Function LeakyReluPrepare

tensorflow/lite/kernels/activations.cc:248–274

}

TfLiteStatus LeakyReluPrepare(TfLiteContext* context, TfLiteNode* node) {
  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
  const TfLiteTensor* input = GetInput(context, node, 0);
  TfLiteTensor* output = GetOutput(context, node, 0);
  TF_LITE_ENSURE_EQ(context, input->type, output->type);

  LeakyReluOpData* data = reinterpret_cast<LeakyReluOpData*>(node->user_data);

  if (output->type == kTfLiteUInt8) {
    const auto* params =
        reinterpret_cast<TfLiteLeakyReluParams*>(node->builtin_data);
    // Quantize the alpha with same zero-point and scale as of input
    data->q_alpha = static_cast<uint8_t>(std::max<float>(
        std::numeric_limits<uint8_t>::min(),
        std::min<float>(std::numeric_limits<uint8_t>::max(),
                        std::round(input->params.zero_point +
                                   (params->alpha / input->params.scale)))));

    double real_multiplier =
        input->params.scale * input->params.scale / output->params.scale;
    QuantizeMultiplierSmallerThanOneExp(
        real_multiplier, &data->output_multiplier, &data->output_shift);
  }
  return context->ResizeTensor(context, output,
                               TfLiteIntArrayCopy(input->dims));
}

template <KernelType kernel_type>
TfLiteStatus TanhPrepare(TfLiteContext* context, TfLiteNode* node) {