[mlir][Linalg] Drop symbol_source abstraction which does not pay for …

…itself.

Differential Revision: https://reviews.llvm.org/D91956

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

@@ -503,28 +503,21 @@ class GenericOpBase<string mnemonic> : LinalgStructuredBase_Op<mnemonic, [
                        OptionalAttr<StrAttr>:$doc,
                        OptionalAttr<StrAttr>:$library_call,
                        // ArrayAttr of StrArrayAttr:
-                       OptionalAttr<ArrayAttr>:$sparse,
-                       Confined<OptionalAttr<I64Attr>, [IntMinValue<0>]>
-                         :$symbol_source);
+                       OptionalAttr<ArrayAttr>:$sparse);
   let results = (outs Variadic<AnyRankedTensor>:$result_tensors);
   let regions = (region AnyRegion:$region);
   let extraClassDeclaration = [{
     SmallVector<StringRef, 8> linalgTraitAttrNames() {
       return SmallVector<StringRef, 8>{
         getDocAttrName(),
         getIndexingMapsAttrName(), getLibraryCallAttrName(),
-        getIteratorTypesAttrName(), getSymbolSourceAttrName()
+        getIteratorTypesAttrName(),
       };
     }
     std::string getLibraryCallName() {
       return library_call().hasValue() ?
         library_call()->str() : "op_has_no_registered_library_name";
     }
-    llvm::Optional<unsigned> getSymbolSource() {
-      auto ss = symbol_source();
-      return ss.hasValue() ?
-        llvm::Optional<unsigned>(ss.getValue()) : llvm::None;
-    }
 
     static std::function<void(Block &)> getRegionBuilder() {
       return nullptr;
@@ -566,10 +559,6 @@ def GenericOp : GenericOpBase<"generic"> {
           parallel, reduction, window
       - sparse: an optional list with per-dimension sparsity annotations (either
         "D" for dense or "S" for sparse) for each input and output view.
-      - symbol_source: index of the operand whose dimensions will be propagated
-        as symbols to the indexing maps. When specified the number of symbols
-        in each of the indexing maps has to be either 0 or the rank of the
-        specified operand.
 
     Example:
     Defining a #matmul_trait attribute in MLIR can be done as follows:
@@ -646,50 +635,17 @@ def GenericOp : GenericOpBase<"generic"> {
     Tensor values must be legalized by a buffer allocation pass before most
     transformations can be applied. Such legalizations move tensor return values
     into output buffer operands and updates the region arguments accordingly.
-
-    The `symbol_source` attribute allows selecting a particular operand and
-    introducing symbols for each operand dimension. Such symbols can then be
-    used in the indexing maps.
-
-    Example of 1D convolution with symbols:
-    ```mlir
-    #conv_1d_accesses = [
-      affine_map<(m, n)[dimN] -> (m + n - dimN floordiv 2)>, // in
-      affine_map<(m, n)[dimN] -> (n)>, // filter
-      affine_map<(m, n)[dimN] -> (m)> // out
-    ]
-
-    #conv_1d_trait = {
-      doc = "O(m) += I(m + n - size(n) floordiv 2) * K(n)",
-      indexing_maps = #conv_1d_accesses,
-      library_call  = "linalg_conv_1d",
-      iterator_types = ["parallel", "parallel"],
-      symbol_source = 1
-    }
-
-    linalg.generic #conv_1d_trait
-      ins(%in, %filter : memref<?xf32>, memref<?xf32>)
-      outs(%out : memref<?xf32>) {
-      ^bb0(%a: f32, %b: f32, %c: f32) :
-        %d = mulf %a, %b : f32
-        %e = addf %c, %d : f32
-        linalg.yield %e : f32
-    }
-    ```
-    where symbol s0 will be substituted with `dim %filter, %c0` i.e. the first
-    and only dimension of the second operand as specified by the symbol_source
-    attribute.
   }];
 
   let builders = [
     OpBuilderDAG<(ins "TypeRange":$resultTensorTypes, "ValueRange":$inputs,
       "ValueRange":$outputBuffers, "ValueRange":$initTensors,
       "ArrayRef<AffineMap>":$indexingMaps, "ArrayRef<StringRef>":$iteratorTypes,
-      "StringRef":$doc, "StringRef":$libraryCall, "IntegerAttr":$symbolSource,
+      "StringRef":$doc, "StringRef":$libraryCall,
       CArg<"function_ref<void(OpBuilder &, Location, ValueRange)>", "nullptr">)>,
     OpBuilderDAG<(ins "ValueRange":$inputs, "ValueRange":$outputBuffers,
       "ArrayRef<AffineMap>":$indexingMaps, "ArrayRef<StringRef>":$iteratorTypes,
-      "StringRef":$doc, "StringRef":$libraryCall, "IntegerAttr":$symbolSource,
+      "StringRef":$doc, "StringRef":$libraryCall,
       CArg<"function_ref<void(OpBuilder &, Location, ValueRange)>", "nullptr">)>,
     OpBuilderDAG<(ins "TypeRange":$resultTensorTypes, "ValueRange":$inputs,
       "ValueRange":$outputBuffers, "ValueRange":$initTensors,
@@ -819,51 +775,18 @@ def IndexedGenericOp : GenericOpBase<"indexed_generic"> {
     Tensor values must be legalized by a buffer allocation pass before most
     transformations can be applied. Such legalizations move tensor return values
     into output buffer operands and update the region arguments accordingly.
-
-    The `symbol_source` attribute allows selecting a particular operand and
-    introducing symbols for each operand dimension. Such symbols can then be
-    used in the indexing maps.
-
-    Example of 1D convolution with symbols:
-    ```mlir
-    #conv_1d_accesses = [
-      affine_map<(m, n)[dimN] -> (m + n - dimN floordiv 2)>, // in
-      affine_map<(m, n)[dimN] -> (n)>, // filter
-      affine_map<(m, n)[dimN] -> (m)> // out
-    ]
-
-    #conv_1d_trait = {
-      doc = "O(m) += I(m + n - size(n) floordiv 2) * K(n)",
-      indexing_maps = #conv_1d_accesses,
-      library_call  = "linalg_conv_1d",
-      iterator_types = ["parallel", "parallel"],
-      symbol_source = 1
-    }
-
-    linalg.generic #conv_1d_trait
-      ins(%in, %filter : memref<?xf32>, memref<?xf32>)
-      outs(%out : memref<?xf32>) {
-      ^bb0(%a: f32, %b: f32, %c: f32) :
-        %d = mulf %a, %b : f32
-        %e = addf %c, %d : f32
-        linalg.yield %e : f32
-    }
-    ```
-    where symbol s0 will be substituted with `dim %filter, %c0` i.e. the first
-    and only dimension of the second operand as specified by the symbol_source
-    attribute.
   }];
 
   let builders = [
     OpBuilderDAG<(ins "TypeRange":$resultTensorTypes, "ValueRange":$inputs,
       "ValueRange":$outputBuffers, "ValueRange":$initTensors,
       "ArrayRef<AffineMap>":$indexingMaps, "ArrayRef<StringRef>":$iteratorTypes,
-      "StringRef":$doc, "StringRef":$libraryCall, "IntegerAttr":$symbolSource,
+      "StringRef":$doc, "StringRef":$libraryCall,
       CArg<"function_ref<void(OpBuilder &, Location, ValueRange, ValueRange)>",
            "nullptr">)>,
     OpBuilderDAG<(ins "ValueRange":$inputs, "ValueRange":$outputBuffers,
       "ArrayRef<AffineMap>":$indexingMaps, "ArrayRef<StringRef>":$iteratorTypes,
-      "StringRef":$doc, "StringRef":$libraryCall, "IntegerAttr":$symbolSource,
+      "StringRef":$doc, "StringRef":$libraryCall,
       CArg<"function_ref<void(OpBuilder &, Location, ValueRange, ValueRange)>",
            "nullptr">)>,
     OpBuilderDAG<(ins "TypeRange":$resultTensorTypes, "ValueRange":$inputs,

mlir/include/mlir/Dialect/Linalg/Passes.td

@@ -64,7 +64,7 @@ def LinalgLowerToLoops : FunctionPass<"convert-linalg-to-loops"> {
 def LinalgBufferize : Pass<"linalg-bufferize", "FuncOp"> {
   let summary = "Bufferize the linalg dialect";
   let constructor = "mlir::createLinalgBufferizePass()";
-  let dependentDialects = ["linalg::LinalgDialect"];
+  let dependentDialects = ["linalg::LinalgDialect", "AffineDialect"];
 }
 
 def LinalgLowerToParallelLoops

mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h

@@ -46,10 +46,6 @@ inline bool isColumnMajorMatmul(ArrayAttr indexingMaps) {
   return indexingMaps == maps;
 }
 
-/// Attribute name for the IntegerAttr which encodes the index of operand
-/// whose dimensions will be propagated as symbols to the indexing maps
-constexpr StringRef getSymbolSourceAttrName() { return "symbol_source"; }
-
 /// Attribute name for the AffineArrayAttr which encodes the relationship
 /// between a structured op iterators' and its operands.
 constexpr StringRef getIndexingMapsAttrName() { return "indexing_maps"; }

mlir/lib/Dialect/Linalg/EDSC/Builders.cpp

@@ -69,8 +69,7 @@ Operation *mlir::edsc::makeGenericLinalgOp(
               builder.getStrArrayAttr(iteratorStrTypes),
               StringAttr() /*doc*/,
               StringAttr() /*library_call*/,
-              ArrayAttr() /*sparse*/,
-              IntegerAttr() /*symbol_source*/
+              ArrayAttr() /*sparse*/
               /* TODO: other attributes in op */
               )
           .getOperation();