[Mlir-commits] [mlir] [mlir][sparse] introduce `sparse_tensor.iterate` operation (PR #88955)

Aart Bik llvmlistbot at llvm.org
Wed Apr 24 11:11:39 PDT 2024


================
@@ -1513,6 +1515,103 @@ def ExtractIterSpaceOp : SparseTensor_Op<"extract_iteration_space",
   let hasVerifier = 1;
 }
 
+def IterateOp : SparseTensor_Op<"iterate",
+    [RecursiveMemoryEffects, RecursivelySpeculatable,
+     DeclareOpInterfaceMethods<LoopLikeOpInterface,
+      ["getInitsMutable", "getLoopResults", "getRegionIterArgs",
+       "getYieldedValuesMutable"]>,
+     DeclareOpInterfaceMethods<RegionBranchOpInterface,
+      ["getEntrySuccessorOperands"]>,
+     SingleBlockImplicitTerminator<"sparse_tensor::YieldOp">]> {
+
+  let summary = "Iterate over a sparse iteration space";
+  let description = [{
+      The `sparse_tensor.iterate` operation represents a loop (nest) 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.
----------------
aartbik wrote:

due to the "can also operate", the returns reads wrong.

Perhaps say

`sparse_tensor.iterate` can also operate on loop-carried variables by returning the final values after loop termination.

(assuming I get this right)



https://github.com/llvm/llvm-project/pull/88955


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