*mutable_quant_method->add_quantization_component_specs() = quant_spec;
  auto output = GetWeightComponentSpec(quant_options);
  EXPECT_TRUE(output.has_value());
}

TEST(TfOpQuantSpecTest, WeightComponentSpecDoNotExist) {
  QuantizationOptions quant_options;
  auto output = GetWeightComponentSpec(quant_options);
  EXPECT_FALSE(output.has_value());
}

}  // namespace

// Check if the data is in quantizable precision. Currently, a value in f32 or
// bf16 is quantizable.
bool IsValueWithQuantizablePrecision(Value val);

std::optional<tensorflow::quantization::QuantizationComponentSpec>
GetWeightComponentSpec(
    const tensorflow::quantization::QuantizationOptions& quantization_options);

// Returns the spec for the given operation that can be used for both of
// dynamic and static range quantization.

  if (type.getElementType().isF32() || type.getElementType().isBF16())
    return true;
  return false;
}

std::optional<tensorflow::quantization::QuantizationComponentSpec>
GetWeightComponentSpec(
    const tensorflow::quantization::QuantizationOptions& quantization_options) {
  for (auto& cur_spec : quantization_options.quantization_method()
                            .quantization_component_specs()) {

        quant_options_(quantization_options) {}

  LogicalResult matchAndRewrite(TF::ConstOp op,
                                PatternRewriter& rewriter) const override {
    auto weight_component_spec = GetWeightComponentSpec(quant_options_);
    if (!weight_component_spec) return failure();

    // 1. Check if the constant is quantizable.
    if (failed((isQuantizableWeight(op)))) {
      return failure();
    }