Method QuantizeTensor

tensorflow/lite/kernels/test_util.h:527–550

  }

  std::vector<int8_t> QuantizeTensor(int index,
                                     const std::vector<float>& data) {
    TfLiteTensor* t = interpreter_->tensor(index);
    const int length = data.size();
    std::vector<int8_t> q(length);
    float min, max, scaling_factor;
    tensor_utils::SymmetricQuantizeFloats(data.data(), length, q.data(), &min,
                                          &max, &scaling_factor);
    // Update quantization params.
    t->params.scale = scaling_factor;
    t->params.zero_point = 0;
    // Populate the new quantization params.
    TfLiteQuantizationFree(&t->quantization);
    t->quantization.type = kTfLiteAffineQuantization;
    auto* affine_quantization = reinterpret_cast<TfLiteAffineQuantization*>(
        malloc(sizeof(TfLiteAffineQuantization)));
    affine_quantization->quantized_dimension = 0;
    affine_quantization->scale = TfLiteFloatArrayCreate(1);
    affine_quantization->zero_point = TfLiteIntArrayCreate(1);
    affine_quantization->scale->data[0] = scaling_factor;
    affine_quantization->zero_point->data[0] = 0;
    t->quantization.params = affine_quantization;
    return q;
  }

  std::map<int, TensorData> tensor_data_;
  std::vector<int32_t> inputs_;