huge refactor for high RewritePatterns usage and less ad-hoc cpp code

remove Spatial many ops in favor of tensor ops like in pim

src/PIM/Conversion/ONNXToSpatial/Common/ShapeTilingUtils.hpp

@@ -5,15 +5,15 @@
 #include "mlir/IR/Value.h"
 #include "mlir/Transforms/DialectConversion.h"
 
+#include "llvm/ADT/ArrayRef.h"
+#include "llvm/ADT/DenseMap.h"
+#include "llvm/ADT/SmallVector.h"
+
 #include <cassert>
 #include <cstddef>
 #include <type_traits>
 #include <utility>
 
-#include "llvm/ADT/DenseMap.h"
-#include "llvm/ADT/ArrayRef.h"
-#include "llvm/ADT/SmallVector.h"
-
 namespace onnx_mlir {
 
 template <class ShapedType>
@@ -105,7 +105,8 @@ inline auto getTensorShape(mlir::Value tensor) {
 inline bool haveSameStaticShape(mlir::Value lhs, mlir::Value rhs) {
   auto lhsType = mlir::dyn_cast<mlir::RankedTensorType>(lhs.getType());
   auto rhsType = mlir::dyn_cast<mlir::RankedTensorType>(rhs.getType());
-  return lhsType && rhsType && lhsType.hasStaticShape() && rhsType.hasStaticShape() && lhsType.getShape() == rhsType.getShape();
+  return lhsType && rhsType && lhsType.hasStaticShape() && rhsType.hasStaticShape()
+      && lhsType.getShape() == rhsType.getShape();
 }
 
 /// Slices a statically shaped tensor along one axis into contiguous pieces of