allTypesQuantizedOrInt &=
          (mlir::isa<quant::QuantizedType>(type.getElementType()) ||
           mlir::isa<IntegerType>(type.getElementType()));
    }

    for (auto result : op->getResults()) {
      ShapedType type = mlir::cast<ShapedType>(result.getType());
      allTypesFp &= !mlir::isa<quant::QuantizedType>(type.getElementType());
      allTypesQuantizedOrInt &=

namespace mlir {
namespace TFL {

FloatAttr ExtractSingleElementAsFloat(ElementsAttr attr) {
  if (attr.getShapedType().getNumElements() != 1 ||
      !mlir::isa<FloatType>(attr.getShapedType().getElementType())) {
    return {};
  }
  return attr.getSplatValue<FloatAttr>();
}

FloatAttr GetSingleElementAsFloatOrSelf(Attribute attr) {
  if (auto m = mlir::dyn_cast_or_null<ElementsAttr>(attr)) {

      return quantizedType.isCompatibleExpressedType(expressed);

    if (auto tensorType = mlir::dyn_cast<TensorType>(expressed))
      return spec == tensorType.getElementType();

    if (auto vectorType = mlir::dyn_cast<VectorType>(expressed))
      return spec == vectorType.getElementType();
  }
  return false;
}

LogicalResult QuantizeRegionOp::verify() {
  // There are specifications for both inputs and outputs.

      return quantizedType.isCompatibleExpressedType(expressed);

    if (auto tensorType = mlir::dyn_cast<TensorType>(expressed))
      return spec == tensorType.getElementType();

    if (auto vectorType = mlir::dyn_cast<VectorType>(expressed))
      return spec == vectorType.getElementType();
  }
  return false;
}

LogicalResult QuantizeRegionOp::verify() {
  // There are specifications for both inputs and outputs.

#include "tsl/platform/statusor.h"

namespace mlir {
namespace TFL {

absl::StatusOr<TypedAttr> CreateTypedAttr(ShapedType shaped_type, int value) {
  Type element_type = shaped_type.getElementType();
  if (element_type.isF16()) {
    auto floatType = mlir::FloatType::getF16(element_type.getContext());
    auto floatAttr = mlir::FloatAttr::get(floatType, static_cast<float>(value));

    auto const_type = mlir::dyn_cast<ShapedType>(op.getOperand(0).getType());
    auto result_type = mlir::dyn_cast<ShapedType>(op.getResult().getType());
    if (!const_type || !const_type.getElementType().isSignlessInteger(4) ||
        !result_type || !result_type.getElementType().isSignlessInteger(8)) {
      return failure();
    }

    auto input_op =
        dyn_cast<arith::ConstantOp>(op.getOperand(0).getDefiningOp());
    if (!input_op) {

      // Ignore types with undefined bit widths.
      if (!tensor_type.getElementType().isIntOrFloat()) continue;
      if (!tensor_type.hasStaticShape()) {
        has_unknown_shape = true;
        return size;
      }
      size += tensor_type.getNumElements() *
              tensor_type.getElementType().getIntOrFloatBitWidth();
    }
    return size;
  };

  if (!tensorType) return false;
  return tensorType.getElementType().isF32();
}

// Returns true iff the given value is a bf16 tensor.
inline bool TFTypeIsBFloat16Tensor(Value value) {
  auto tensorType = mlir::dyn_cast<TensorType>(value.getType());
  if (!tensorType) return false;
  return tensorType.getElementType().isBF16();
}

// Returns true iff the given value is a f16 tensor.

    IntegerAttr attr = IntegerAttr::get(int_ty, raw_value);
    return DenseElementsAttr::get(scalar_ty, attr);
  } else if (auto complex_ty = mlir::dyn_cast<ComplexType>(ty)) {
    Type complex_element_ty = complex_ty.getElementType();
    if (complex_element_ty.isF32()) {
      return DenseElementsAttr::get(
          scalar_ty, static_cast<std::complex<float>>(raw_value));
    } else if (complex_element_ty.isF64()) {

    return tflite::TensorType_STRING;
  } else if (auto complex_type = mlir::dyn_cast<mlir::ComplexType>(type)) {
    if (complex_type.getElementType().isF32()) {
      return tflite::TensorType_COMPLEX64;
    } else if (complex_type.getElementType().isF64()) {
      return tflite::TensorType_COMPLEX128;
    }
    llvm_unreachable("invalid complex Type in conversion");