optional int32 dimension = 1;
}

// Signals quantization type to be per-tensor.
message PerTensor {}

// Corresponds to StableHLO's `QuantizedTensorElementType`. Type parameters such
// as `QuantizationParameters` is omitted because they are determined during
// quantization.
// See https://github.com/openxla/stablehlo/blob/main/docs/spec.md#types for
// details.
//

  std::optional<BufferOffset<tflite::Tensor>> BuildTensor(
      Value value, const std::string& name, unsigned buffer_idx,
      const std::optional<BufferOffset<tflite::QuantizationParameters>>&
          quant_parameters);

  // TODO(b/137395003): Legalize tf.IfOp to TFLite dialect, and change the
  // following method to handle TFL::IfOp.
  BufferOffset<tflite::Operator> BuildIfOperator(

struct QuantizationParametersBuilder {
  typedef QuantizationParameters Table;
  ::flatbuffers::FlatBufferBuilder &fbb_;
  ::flatbuffers::uoffset_t start_;
  void add_min(::flatbuffers::Offset<::flatbuffers::Vector<float>> min) {
    fbb_.AddOffset(QuantizationParameters::VT_MIN, min);
  }
  void add_max(::flatbuffers::Offset<::flatbuffers::Vector<float>> max) {
    fbb_.AddOffset(QuantizationParameters::VT_MAX, max);
  }

}

template <typename T>
std::vector<T> GetAsVector(const flatbuffers::Vector<T>* vec) {
  return std::vector<T>(vec->begin(), vec->end());
}

void VerifyQuantizationScale(
    const QuantizationParameters& float_quant_params,
    const QuantizationParametersT& quantized_quant_params, const int bit_num,
    const bool symmetric) {
  const float eps = 1e-7;
  ASSERT_THAT(*float_quant_params.min(), SizeIs(1));

}

// Represents a specific quantization technique's parameters.
union QuantizationDetails {
  CustomQuantization,
}

// Parameters for converting a quantized tensor back to float.
table QuantizationParameters {
  // These four parameters are the asymmetric linear quantization parameters.
  // Given a quantized value q, the corresponding float value f should be:
  //   f = scale * (q - zero_point)

}

// Represents a specific quantization technique's parameters.
union QuantizationDetails {
  CustomQuantization,
}

// Parameters for converting a quantized tensor back to float.
table QuantizationParameters {
  // These four parameters are the asymmetric linear quantization parameters.
  // Given a quantized value q, the corresponding float value f should be:
  //   f = scale * (q - zero_point)

}

// Represents a specific quantization technique's parameters.
union QuantizationDetails {
  CustomQuantization,
}

// Parameters for converting a quantized tensor back to float.
table QuantizationParameters {
  // These four parameters are the asymmetric linear quantization parameters.
  // Given a quantized value q, the corresponding float value f should be:
  //   f = scale * (q - zero_point)