.*]] = tensor.pad %[[t]] low[5] high[%[[high]]] // CHECK: %[[dim:.*]] = tensor.dim %[[t]] // CHECK: %[[size:.*]] = affine.apply #[[$map1]](%[[iv]])[%[[ub]], %[[dim]]] // CHECK: %[[replacement:.*]] = tensor.extract_slice %[[padded]][0] [%[[size]]] [1] %high = affine.apply affine_map<(d0)[s0] -> (s0 - d0)> (%i)[%ub] %p = tensor.pad %t low[5] high[%high] { ^bb0(%arg1: index): tensor.yield %f : f32 } : tensor to tensor // CHECK: "dummy.some_use"(%[[replacement]]) "dummy.some_use"(%p) : (tensor) -> () } return } module attributes {transform.with_named_sequence} { transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op %1 = transform.tensor.make_loop_independent %0 {num_loops = 1} : (!transform.any_op) -> !transform.any_op transform.yield } } // ----- // This is a test case where "low" padding depends on the IV. // CHECK: #[[$map:.*]] = affine_map<()[s0, s1] -> (s0 - s1)> // CHECK: #[[$map1:.*]] = affine_map<(d0)[s0, s1] -> (-d0 + s0 + s1 + 5)> // CHECK: #[[$map2:.*]] = affine_map<(d0)[s0] -> (d0 - s0)> // CHECK-LABEL: func @make_pad_loop_independent_1( // CHECK-SAME: %[[lb:.*]]: index, %[[ub:.*]]: index, %[[step:.*]]: index, // CHECK-SAME: %[[t:.*]]: tensor func.func @make_pad_loop_independent_1(%lb: index, %ub: index, %step: index, %t: tensor, %f: f32) { // CHECK: scf.for %[[iv:.*]] = %[[lb]] to %[[ub]] scf.for %i = %lb to %ub step %step { // CHECK: %[[low:.*]] = affine.apply #[[$map]]()[%[[ub]], %[[lb]]] // CHECK: %[[padded:.*]] = tensor.pad %[[t]] low[%[[low]]] high[5] // CHECK: %[[dim:.*]] = tensor.dim %[[t]] // CHECK: %[[size:.*]] = affine.apply #[[$map1]](%[[iv]])[%[[ub]], %[[dim]]] // CHECK: %[[offset:.*]] = affine.apply #[[$map2]](%[[iv]])[%[[lb]]] // CHECK: %[[replacement:.*]] = tensor.extract_slice %[[padded]][%[[offset]]] [%[[size]]] [1] %low = affine.apply affine_map<(d0)[s0] -> (s0 - d0)> (%i)[%ub] %p = tensor.pad %t low[%low] high[5] { ^bb0(%arg1: index): tensor.yield %f : f32 } : tensor to tensor // CHECK: "dummy.some_use"(%[[replacement]]) "dummy.some_use"(%p) : (tensor) -> () } return } module attributes {transform.with_named_sequence} { transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op %1 = transform.tensor.make_loop_independent %0 {num_loops = 1} : (!transform.any_op) -> !transform.any_op transform.yield } } // ----- // CHECK: #[[$map:.*]] = affine_map<()[s0] -> (s0 * 2 - 2)> // CHECK-LABEL: func @two_loops( func.func @two_loops(%lb: index, %ub: index, %step: index, %t: tensor, %f: f32) { scf.for %i = %lb to %ub step %step { scf.for %j = %lb to %ub step %step { // CHECK: affine.apply #map()[%{{.*}}] %low = affine.apply affine_map<(d0, d1)[] -> (d0 + d1)> (%i, %j)[] %p = tensor.pad %t low[%low] high[5] { ^bb0(%arg1: index): tensor.yield %f : f32 } : tensor to tensor "dummy.some_use"(%p) : (tensor) -> () } } return } module attributes {transform.with_named_sequence} { transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op %1 = transform.tensor.make_loop_independent %0 {num_loops = 2} : (!transform.any_op) -> !transform.any_op transform.yield } } // ----- func.func @not_enough_loops(%lb: index, %ub: index, %step: index, %t: tensor, %f: f32) { scf.for %i = %lb to %ub step %step { scf.for %j = %lb to %ub step %step { %low = affine.apply affine_map<(d0, d1)[] -> (d0 + d1)> (%i, %j)[] // expected-note@below {{target op}} %p = tensor.pad %t low[%low] high[5] { ^bb0(%arg1: index): tensor.yield %f : f32 } : tensor to tensor "dummy.some_use"(%p) : (tensor) -> () } } return } module attributes {transform.with_named_sequence} { transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { %0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op // expected-error@below {{could not find 2-th enclosing loop}} %1 = transform.tensor.make_loop_independent %0 {num_loops = 3} : (!transform.any_op) -> !transform.any_op transform.yield } } // ----- // CHECK: #[[$map:.*]] = affine_map<(d0)[s0] -> (-d0 + s0)> // CHECK: #[[$map1:.*]] = affine_map<()[s0, s1] -> (s0 - s1)> // CHECK-LABEL: func @make_empty_loop_independent( // CHECK-SAME: %[[lb:.*]]: index, %[[ub:.*]]: index, %[[step:.*]]: index) func.func @make_empty_loop_independent(%lb: index, %ub: index, %step: index) { // CHECK: scf.for %[[iv:.*]] = %[[lb]] to %[[ub]] scf.for %i = %lb to %ub step %step { // CHECK: %[[slice_sz:.*]] = affine.apply #[[$map]](%[[iv]])[%[[ub]]] // CHECK: %[[empty_sz:.*]] = affine.apply #[[$map1]]()[%[[ub]], %[[lb]]] // CHECK: %[[empty:.*]] = tensor.empty(%[[empty_sz]]) : tensor // CHECK: %[[replacement:.*]] = tensor.extract_slice %[[empty]][0] [%[[slice_sz]]] [1] %sz = affine.apply affine_map<(d0)[s0] -> (s0 - d0)> (%i)[%ub] %empty = tensor.empty(%sz) : tensor // CHECK: "dummy.some_use"(%[[replacement]]) "dummy.some_use"(%empty) : (tensor) -> () } return } module attributes {transform.with_named_sequence} { transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { %0 = transform.structured.match ops{["tensor.empty"]} in %arg1 : (!transform.any_op) -> !transform.any_op %1 = transform.tensor.make_loop_independent %0 {num_loops = 1} : (!transform.any_op) -> !transform.any_op transform.yield } }