[mlir][sparse] remove dead code from utils (#68943)

Author: aartbik

mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.cpp

@@ -23,54 +23,6 @@
 using namespace mlir;
 using namespace mlir::sparse_tensor;
 
-/// If the tensor is a sparse constant, generates and returns the pair of
-/// the constants for the coordinates and the values.
-static std::optional<std::pair<Value, Value>>
-genSplitSparseConstant(OpBuilder &builder, Location loc, Value tensor) {
-  if (auto constOp = tensor.getDefiningOp<arith::ConstantOp>()) {
-    if (auto a = dyn_cast<SparseElementsAttr>(constOp.getValue())) {
-      auto coordinates = builder.create<arith::ConstantOp>(loc, a.getIndices());
-      auto values = builder.create<arith::ConstantOp>(loc, a.getValues());
-      return std::make_pair(coordinates, values);
-    }
-  }
-  return {};
-}
-
-/// Reads `coordinates[k][0..rank-1]` and `value[k]`, appending the
-/// former onto `cvs` and returning the latter.
-// FIXME: Change the `rank` argument to `Dimension dimRank` or `Level lvlRank`,
-// to clarify its intended meaning.
-static Value genCoordsAndValueForSparse(OpBuilder &builder, Location loc,
-                                        Value coordinates, Value values,
-                                        SmallVectorImpl<Value> &cvs, Value k,
-                                        unsigned rank) {
-  for (unsigned d = 0; d < rank; d++) {
-    Value dim = constantIndex(builder, loc, d);
-    Value crd =
-        builder.create<tensor::ExtractOp>(loc, coordinates, ValueRange{k, dim});
-    crd = builder.create<arith::IndexCastOp>(loc, builder.getIndexType(), crd);
-    // builder.create<memref::StoreOp>(loc, crd, cvs, dim);
-    cvs.push_back(crd);
-  }
-  return builder.create<tensor::ExtractOp>(loc, values, k);
-}
-
-/// Generates code to read the value from `tensor[ivs]`, and open
-/// a conditional for whether the value is non-zero.  The generated code
-/// looks like the following and the insertion point after this routine
-/// is inside the then-branch.
-///    if (tensor[ivs] != 0)
-///      insert_point
-static Value genCoordsAndValueForDense(OpBuilder &builder, Location loc,
-                                       Value tensor,
-                                       SmallVectorImpl<Value> &cvs,
-                                       ValueRange ivs) {
-  Value val = genValueForDense(builder, loc, tensor, ivs);
-  cvs.append(ivs.begin(), ivs.end());
-  return val;
-}
-
 //===----------------------------------------------------------------------===//
 // ExecutionEngine/SparseTensorUtils helper functions.
 //===----------------------------------------------------------------------===//
@@ -450,65 +402,6 @@ void mlir::sparse_tensor::deallocDenseTensor(OpBuilder &builder, Location loc,
   builder.create<memref::DeallocOp>(loc, buffer);
 }
 
-Value mlir::sparse_tensor::genValueForDense(OpBuilder &builder, Location loc,
-                                            Value tensor, ValueRange ivs) {
-  Value val = builder.create<tensor::ExtractOp>(loc, tensor, ivs);
-  Value cond = genIsNonzero(builder, loc, val);
-  scf::IfOp ifOp = builder.create<scf::IfOp>(loc, cond, /*else*/ false);
-  builder.setInsertionPointToStart(&ifOp.getThenRegion().front());
-  return val;
-}
-
-// FIXME:
-// 1. Dense tensors loop should be generated by loop emitter.
-// 2. Support reduction variables to propagate SSA chains properly.
-// 3. Change the `rank` argument to `Dimension dimRank` or `Level lvlRank`,
-//    to clarify its meaning.
-void mlir::sparse_tensor::genDenseTensorOrSparseConstantIterLoop(
-    OpBuilder &builder, Location loc, Value src, unsigned rank,
-    function_ref<void(OpBuilder &, Location, Value, ValueRange)> bodyBuilder) {
-  // `cvs` is actually the flattened coordinates array for all elements,
-  // not just for one element (since we do not `SmallVector::clear` after
-  // each iteration of the body of the loopnest.
-  SmallVector<Value> cvs;
-  SmallVector<Value> lo;
-  SmallVector<Value> hi;
-  SmallVector<Value> st;
-  const Value zero = constantIndex(builder, loc, 0);
-  const Value one = constantIndex(builder, loc, 1);
-  const auto splitSrc = genSplitSparseConstant(builder, loc, src);
-  if (splitSrc.has_value()) {
-    const Value srcCoordinates = splitSrc->first;
-    const Value srcValues = splitSrc->second;
-    lo.push_back(zero);
-    hi.push_back(linalg::createOrFoldDimOp(builder, loc, srcValues, 0));
-    st.push_back(one);
-    scf::buildLoopNest(builder, loc, lo, hi, st, {},
-                       [&](OpBuilder &builder, Location loc, ValueRange ivs,
-                           ValueRange /*args*/) -> scf::ValueVector {
-                         Value val = genCoordsAndValueForSparse(
-                             builder, loc, srcCoordinates, srcValues, cvs,
-                             ivs[0], rank);
-                         bodyBuilder(builder, loc, val, cvs);
-                         return {};
-                       });
-  } else {
-    for (unsigned i = 0; i < rank; i++) {
-      lo.push_back(zero);
-      hi.push_back(linalg::createOrFoldDimOp(builder, loc, src, i));
-      st.push_back(one);
-    }
-    scf::buildLoopNest(builder, loc, lo, hi, st, {},
-                       [&](OpBuilder &builder, Location loc, ValueRange ivs,
-                           ValueRange /*args*/) -> scf::ValueVector {
-                         Value val = genCoordsAndValueForDense(builder, loc,
-                                                               src, cvs, ivs);
-                         bodyBuilder(builder, loc, val, cvs);
-                         return {};
-                       });
-  }
-}
-
 void mlir::sparse_tensor::sizesFromSrc(OpBuilder &builder,
                                        SmallVectorImpl<Value> &sizes,
                                        Location loc, Value src) {

mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.h

@@ -221,34 +221,6 @@ Value allocDenseTensor(OpBuilder &builder, Location loc,
 /// Generates code to deallocate a dense buffer.
 void deallocDenseTensor(OpBuilder &builder, Location loc, Value buffer);
 
-/// Generates code to read the value from `tensor[ivs]`. The generated code
-/// looks like the following and the insertion point after this routine is
-/// inside the then-branch.
-///    if (tensor[ivs] != 0)
-///      insert_point
-Value genValueForDense(OpBuilder &builder, Location loc, Value tensor,
-                       ValueRange ivs);
-
-/// Generates the loop structure to iterate over a dense tensor or a sparse
-/// tensor constant to support the lowering of dense-to-sparse convert operator.
-//
-// The loop to iterate a dense tensor:
-//   for i1 in dim1
-//    ..
-//     for ik in dimk
-//       val = a[i1,..,ik]
-//       if val != 0
-//         loop-body
-//
-// The loop to iterate a sparse tensor constant:
-//   for i in range(NNZ)
-//     val = values[i]
-//     [i1,..,ik] = coordinates[i]
-//     loop-body
-void genDenseTensorOrSparseConstantIterLoop(
-    OpBuilder &builder, Location loc, Value src, unsigned rank,
-    function_ref<void(OpBuilder &, Location, Value, ValueRange)> bodyBuilder);
-
 /// Populates given sizes array from dense tensor or sparse tensor constant.
 void sizesFromSrc(OpBuilder &builder, SmallVectorImpl<Value> &sizes,
                   Location loc, Value src);

mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp

@@ -241,16 +241,6 @@ class NewCallParams final {
     return true;
   }
 
-  /// Gets the dimension-to-level mapping.
-  //
-  // TODO: This is only ever used for passing into `genAddEltCall`;
-  // is there a better way to encapsulate that pattern (both to avoid
-  // this one-off getter, and to avoid potential mixups)?
-  Value getDimToLvl() const {
-    assert(isInitialized() && "Must initialize before getDimToLvl");
-    return params[kParamDim2Lvl];
-  }
-
   /// Generates a function call, with the current static parameters
   /// and the given dynamic arguments.
   Value genNewCall(Action action, Value ptr = Value()) {