const ::tflite::Model* input_model = ::tflite::GetModel(buffer);

  ::tflite::optimize::BufferType quantized_type;
  switch (quant_specs.inference_type) {
    case DT_QINT8:
      quantized_type = ::tflite::optimize::BufferType::QUANTIZED_INT8;
      break;
    case DT_HALF:
      quantized_type = ::tflite::optimize::BufferType::QUANTIZED_FLOAT16;
      break;
    default:

      return;
    }

    TensorType old_result_type =
        mlir::dyn_cast<TensorType>(op.getResult().getType());
    const FloatType quantized_type = FloatType::getF16(op.getContext());
    const ShapedType new_result_type = old_result_type.clone(quantized_type);

    // Insert ConvertOp if it does not exist yet. Otherwise, just rewire without
    // creating a ConvertOp.

      return;
    }

    // Get types
    TensorType old_result_type =
        mlir::dyn_cast<TensorType>(op.getResult().getType());
    FloatType quantized_type = FloatType::getF16(op.getContext());
    ShapedType new_result_type = old_result_type.clone(quantized_type);

    // Insert CastOp if it does not exist yet. Otherwise, just rewire without
    // creating a CastOp.
    for (auto& connected_op : op.getResult().getUses()) {

         !quantized_type.isSigned();
}

// Return true when the given element_type is QI16.
bool IsQI16Type(Type element_type) {
  auto quantized_type = element_type.dyn_cast<QuantizedType>();
  return quantized_type != nullptr &&
         quantized_type.getStorageTypeIntegralWidth() == 16 &&
         quantized_type.isSigned();
}

// operand's tensor types.
def QI4 : QuantizedType<"Uniform", [4], 1>;
def QUI8 : QuantizedType<"Uniform", [8], 0>;
def QI8 : QuantizedType<"Uniform", [8], 1>;
def QUI16 : QuantizedType<"Uniform", [16], 0>;
def QI16 : QuantizedType<"Uniform", [16], 1>;
def QUI32 : QuantizedType<"Uniform", [32], 0>;
def QI32 : QuantizedType<"Uniform", [32], 1>;

//===----------------------------------------------------------------------===//

    auto arg = bb.getArgument(0);

    auto remove_quantize_op = [&](QuantizeOp quantize_op) {
      auto quantize_output = quantize_op.getOutput();
      auto quantize_type = quantize_output.getType();
      input_types.push_back(quantize_type);
      auto new_arg = bb.addArgument(quantize_type, loc);
      quantize_output.replaceAllUsesWith(new_arg);
      quantize_op.erase();
      arg.dropAllUses();
      bb.eraseArgument(0);
    };

      allTypesFp &= !mlir::isa<quant::QuantizedType>(type.getElementType());
      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());

/// corresponding storage attribute (typically FloatAttr -> IntegerAttr).
/// quantizedElementType is the QuantizedType that describes the expressed
/// origValue.
/// Returns a converter Attribute or nullptr if conversion is not possible.
static Attribute convertPrimitiveValueAttr(
    Attribute origRealValue, quant::QuantizedType quantizedElementType,
    const UniformQuantizedValueConverter &converter, Type &outConvertedType) {

    }

    quant::QuantizedType elementType =
        static_cast<const ConcreteRewriteClass *>(this)
            ->convertFakeQuantAttrsToType(op, converter.expressed_type);

    if (!elementType) {
      // Note that the fakeQuantAttrsToType will have emitted the error.
      return true;
    }

    Type quantizedType = converter.convert(elementType);
    assert(quantizedType &&

class Attribute;
class Type;

namespace quant {
class QuantizedType;
class UniformQuantizedType;
}  // namespace quant
namespace quantfork {
class UniformQuantizedValueConverter;

/// Converts an attribute from a type based on
/// quantizedElementType.getExpressedType() to one based on
/// quantizedElementType.getStorageType(), where quantizedElementType is as from
/// QuantizedType::getQuantizedElementType().