Revert "[mlir][sparse] introduce sparse_tensor.iterate operation (#88807)"

This reverts commit 8debcf0.

Author: Peiming Liu

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h

@@ -17,13 +17,9 @@
 #include "mlir/IR/OpDefinition.h"
 #include "mlir/IR/OpImplementation.h"
 #include "mlir/IR/TensorEncoding.h"
-#include "mlir/Interfaces/ControlFlowInterfaces.h"
 #include "mlir/Interfaces/InferTypeOpInterface.h"
-#include "mlir/Interfaces/LoopLikeInterface.h"
 #include "mlir/Interfaces/SideEffectInterfaces.h"
 
-#include "llvm/ADT/bit.h"
-
 //===----------------------------------------------------------------------===//
 //
 // Type aliases to help code be more self-documenting. Unfortunately
@@ -45,40 +41,6 @@ using Level = uint64_t;
 /// including the value `ShapedType::kDynamic` (for shapes).
 using Size = int64_t;
 
-/// A simple wrapper to encode a bitset of defined  (at most 64) levels.
-class LevelSet {
-  uint64_t bits = 0;
-
-public:
-  LevelSet() = default;
-  explicit LevelSet(uint64_t bits) : bits(bits) {}
-  operator uint64_t() const { return bits; }
-
-  LevelSet &set(unsigned i) {
-    assert(i < 64);
-    bits |= 1 << i;
-    return *this;
-  }
-
-  LevelSet &operator|=(LevelSet lhs) {
-    bits |= static_cast<uint64_t>(lhs);
-    return *this;
-  }
-
-  LevelSet &lshift(unsigned offset) {
-    bits = bits << offset;
-    return *this;
-  }
-
-  bool operator[](unsigned i) const {
-    assert(i < 64);
-    return (bits & (1 << i)) != 0;
-  }
-
-  unsigned count() const { return llvm::popcount(bits); }
-  bool empty() const { return bits == 0; }
-};
-
 } // namespace sparse_tensor
 } // namespace mlir
 

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td

@@ -19,21 +19,6 @@ class SparseTensor_Attr<string name,
                         list<Trait> traits = []>
     : AttrDef<SparseTensor_Dialect, name, traits>;
 
-//===----------------------------------------------------------------------===//
-// A simple bitset attribute wrapped over a single int64_t to encode a set of
-// sparse tensor levels.
-//===----------------------------------------------------------------------===//
-
-def LevelSetAttr :
-    TypedAttrBase<
-      I64, "IntegerAttr",
-      And<[CPred<"::llvm::isa<::mlir::IntegerAttr>($_self)">,
-           CPred<"::llvm::cast<::mlir::IntegerAttr>($_self).getType().isInteger(64)">]>,
-      "LevelSet attribute"> {
-  let returnType = [{::mlir::sparse_tensor::LevelSet}];
-  let convertFromStorage = [{::mlir::sparse_tensor::LevelSet($_self.getValue().getZExtValue())}];
-}
-
 //===----------------------------------------------------------------------===//
 // These attributes are just like `IndexAttr` except that they clarify whether
 // the index refers to a dimension (an axis of the semantic tensor) or a level

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td

@@ -15,8 +15,6 @@ include "mlir/Dialect/SparseTensor/IR/SparseTensorTypes.td"
 include "mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.td"
 include "mlir/Interfaces/InferTypeOpInterface.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
-include "mlir/Interfaces/ControlFlowInterfaces.td"
-include "mlir/Interfaces/LoopLikeInterface.td"
 
 //===----------------------------------------------------------------------===//
 // Base class.
@@ -1279,7 +1277,7 @@ def SparseTensor_SelectOp : SparseTensor_Op<"select", [Pure, SameOperandsAndResu
 
 def SparseTensor_YieldOp : SparseTensor_Op<"yield", [Pure, Terminator,
     ParentOneOf<["BinaryOp", "UnaryOp", "ReduceOp", "SelectOp",
-                 "ForeachOp", "IterateOp"]>]>,
+                 "ForeachOp"]>]>,
     Arguments<(ins Variadic<AnyType>:$results)> {
   let summary = "Yield from sparse_tensor set-like operations";
   let description = [{
@@ -1432,154 +1430,6 @@ def SparseTensor_ForeachOp : SparseTensor_Op<"foreach",
   let hasVerifier = 1;
 }
 
-//===----------------------------------------------------------------------===//
-// Sparse Tensor Iteration Operations.
-//===----------------------------------------------------------------------===//
-
-def ExtractIterSpaceOp : SparseTensor_Op<"extract_iteration_space",
-    [Pure, DeclareOpInterfaceMethods<InferTypeOpInterface>]> {
-
-  let arguments = (ins AnySparseTensor:$tensor,
-                       Optional<AnySparseIterator>:$parentIter,
-                       LevelAttr:$loLvl, LevelAttr:$hiLvl);
-
-  let results = (outs AnySparseIterSpace:$resultSpace);
-
-  let summary = "Extract an iteration space from a sparse tensor between certain levels";
-  let description = [{
-      Extracts a `!sparse_tensor.iter_space` from a sparse tensor between
-      certian (consecutive) levels.
-
-      `tensor`: the input sparse tensor that defines the iteration space.
-      `parentIter`: the iterator for the previous level, at which the iteration space
-      at the current levels will be extracted.
-      `loLvl`, `hiLvl`: the level range between [loLvl, hiLvl) in the input tensor that
-      the returned iteration space covers. `hiLvl - loLvl` defines the dimension of the
-      iteration space.
-
-      Example:
-      ```mlir
-      // Extracts a 1-D iteration space from a COO tensor at level 1.
-      %space = sparse_tensor.iteration.extract_space %sp at %it1 lvls = 1
-        : tensor<4x8xf32, #COO>, !sparse_tensor.iterator<#COO, lvls = 0>
-      ```
-  }];
-
-
-  let extraClassDeclaration = [{
-    std::pair<Level, Level> getLvlRange() {
-      return std::make_pair(getLoLvl(), getHiLvl());
-    }
-    unsigned getSpaceDim() {
-      return getHiLvl() - getLoLvl();
-    }
-    ArrayRef<::mlir::sparse_tensor::LevelType> getSpaceLvlTypes() {
-      return getResultSpace().getType().getLvlTypes();
-    }
-  }];
-
-  let hasVerifier = 1;
-  let assemblyFormat = "$tensor (`at` $parentIter^)? `lvls` `=` custom<LevelRange>($loLvl, $hiLvl) "
-                       " attr-dict `:` type($tensor) (`,` type($parentIter)^)?";
-}
-
-def IterateOp : SparseTensor_Op<"iterate",
-    [RecursiveMemoryEffects, RecursivelySpeculatable,
-     DeclareOpInterfaceMethods<LoopLikeOpInterface,
-      ["getInitsMutable", "getLoopResults", "getRegionIterArgs",
-       "getYieldedValuesMutable"]>,
-     DeclareOpInterfaceMethods<RegionBranchOpInterface,
-      ["getEntrySuccessorOperands"]>,
-     SingleBlockImplicitTerminator<"sparse_tensor::YieldOp">]> {
-
-  let arguments = (ins AnySparseIterSpace:$iterSpace,
-                       Variadic<AnyType>:$initArgs,
-                       LevelSetAttr:$crdUsedLvls);
-  let results = (outs Variadic<AnyType>:$results);
-  let regions = (region SizedRegion<1>:$region);
-
-  let summary = "Iterate over a sparse iteration space";
-  let description = [{
-      The `sparse_tensor.iterate` operations represents a loop over the
-      provided iteration space extracted from a specific sparse tensor.
-      The operation defines an SSA value for a sparse iterator that points
-      to the current stored element in the sparse tensor and SSA values
-      for coordinates of the stored element. The coordinates are always
-      converted to `index` type despite of the underlying sparse tensor
-      storage. When coordinates are not used, the SSA values can be skipped
-      by `_` symbols, which usually leads to simpler generated code after
-      sparsification. For example:
-
-      ```mlir
-      // The coordinate for level 0 is not used when iterating over a 2-D
-      // iteration space.
-      %sparse_tensor.iterate %iterator in %space at(_, %crd_1)
-        : !sparse_tensor.iter_space<#CSR, lvls = 0 to 2>
-      ```
-
-      `sparse_tensor.iterate` can also operate on loop-carried variables
-      and returns the final values after loop termination.
-      The initial values of the variables are passed as additional SSA operands
-      to the iterator SSA value and used coordinate SSA values mentioned
-      above. The operation region has an argument for the iterator, variadic
-      arguments for specified (used) coordiates and followed by one argument
-      for each loop-carried variable, representing the value of the variable
-      at the current iteration.
-      The body region must contain exactly one block that terminates with
-      `sparse_tensor.yield`.
-
-      `sparse_tensor.iterate` results hold the final values after the last
-      iteration. If the `sparse_tensor.iterate` defines any values, a yield
-      must be explicitly present.
-      The number and types of the `sparse_tensor.iterate` results must match
-      the initial values in the iter_args binding and the yield operands.
-
-
-      A nested `sparse_tensor.iterate` example that prints all the coordinates
-      stored in the sparse input:
-
-      ```mlir
-      func.func @nested_iterate(%sp : tensor<4x8xf32, #COO>) {
-        // Iterates over the first level of %sp
-        %l1 = sparse_tensor.extract_iteration_space %sp lvls = 0 : tensor<4x8xf32, #COO>
-        %r1 = sparse_tensor.iterate %it1 in %l1 at (%crd0)
-            : !sparse_tensor.iter_space<#COO, lvls = 0 to 1>  {
-          // Iterates over the second level of %sp
-          %l2 = sparse_tensor.extract_iteration_space %sp at %it1 lvls = 1
-              : tensor<4x8xf32, #COO>, !sparse_tensor.iterator<#COO, lvls = 0 to 1>
-          %r2 = sparse_tensor.iterate %it2 in %l2 at (crd1)
-              : !sparse_tensor.iter_space<#COO, lvls = 1 to 2>  {
-             vector.print %crd0 : index
-             vector.print %crd1 : index
-          }
-        }
-      }
-
-      ```
-  }];
-
-  let extraClassDeclaration = [{
-    unsigned getSpaceDim() {
-      return getIterSpace().getType().getSpaceDim();
-    }
-    BlockArgument getIterator() {
-      return getRegion().getArguments().front();
-    }
-    Block::BlockArgListType getCrds() {
-      // The first block argument is iterator, the remaining arguments are
-      // referenced coordinates.
-      return getRegion().getArguments().slice(1, getCrdUsedLvls().count());
-    }
-    unsigned getNumRegionIterArgs() {
-      return getRegion().getArguments().size() - 1 - getCrdUsedLvls().count();
-    }
-  }];
-
-  let hasVerifier = 1;
-  let hasRegionVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 //===----------------------------------------------------------------------===//
 // Sparse Tensor Debugging and Test-Only Operations.
 //===----------------------------------------------------------------------===//

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorTypes.td

@@ -72,99 +72,4 @@ def SparseTensorStorageSpecifier
     : Type<CPred<"::llvm::isa<::mlir::sparse_tensor::StorageSpecifierType>($_self)">, "metadata",
           "::mlir::sparse_tensor::StorageSpecifierType">;
 
-//===----------------------------------------------------------------------===//
-// Sparse Tensor Iteration Types.
-//===----------------------------------------------------------------------===//
-
-def SparseTensor_IterSpace : SparseTensor_Type<"IterSpace"> {
-  let mnemonic = "iter_space";
-
-  let description = [{
-    A sparse iteration space that represents an abstract N-D (sparse) iteration space
-    extracted from a sparse tensor.
-
-    Examples:
-
-    ```mlir
-    // An iteration space extracted from a CSR tensor between levels [0, 2).
-    !iter_space<#CSR, lvls = 0 to 2>
-    ```
-  }];
-
-  let parameters = (ins
-     SparseTensorEncodingAttr : $encoding,
-     "Level" : $loLvl,
-     "Level" : $hiLvl
-  );
-
-  let extraClassDeclaration = [{
-     /// The the dimension of the iteration space.
-     unsigned getSpaceDim() const {
-       return getHiLvl() - getLoLvl();
-     }
-
-     /// Get the level types for the iteration space.
-     ArrayRef<LevelType> getLvlTypes() const {
-       return getEncoding().getLvlTypes().slice(getLoLvl(), getSpaceDim());
-     }
-
-     /// Whether the iteration space is unique (i.e., no duplicated coordinate).
-     bool isUnique() {
-       return !getLvlTypes().back().isa<LevelPropNonDefault::Nonunique>();
-     }
-
-     /// Get the corresponding iterator type.
-     ::mlir::sparse_tensor::IteratorType getIteratorType() const;
-  }];
-
-  let assemblyFormat="`<` $encoding `,` `lvls` `=` custom<LevelRange>($loLvl, $hiLvl) `>`";
-}
-
-def SparseTensor_Iterator : SparseTensor_Type<"Iterator"> {
-  let mnemonic = "iterator";
-
-  let description = [{
-    An iterator that points to the current element in the corresponding iteration space.
-
-    Examples:
-
-    ```mlir
-    // An iterator that iterates over a iteration space of type `!iter_space<#CSR, lvls = 0 to 2>`
-    !iterator<#CSR, lvls = 0 to 2>
-    ```
-  }];
-
-  let parameters = (ins
-     SparseTensorEncodingAttr : $encoding,
-     "Level" : $loLvl,
-     "Level" : $hiLvl
-  );
-
-  let extraClassDeclaration = [{
-     /// Get the corresponding iteration space type.
-     ::mlir::sparse_tensor::IterSpaceType getIterSpaceType() const;
-
-     unsigned getSpaceDim() const { return getIterSpaceType().getSpaceDim(); }
-     ArrayRef<LevelType> getLvlTypes() const { return getIterSpaceType().getLvlTypes(); }
-     bool isUnique() { return getIterSpaceType().isUnique(); }
-  }];
-
-  let assemblyFormat="`<` $encoding `,` `lvls` `=` custom<LevelRange>($loLvl, $hiLvl) `>`";
-}
-
-def IsSparseSparseIterSpaceTypePred
-    : CPred<"::llvm::isa<::mlir::sparse_tensor::IterSpaceType>($_self)">;
-
-def IsSparseSparseIteratorTypePred
-    : CPred<"::llvm::isa<::mlir::sparse_tensor::IteratorType>($_self)">;
-
-def AnySparseIterSpace
-    : Type<IsSparseSparseIterSpaceTypePred, "sparse iteration space",
-          "::mlir::sparse_tensor::IterSpaceType">;
-
-def AnySparseIterator
-    : Type<IsSparseSparseIteratorTypePred, "sparse iterator",
-          "::mlir::sparse_tensor::IteratorType">;
-
-
 #endif // SPARSETENSOR_TYPES