[mlir][sparse] add source materizalization callback for sparse tensor codegen type converter.

[Peiming]

Summary

Required by scf.for to achieve 1:N type conversion (See D136314).

[aartbik]

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

169 ↗

(On Diff #469276)

This looks okay, but shall we do this in the constructor in the SparseTensorCodegen.cpp file?
Just so that all logic is in one place?

mlir::SparseTensorTypeToBufferConverter::SparseTensorTypeToBufferConverter() {

addConversion([](Type type) { return type; });
addConversion(convertSparseTensorType);

}

[Peiming]

address comments from Aart.

[aartbik]

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

754

Last nit: Not a sparse tensor.
;=)

(capital N)

757

Ah, this is a nice side-effect of moving it ;)
genTuple reuse

[Peiming]

fix comment.

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

 
 //===----------------------------------------------------------------------===//
 // Sparse tensor type conversion into an actual buffer.
 //===----------------------------------------------------------------------===//
 
 mlir::SparseTensorTypeToBufferConverter::SparseTensorTypeToBufferConverter() {
   addConversion([](Type type) { return type; });
   addConversion(convertSparseTensorType);
+
+  // Required by scf.for 1:N type conversion.
+  addSourceMaterialization([](OpBuilder &builder, RankedTensorType tp,
+                              ValueRange inputs,
+                              Location loc) -> Optional<Value> {
+    if (!getSparseTensorEncoding(tp))
+      // Not a sparse tensor.
+      return llvm::None;
+    // Sparse compiler knows how to cancel out these casts.
+    return genTuple(builder, loc, tp, inputs);
+  });
 }
 
 //===----------------------------------------------------------------------===//
 // Public method for populating conversion rules.
 //===----------------------------------------------------------------------===//
 
 /// Populates the given patterns list with conversion rules required for
 /// the sparsification of linear algebra operations.