[Mlir-commits] [mlir] Add support of param type for transform.structured.tile_using_forall (PR #72097)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Wed Jan 24 14:55:50 PST 2024
https://github.com/jinchen62 updated https://github.com/llvm/llvm-project/pull/72097
>From 988b39e8e5b5e27e0d4c32abd440d7af4e35d66b Mon Sep 17 00:00:00 2001
From: jinchen62 <jinchenye62 at gmail.com>
Date: Mon, 13 Nov 2023 02:19:39 -0800
Subject: [PATCH] Add support of param type for
transform.structured.tile_using_forall
---
.../Linalg/TransformOps/LinalgTransformOps.td | 24 +--
.../TransformOps/LinalgTransformOps.cpp | 43 ++++--
mlir/test/Dialect/Linalg/tile-to-forall.mlir | 137 +++++++++++++++++-
3 files changed, 182 insertions(+), 22 deletions(-)
diff --git a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
index b139f1ef58b3a99..309573a562872fb 100644
--- a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
@@ -21,10 +21,10 @@ include "mlir/IR/RegionKindInterface.td"
// This is roughly similar to OpFoldResult assuming the handle produces a single
// value in the payload IR.
-def TransformParamTypeOrAnyHandle : Type<
+def TransformAnyParamTypeOrAnyHandle : Type<
Or<[TransformHandleTypeInterface.predicate,
- Transform_ParamType.predicate]>,
- "transform 'param' type or any handle type">;
+ TransformParamTypeInterface.predicate]>,
+ "transform any param type or any handle type">;
//===----------------------------------------------------------------------===//
// Apply...PatternsOp
@@ -691,9 +691,9 @@ def MultiTileSizesOp : Op<Transform_Dialect, "structured.multitile_sizes",
I64Attr:$dimension,
I64Attr:$target_size,
DefaultValuedAttr<I64Attr, "1">:$divisor);
- let results = (outs TransformParamTypeOrAnyHandle:$low_size,
- TransformParamTypeOrAnyHandle:$high_size,
- TransformParamTypeOrAnyHandle:$split_point);
+ let results = (outs TransformAnyParamTypeOrAnyHandle:$low_size,
+ TransformAnyParamTypeOrAnyHandle:$high_size,
+ TransformAnyParamTypeOrAnyHandle:$split_point);
let hasVerifier = 1;
let assemblyFormat =
"$target attr-dict `:` custom<MultitileSizesTypes>("
@@ -1408,7 +1408,7 @@ def SplitOp : Op<Transform_Dialect, "structured.split",
let arguments = (ins TransformHandleTypeInterface:$target,
I64Attr:$dimension,
- Optional<TransformParamTypeOrAnyHandle>:$dynamic_split_point,
+ Optional<TransformAnyParamTypeOrAnyHandle>:$dynamic_split_point,
I64Attr:$static_split_point);
let results = (outs TransformHandleTypeInterface:$first,
TransformHandleTypeInterface:$second);
@@ -1857,7 +1857,7 @@ def TileUsingForOp : Op<Transform_Dialect, "structured.tile_using_for",
}];
let arguments = (ins TransformHandleTypeInterface:$target,
- Variadic<TransformParamTypeOrAnyHandle>:$dynamic_sizes,
+ Variadic<TransformAnyParamTypeOrAnyHandle>:$dynamic_sizes,
DefaultValuedOptionalAttr<DenseI64ArrayAttr, "{}">:$static_sizes,
DefaultValuedOptionalAttr<DenseI64ArrayAttr, "{}">:$interchange,
DefaultValuedOptionalAttr<DenseBoolArrayAttr, "{}">:$scalable_sizes);
@@ -1968,10 +1968,10 @@ def TileUsingForallOp :
}];
let arguments = (ins TransformHandleTypeInterface:$target,
- Variadic<TransformHandleTypeInterface>:$num_threads,
- Variadic<TransformHandleTypeInterface>:$tile_sizes,
- Optional<TransformHandleTypeInterface>:$packed_num_threads,
- Optional<TransformHandleTypeInterface>:$packed_tile_sizes,
+ Variadic<TransformAnyParamTypeOrAnyHandle>:$num_threads,
+ Variadic<TransformAnyParamTypeOrAnyHandle>:$tile_sizes,
+ Optional<TransformAnyParamTypeOrAnyHandle>:$packed_num_threads,
+ Optional<TransformAnyParamTypeOrAnyHandle>:$packed_tile_sizes,
DefaultValuedOptionalAttr<DenseI64ArrayAttr, "{}">:$static_num_threads,
DefaultValuedOptionalAttr<DenseI64ArrayAttr, "{}">:$static_tile_sizes,
OptionalAttr<DeviceMappingArrayAttr>:$mapping);
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index 140bdd1f2db3618..6ae7e09096729c3 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -86,8 +86,9 @@ static FailureOr<LinalgOp> tryApply(Operation *operation, Args &&...args) {
return cast<LinalgOp>(result->getOperation());
}
-/// Assuming that `ofr` is an index attr or a transform dialect handle mapped
-/// to exactly one op with one index result, return that value.
+/// Assuming that `ofr` is an index attr or a param of index type
+/// or a transform dialect handle mapped to exactly one op
+/// with one index result, return that value.
static DiagnosedSilenceableFailure unpackSingleIndexResultPayloadOperations(
transform::TransformState &state, TransformOpInterface transformOp,
SmallVector<OpFoldResult> &result, ArrayRef<OpFoldResult> ofrs) {
@@ -98,12 +99,23 @@ static DiagnosedSilenceableFailure unpackSingleIndexResultPayloadOperations(
result.push_back(ofr);
continue;
}
- auto payloadOps = state.getPayloadOps(ofr.get<Value>());
+
+ Value transformValue = ofr.get<Value>();
+ if (isa<TransformParamTypeInterface>(transformValue.getType())) {
+ ArrayRef<Attribute> params = state.getParams(transformValue);
+ if (params.size() != 1)
+ return transformOp.emitDefiniteFailure()
+ << "requires exactly one parameter associated";
+ result.push_back(params[0]);
+ continue;
+ }
+
+ auto payloadOps = state.getPayloadOps(transformValue);
if (!llvm::hasSingleElement(payloadOps)) {
DiagnosedSilenceableFailure diag =
transformOp.emitSilenceableError()
<< "handle must be mapped to exactly one payload op";
- diag.attachNote(ofr.get<Value>().getLoc())
+ diag.attachNote(transformValue.getLoc())
<< "mapped to " << llvm::range_size(payloadOps) << " payload ops";
return diag;
}
@@ -123,14 +135,27 @@ static DiagnosedSilenceableFailure unpackSingleIndexResultPayloadOperations(
return DiagnosedSilenceableFailure::success();
}
-// Given a list of OpFoldResults that are either index attrs or op
-// handles, return a list of OpFoldResults where all op handles are
-// replaced with the first (and only) OpResult of that payload op. (There
-// must be exactly one mapped payload op and it must have exactly one
-// index result.)
+// Given a list of params that are index attrs or a list of OpFoldResults
+// that are either index attrs or op handles, return a list of OpFoldResults
+// of index attrs or a list of OpFoldResults where all op handles are
+// replaced with the first (and only) OpResult of that payload op.
+// (There must be exactly one parameter associated with the AnyParamType or
+// one mapped payload op which must have exactly one index result.)
static DiagnosedSilenceableFailure unpackSingleIndexResultPayloadOperations(
transform::TransformState &state, TransformOpInterface transformOp,
SmallVector<OpFoldResult> &result, Value packedHandle) {
+ if (isa<TransformParamTypeInterface>(packedHandle.getType())) {
+ ArrayRef<Attribute> params = state.getParams(packedHandle);
+ for (auto param : params) {
+ if (!isa<IntegerAttr>(param))
+ return transformOp.emitDefiniteFailure()
+ << "expected the parameter to be associated with an integer "
+ "attribute";
+ result.push_back(param);
+ }
+ return DiagnosedSilenceableFailure::success();
+ }
+
for (Operation *op : state.getPayloadOps(packedHandle)) {
if (op->getNumResults() != 1 || !op->getResult(0).getType().isIndex()) {
DiagnosedSilenceableFailure diag =
diff --git a/mlir/test/Dialect/Linalg/tile-to-forall.mlir b/mlir/test/Dialect/Linalg/tile-to-forall.mlir
index 2192d160b1150f7..abd807b3e4d3e19 100644
--- a/mlir/test/Dialect/Linalg/tile-to-forall.mlir
+++ b/mlir/test/Dialect/Linalg/tile-to-forall.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s --transform-interpreter -canonicalize -cse -split-input-file | FileCheck %s
+// RUN: mlir-opt %s --transform-interpreter -canonicalize -cse -split-input-file -verify-diagnostics | FileCheck %s
// Offset per thread:
// CHECK-DAG: affine_map<(d0)[s0] -> (d0 * (s0 ceildiv 10))>
@@ -451,3 +451,138 @@ module attributes {transform.with_named_sequence} {
}
}
+// -----
+
+// CHECK-DAG: #[[$map0:.+]] = affine_map<()[s0] -> (s0 ceildiv 10)>
+// CHECK-DAG: #[[$map1:.+]] = affine_map<()[s0] -> (s0 ceildiv 20)>
+// CHECK-DAG: #[[$map2:.+]] = affine_map<(d0)[s0] -> (d0 * -10 + s0, 10)>
+// CHECK-DAG: #[[$map3:.+]] = affine_map<(d0)[s0] -> (d0 * -20 + s0, 20)>
+// CHECK-DAG: #[[$map4:.+]] = affine_map<(d0) -> (d0 * 10)>
+// CHECK-DAG: #[[$map5:.+]] = affine_map<(d0) -> (d0 * 20)>
+
+// CHECK-LABEL: matmul_tile_size_dynamic(
+// CHECK-SAME: %[[A:[0-9a-z]+]]: tensor<?x?xf32>
+// CHECK-SAME: %[[B:[0-9a-z]+]]: tensor<?x?xf32>
+// CHECK-SAME: %[[C:[0-9a-z]+]]: tensor<?x?xf32>
+func.func @matmul_tile_size_dynamic(%A: tensor<?x?xf32>, %B: tensor<?x?xf32>, %C: tensor<?x?xf32>) -> tensor<?x?xf32> {
+ // CHECK: %[[c1:.*]] = arith.constant 1 : index
+ // CHECK: %[[c0:.*]] = arith.constant 0 : index
+ // CHECK: %[[M:.+]] = tensor.dim %[[A]], %[[c0]] :
+ // CHECK: %[[N:.+]] = tensor.dim %[[B]], %[[c1]] :
+ // CHECK: %[[NT0:.+]] = affine.apply #map()[%[[M]]]
+ // CHECK: %[[NT1:.+]] = affine.apply #map1()[%[[N]]]
+ // CHECK: %[[K:.+]] = tensor.dim %[[A]], %[[c1]] :
+ // CHECK: scf.forall (%[[IV0:.+]], %[[IV1:.+]]) in (%[[NT0]], %[[NT1]]) shared_outs(%[[C_BLK:.*]] = %[[C]])
+ // CHECK: %[[TS0:.+]] = affine.min #[[$map2]](%[[IV0]])[%[[M]]]
+ // CHECK: %[[TS1:.+]] = affine.min #[[$map3]](%[[IV1]])[%[[N]]]
+ // CHECK: %[[LB0:.+]] = affine.apply #[[$map4]](%[[IV0]])
+ // CHECK: %[[LB1:.+]] = affine.apply #[[$map5]](%[[IV1]])
+ // CHECK: tensor.extract_slice %[[A]][%[[LB0]], 0] [%[[TS0]], %[[K]]] [1, 1] :
+ // CHECK: tensor.extract_slice %[[B]][0, %[[LB1]]] [%[[K]], %[[TS1]]] [1, 1] :
+ // CHECK: tensor.extract_slice %[[C_BLK]][%[[LB0]], %[[LB1]]] [%[[TS0]], %[[TS1]]] [1, 1] :
+ // CHECK: linalg.matmul
+ // CHECK: scf.forall.in_parallel
+ // CHECK-NEXT: tensor.parallel_insert_slice
+ %0 = linalg.matmul ins(%A, %B : tensor<?x?xf32>, tensor<?x?xf32>)
+ outs(%C : tensor<?x?xf32>) -> (tensor<?x?xf32>)
+ return %0 : tensor<?x?xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %sz = transform.param.constant 10 : i64 -> !transform.param<i64>
+ %1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz : !transform.param<i64>, 20]
+ : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+ transform.yield
+ }
+}
+
+// -----
+
+func.func @matmul_tile_size_dynamic(%A: tensor<?x?xf32>, %B: tensor<?x?xf32>, %C: tensor<?x?xf32>) -> tensor<?x?xf32> {
+ %0 = linalg.matmul ins(%A, %B : tensor<?x?xf32>, tensor<?x?xf32>)
+ outs(%C : tensor<?x?xf32>) -> (tensor<?x?xf32>)
+ return %0 : tensor<?x?xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match ops{["linalg.matmul_transpose_b"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %c10 = transform.param.constant 10 : i64 -> !transform.param<i64>
+ %c20 = transform.param.constant 20 : i64 -> !transform.param<i64>
+ %sz = transform.merge_handles %c10, %c20 : !transform.param<i64>
+ // expected-error @below {{requires exactly one parameter associated}}
+ %1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz : !transform.param<i64>, 20]
+ : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+ transform.yield
+ }
+}
+
+// -----
+
+// CHECK-DAG: #[[$map0:.+]] = affine_map<()[s0] -> (s0 ceildiv 10)>
+// CHECK-DAG: #[[$map1:.+]] = affine_map<()[s0] -> (s0 ceildiv 20)>
+// CHECK-DAG: #[[$map2:.+]] = affine_map<(d0)[s0] -> (d0 * -10 + s0, 10)>
+// CHECK-DAG: #[[$map3:.+]] = affine_map<(d0)[s0] -> (d0 * -20 + s0, 20)>
+// CHECK-DAG: #[[$map4:.+]] = affine_map<(d0) -> (d0 * 10)>
+// CHECK-DAG: #[[$map5:.+]] = affine_map<(d0) -> (d0 * 20)>
+
+// CHECK-LABEL: matmul_tile_size_dynamic(
+// CHECK-SAME: %[[A:[0-9a-z]+]]: tensor<?x?xf32>
+// CHECK-SAME: %[[B:[0-9a-z]+]]: tensor<?x?xf32>
+// CHECK-SAME: %[[C:[0-9a-z]+]]: tensor<?x?xf32>
+func.func @matmul_tile_size_dynamic(%A: tensor<?x?xf32>, %B: tensor<?x?xf32>, %C: tensor<?x?xf32>) -> tensor<?x?xf32> {
+ // CHECK: %[[c1:.*]] = arith.constant 1 : index
+ // CHECK: %[[c0:.*]] = arith.constant 0 : index
+ // CHECK: %[[M:.+]] = tensor.dim %[[A]], %[[c0]] :
+ // CHECK: %[[N:.+]] = tensor.dim %[[B]], %[[c1]] :
+ // CHECK: %[[NT0:.+]] = affine.apply #map()[%[[M]]]
+ // CHECK: %[[NT1:.+]] = affine.apply #map1()[%[[N]]]
+ // CHECK: %[[K:.+]] = tensor.dim %[[A]], %[[c1]] :
+ // CHECK: scf.forall (%[[IV0:.+]], %[[IV1:.+]]) in (%[[NT0]], %[[NT1]]) shared_outs(%[[C_BLK:.*]] = %[[C]])
+ // CHECK: %[[TS0:.+]] = affine.min #[[$map2]](%[[IV0]])[%[[M]]]
+ // CHECK: %[[TS1:.+]] = affine.min #[[$map3]](%[[IV1]])[%[[N]]]
+ // CHECK: %[[LB0:.+]] = affine.apply #[[$map4]](%[[IV0]])
+ // CHECK: %[[LB1:.+]] = affine.apply #[[$map5]](%[[IV1]])
+ // CHECK: tensor.extract_slice %[[A]][%[[LB0]], 0] [%[[TS0]], %[[K]]] [1, 1] :
+ // CHECK: tensor.extract_slice %[[B]][0, %[[LB1]]] [%[[K]], %[[TS1]]] [1, 1] :
+ // CHECK: tensor.extract_slice %[[C_BLK]][%[[LB0]], %[[LB1]]] [%[[TS0]], %[[TS1]]] [1, 1] :
+ // CHECK: linalg.matmul
+ // CHECK: scf.forall.in_parallel
+ // CHECK-NEXT: tensor.parallel_insert_slice
+ %0 = linalg.matmul ins(%A, %B : tensor<?x?xf32>, tensor<?x?xf32>)
+ outs(%C : tensor<?x?xf32>) -> (tensor<?x?xf32>)
+ return %0 : tensor<?x?xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %c10 = transform.param.constant 10 : i64 -> !transform.any_param
+ %c20 = transform.param.constant 20 : i64 -> !transform.any_param
+ %sz = transform.merge_handles %c10, %c20 : !transform.any_param
+ %1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz : !transform.any_param)
+ : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+ transform.yield
+ }
+}
+
+// -----
+
+func.func @matmul_tile_size_dynamic(%A: tensor<?x?xf32>, %B: tensor<?x?xf32>, %C: tensor<?x?xf32>) -> tensor<?x?xf32> {
+ %0 = linalg.matmul ins(%A, %B : tensor<?x?xf32>, tensor<?x?xf32>)
+ outs(%C : tensor<?x?xf32>) -> (tensor<?x?xf32>)
+ return %0 : tensor<?x?xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+ transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+ %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+ %sz = transform.param.constant "[10 : i64, 20 : i64]" -> !transform.any_param
+ // expected-error @below {{expected the parameter to be associated with an integer attribute}}
+ %1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz : !transform.any_param)
+ : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+ transform.yield
+ }
+}
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