Type result_element_type = op.getType().getElementType();
    Type element_type = input_tensor_element_type.getIntOrFloatBitWidth() >=
                                result_element_type.getIntOrFloatBitWidth()
                            ? input_tensor_element_type
                            : result_element_type;
    auto output_shape = InferXlaConvOutputShape(

ShapedType ConvertIntToQint(ShapedType input_type, MLIRContext* ctx) {
  int bit_width;
  bool is_signed;

  Type ele_type = input_type.getElementType();
  if (ele_type.isIntOrFloat()) {
    bit_width = ele_type.getIntOrFloatBitWidth();
    is_signed = ele_type.isSignlessIntOrFloat() || ele_type.isSignedInteger();
  } else if (QuantizedType qtype = mlir::dyn_cast<QuantizedType>(ele_type)) {
    bit_width = qtype.getStorageTypeIntegralWidth();

      input_element_type.isIntOrFloat() && output_element_type.isIntOrFloat()) {
    const auto input_element_type_bitwidth =
        input_element_type.getIntOrFloatBitWidth();
    const auto output_element_type_bitwidth =
        output_element_type.getIntOrFloatBitWidth();

    auto is_output_shape_valid_with_small_input_element_type_bitwidth = [&]() {
      if (output_element_type_bitwidth % input_element_type_bitwidth != 0) {

  Type type = x_type.clone(builder->getI32Type());
  return builder->create<CastOp>(loc, type, x, truncate);
}

static APFloat ConvertToAPFloat(double val, Type type) {
  if (type.getIntOrFloatBitWidth() == 32) {
    return APFloat(static_cast<float>(val));
  }

  return APFloat(val);
}

// Performs the operation of `Shape(input)[idx]`.

  // aligned to the nearest byte. So this is allowed.
  const char* raw_input = input_tensor.getRawData().data();
  const int element_byte_size =
      input_tensor.getElementType().getIntOrFloatBitWidth() / 8;

  // Hold current ND index in input tensor when computing
  // permutation.
  llvm::OwningArrayRef<uint64_t> current_input_index(
      input_tensor.getType().getRank());