// 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<?xf32>
func.func @make_pad_loop_independent_1(%lb: index, %ub: index, %step: index,
%t: tensor<?xf32>, %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<?xf32> to tensor<?xf32>
// CHECK: "dummy.some_use"(%[[replacement]])
"dummy.some_use"(%p) : (tensor<?xf32>) -> ()
}
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: #[[$map2:.*]] = affine_map<(d0)[s0] -> (d0 - s0)>
// CHECK-LABEL: func @make_pad_loop_independent_1(
// CHECK-SAME: %[[lb:.*]]: index, %[[ub:.*]]: index, %[[step:.*]]: index,
// CHECK-SAME: %[[t:.*]]: tensor<?xf32>
func.func @make_pad_loop_independent_1(%lb: index, %ub: index, %step: index,
%t: tensor<?xf32>, %f: f32) {
// CHECK: scf.for %[[iv:.*]] = %[[lb]] to %[[ub]]
scf.for %i = %lb to %ub step %step {
// CHECK: %[[low:.*]] = affine.apply #[[$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<?xf32> to tensor<?xf32>
// CHECK: "dummy.some_use"(%[[replacement]])
"dummy.some_use"(%p) : (tensor<?xf32>) -> ()
}
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: #[[$map:.*]] = affine_map<()[s0] -> (s0 * 2 - 2)>
// CHECK-LABEL: func @two_loops(
func.func @two_loops(%lb: index, %ub: index, %step: index,
%t: tensor<?xf32>, %f: f32) {
scf.for %i = %lb to %ub step %step {
scf.for %j = %lb to %ub step %step {
// CHECK: affine.apply #map()[%{{.*}}]
%low = affine.apply affine_map<(d0, d1)[] -> (d0 + d1)> (%i, %j)[]
%p = tensor.pad %t low[%low] high[5] {
^bb0(%arg1: index):
tensor.yield %f : f32
} : tensor<?xf32> to tensor<?xf32>
"dummy.some_use"(%p) : (tensor<?xf32>) -> ()
}
}
return
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1 = transform.tensor.make_loop_independent %0 {num_loops = 2} : (!transform.any_op) -> !transform.any_op
transform.yield
}
}
// -----
func.func @not_enough_loops(%lb: index, %ub: index, %step: index,
%t: tensor<?xf32>, %f: f32) {
scf.for %i = %lb to %ub step %step {
scf.for %j = %lb to %ub step %step {
%low = affine.apply affine_map<(d0, d1)[] -> (d0 + d1)> (%i, %j)[]
// expected-note@below {{target op}}
%p = tensor.pad %t low[%low] high[5] {
^bb0(%arg1: index):
tensor.yield %f : f32
} : tensor<?xf32> to tensor<?xf32>
"dummy.some_use"(%p) : (tensor<?xf32>) -> ()
}
}
return
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
// expected-error@below {{could not find 2-th enclosing loop}}
%1 = transform.tensor.make_loop_independent %0 {num_loops = 3} : (!transform.any_op) -> !transform.any_op
transform.yield
}
}
// -----
// CHECK: #[[$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<?xf32>
// 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<?xf32>
// CHECK: "dummy.some_use"(%[[replacement]])
"dummy.some_use"(%empty) : (tensor<?xf32>) -> ()
}
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
}
}