[mlir][Interfaces] Add interface methods to allow reifying single result/single dim of result.

Current implementation of `reifyResultShapes` forces all
implementations to return all dimensions of all results. This can be
wasteful when you only require dimensions of one result, or a single
dimension of a result.  This was initially done with the restriction
in mind that it might not always be possible to compute dimension of a
single result or one dimension of a single result in all cases. To
handle such cases

- `reifyShapeOfResult` (which allows reifying dimensions of
  just one result), has a default implementation that calls
  `reifyResultShapes` and returns the dimensions of a single result.
- `reifyDimOfResult` (which allows reifying a single dimension of a
  single result) has a default implementation that calls
  `reifyDimOfResult` and returns the value for the dimension of the
  result (which in turn for the default case would call
  `reifyDimOfResult`).

Changes required downstream to integrate this change

1. In operation definitions in .td files, for those operations that
   implement the `ReifyRankedShapedTypeOpInterface`.

```
def <op-name> : Op<..., [...,
    DeclareOpInterfaceMethods[ReifyRankedShapedTypeOpInterface]]>
```

should be changed to

```
def <op-name> : Op<..., [...,
    DeclareOpInterfaceMethods[ReifyRankedShapedTypeOpInterface, [
        "reifyResultShapes"]]]>
```

Signed-off-by: MaheshRavishankar <[email protected]>

Author: MaheshRavishankar

mlir/include/mlir/Dialect/Bufferization/IR/BufferizationOps.td

@@ -28,7 +28,8 @@ class Bufferization_Op<string mnemonic, list<Trait> traits = []>
 
 def Bufferization_AllocTensorOp : Bufferization_Op<"alloc_tensor",
     [AttrSizedOperandSegments, BufferizableOpInterface,
-     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>]> {
+     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+       "reifyResultShapes"]>]> {
   let summary = "allocate buffer for a tensor";
 
   let description = [{
@@ -219,7 +220,8 @@ def Bufferization_MaterializeInDestinationOp
     : Bufferization_Op<"materialize_in_destination",
         [AllElementTypesMatch<["source", "dest"]>,
          BufferizableOpInterface, DestinationStyleOpInterface,
-         DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+         DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+           "reifyResultShapes"]>,
          DeclareOpInterfaceMethods<SubsetOpInterface,
             ["operatesOnEquivalentSubset", "operatesOnDisjointSubset"]>,
          DeclareOpInterfaceMethods<SubsetInsertionOpInterface,

mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td

@@ -94,7 +94,8 @@ def Linalg_IndexOp : Linalg_Op<"index", [Pure]>,
 def Linalg_SoftmaxOp : Linalg_Op<"softmax",
     [DestinationStyleOpInterface,
      PredOpTrait<"input and output have same element type", TCopVTEtIsSameAs<0, 1>>,
-     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface,
+      ["reifyResultShapes"]>,
      DeclareOpInterfaceMethods<AggregatedOpInterface, ["decomposeOperation"]>,
      DeclareOpInterfaceMethods<MemoryEffectsOpInterface>,
      DeclareOpInterfaceMethods<TilingInterface,

mlir/include/mlir/Dialect/Linalg/IR/LinalgRelayoutOps.td

@@ -35,7 +35,8 @@ class Linalg_RelayoutOp<string mnemonic, list<Trait> traits = []> :
         DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
         DestinationStyleOpInterface, LinalgRelayoutOpInterface,
         ConditionallySpeculatable, NoMemoryEffect,
-        DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+        DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+          "reifyResultShapes"]>,
         TypesMatchWith<"result type matches type of dest",
                    "dest", "result",
                    "$_self">])> {

mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td

@@ -1776,7 +1776,8 @@ class MemRef_ReassociativeReshapeOp<string mnemonic, list<Trait> traits = []> :
 def MemRef_ExpandShapeOp : MemRef_ReassociativeReshapeOp<"expand_shape", [
     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
     DeclareOpInterfaceMethods<MemorySpaceCastConsumerOpInterface>,
-    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>]> {
+    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface,
+      ["reifyResultShapes"]>]> {
   let summary = "operation to produce a memref with a higher rank.";
   let description = [{
     The `memref.expand_shape` op produces a new view with a higher rank whose

mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td

@@ -131,7 +131,9 @@ def Tensor_CastOp : Tensor_Op<"cast", [
 def Tensor_ConcatOp : Tensor_Op<"concat",
     [Pure,
      DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
-     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>]> {
+     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+       "reifyResultShapes"]>,
+     ]> {
   let summary = "tensor concatenation operation";
   let description = [{
     The "concat" operation constructs a tensor out of a variadic list of input
@@ -261,7 +263,8 @@ def Tensor_DimOp : Tensor_Op<"dim", [
 
 def Tensor_EmptyOp : Tensor_Op<"empty",
     [Pure,
-     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>]> {
+     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+       "reifyResultShapes"]>]> {
   let summary = "empty tensor operation";
 
   let description = [{
@@ -358,7 +361,8 @@ def Tensor_ExtractOp : Tensor_Op<"extract", [
 
 def Tensor_ExtractSliceOp : Tensor_OpWithOffsetSizesAndStrides<"extract_slice", [
     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
-    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+      "reifyResultShapes"]>,
     AttrSizedOperandSegments,
     Pure,
     OffsetSizeAndStrideOpInterface
@@ -740,7 +744,8 @@ def Tensor_GatherOp : Tensor_Op<"gather", [
 def Tensor_GenerateOp : Tensor_Op<"generate", [
     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
     RecursiveMemoryEffects,
-    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+      "reifyResultShapes"]>,
     SingleBlockImplicitTerminator<"mlir::tensor::YieldOp">]> {
   let summary = "Creates a dynamically sized tensor from elements";
   let description = [{
@@ -835,7 +840,8 @@ def Tensor_InsertOp : Tensor_Op<"insert", [
 
 def Tensor_InsertSliceOp : Tensor_OpWithOffsetSizesAndStrides<"insert_slice", [
     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
-    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+      "reifyResultShapes"]>,
     AttrSizedOperandSegments,
     DestinationStyleOpInterface,
     Pure,
@@ -1256,7 +1262,8 @@ def Tensor_CollapseShapeOp : Tensor_ReassociativeReshapeOp<"collapse_shape"> {
 
 def Tensor_PadOp : Tensor_Op<"pad", [
     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
-    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, [
+      "reifyResultShapes"]>,
     AttrSizedOperandSegments,
     Pure,
     SingleBlockImplicitTerminator<"mlir::tensor::YieldOp">]> {
@@ -1764,7 +1771,8 @@ def Tensor_ScatterOp : Tensor_Op<"scatter", [
 
 def Tensor_SplatOp : Tensor_Op<"splat", [
     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
-    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+    DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, 
+      ["reifyResultShapes"]>,
     Pure,
     TypesMatchWith<"operand type matches element type of result",
                    "aggregate", "input",

mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td

@@ -2186,7 +2186,8 @@ def Tosa_TileOp : Tosa_InferShapedTypeOp<"tile"> {
 // Operator: transpose
 //===----------------------------------------------------------------------===//
 def Tosa_TransposeOp : Tosa_InferShapedTypeOp<"transpose",
-                [DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>,
+                [DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface ,
+                                           ["reifyResultShapes"]>,
                  AllElementTypesMatch<["input1", "output"]>]> {
   let summary = "Transpose operator.";
 

mlir/include/mlir/Interfaces/InferTypeOpInterface.td

@@ -361,20 +361,76 @@ def ReifyRankedShapedTypeOpInterface :
   let methods = [
     InterfaceMethod<
       /*desc=*/[{
-        Reify the shape of the result of an operation (typically in terms of the
-        shape of its operands).
+        Reify the shapes of all the result of an operation (typically in terms 
+        of the shape of its operands).
 
         `reifiedReturnShapes` is populated with one vector per op result. Each
         of those vectors contains an OpFoldResult for each dimension of the
         shaped type. The given builder may be used to insert ops that compute
         result shapes.
 
-        If the shape of a particular result cannot be computed it must be empty.
+        If the shape of a particular result cannot be computed it in terms of
+        its operands it must be left empty. If any dimension of the result cannot
+        be computed it must be set to OpFoldResult().
       }],
       /*retTy=*/"::llvm::LogicalResult",
       /*methodName=*/"reifyResultShapes",
       /*args=*/(ins "::mlir::OpBuilder &":$builder,
-        "::mlir::ReifiedRankedShapedTypeDims &":$reifiedReturnShapes)
+        "::mlir::ReifiedRankedShapedTypeDims &":$reifiedReturnShapes),
+      /*methodBody=*/"",
+      /*defaultImplementation=*/[{ return ::mlir::failure(); }]
+    >,
+    InterfaceMethod<
+      /*desc=*/[{
+        Reify the shape of a single result of an operation (typically in terms 
+        of the shape of its operands).
+
+        Returns the shape of a single result of the operation as a
+        `SmallVector<OpFoldResult>`, one per dimension of the shaped type. The
+        given builder may be used to insert ops that compute result shapes.
+
+        If any dimension of the result cannot be computed it must be set to
+        OpFoldResult().
+      }],
+      /*retTy=*/"::llvm::FailureOr<SmallVector<::mlir::OpFoldResult>>",
+      /*methodName=*/"reifyShapeOfResult",
+      /*args=*/(ins "::mlir::OpBuilder &":$builder,
+        "int":$resultIndex),
+      /*methodBody=*/"",
+      /*defaultImplementation=*/[{
+        ReifiedRankedShapedTypeDims reifiedShapes;
+        if (failed(cast<ReifyRankedShapedTypeOpInterface>($_op.getOperation()).reifyResultShapes(builder, reifiedShapes)))
+          return failure();
+        if (resultIndex < 0 || resultIndex >= (int)(reifiedShapes.size()))
+          return $_op.emitOpError("invalid result index");
+        return reifiedShapes[resultIndex];
+      }]
+    >,
+    InterfaceMethod<
+      /*desc=*/[{
+        Reify the shape of a dimension of a given result of an operation
+        (typically in terms of the shape of its operands).
+
+        Returns the shape of a specific dimension of a result of the operation as
+        an OpFoldResult. The given builder may be used to insert ops that compute
+        the shapes.
+
+        If the dimension of the result cannot be computed the method must return
+        `failure()`.
+      }],
+      /*retTy=*/"::llvm::FailureOr<::mlir::OpFoldResult>",
+      /*methodName=*/"reifyDimOfResult",
+      /*args=*/(ins "::mlir::OpBuilder &":$builder,
+        "int":$resultIndex, "int":$dim),
+      /*methodBody=*/"",
+      /*defaultImplementation=*/[{
+        auto shapes = cast<ReifyRankedShapedTypeOpInterface>($_op.getOperation()).reifyShapeOfResult(builder, resultIndex);
+        if (failed(shapes))
+          return failure();
+        if (dim < 0 || dim >= (int)((*shapes).size()))
+          return $_op.emitOpError("invalid dimension");
+        return (*shapes)[dim];
+      }]
     >
   ];
 }

mlir/lib/Dialect/Tensor/IR/TensorInferTypeOpInterfaceImpl.cpp

@@ -77,6 +77,9 @@ namespace {
 struct ReifyExpandShapeOp
     : public ReifyRankedShapedTypeOpInterface::ExternalModel<ReifyExpandShapeOp,
                                                              ExpandShapeOp> {
+  using Base =
+      ReifyRankedShapedTypeOpInterface::ExternalModel<ReifyExpandShapeOp,
+                                                      ExpandShapeOp>;
   LogicalResult
   reifyResultShapes(Operation *op, OpBuilder &b,
                     ReifiedRankedShapedTypeDims &reifyResultShapes) const {

mlir/test/lib/Dialect/Test/TestOps.td

@@ -915,7 +915,8 @@ def OpWithResultShapeInterfaceOp : TEST_Op<"op_with_result_shape_interface",
 
 def OpWithResultShapePerDimInterfaceOp :
     TEST_Op<"op_with_result_shape_per_dim_interface",
-        [DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>]> {
+        [DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface, 
+            ["reifyResultShapes"]>]> {
   let arguments = (ins AnyRankedTensor:$operand1, AnyRankedTensor:$operand2);
   let results = (outs AnyRankedTensor:$result1, AnyRankedTensor:$result2);
 }