return op->getResult(0).getType().cast<TensorType>().clone(
      new_result_quantized_type);
}

// Matches kernel dimension numbers, ranks of input and output and constant
// kernel for legalization to TFLite convolution ops.
LogicalResult MatchConvolutionFormat(stablehlo::ConvolutionOp op) {
  stablehlo::ConvDimensionNumbersAttr dimension_numbers =
      op.getDimensionNumbers();

#define GEN_PASS_DEF_LEGALIZEHLOTOTFPASS
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h.inc"

class LegalizeHloToTf : public impl::LegalizeHloToTfPassBase<LegalizeHloToTf> {
  /// Performs the legalization to the TF dialect.
  void runOnOperation() override;
};

using mhlo::DotDimensionNumbersAttr;

// Replaces `region`'s terminator to TF::Yield.
void ReplaceReturnOp(Region& region, PatternRewriter& rewriter) {

      first = false;
      os << result_type;
    }
  }
  os << ")";
  // Print out attributes except for large elementsattributes (which should
  // rarely be the cause why the legalization didn't happen).
  if (!inst->getAttrDictionary().empty()) {
    os << " : {";
    bool first = true;
    for (auto& named_attr : inst->getAttrDictionary()) {
      os << (!first ? ", " : "");
      first = false;

  let hasFolder = 1;
}

// If there is a change in supporting more types in the TFLite cast op kernel,
// the While loop outline pass should be updated since it inserts cast op(s)
// after the TF -> TFL legalization pass is done.
// LINT.IfChange
def TFL_CastOp : TFL_Op<"cast", [
    Pure,
    SameOperandsAndResultShape]> {
  let summary = "Cast operator";

  let description = [{

  func.return %0 : tensor<16xf32>
}

// -----

// Test tf.Min with complex numbers.
// Previous versions of tensorflow said complex numbers were allowed with
// tf.Min even though it doesn't make sense. The legalization of tf to xla
// requires that complex types are not allowed in tf.Min, so we have an
// explicit unit here to make sure that invariant is enforced.