Function Tensor2Response

serving/processor/serving/util.cc:792–987

}

eas::PredictResponse Tensor2Response(
    const processor::Request& req,
    const processor::Response& resp,
    const SignatureInfo* signature_info) {
  eas::PredictResponse response;
  const auto& output_tensor_names = req.output_tensor_names;
  const auto & outputs = resp.outputs;

  for (size_t i = 0; i < outputs.size(); ++i) {
    eas::ArrayProto output;
    int64 total_dim_size = 1;
    for (int j = 0; j < outputs[i].dims(); ++j) {
      int64 dim_size = outputs[i].dim_size(j);
      output.mutable_array_shape()->add_dim(dim_size);
      total_dim_size *= dim_size;
    }

    switch (outputs[i].dtype()) {
      case DT_FLOAT: {
        output.set_dtype(eas::DT_FLOAT);
        auto flat = outputs[i].flat<float>();
        for (int64 j = 0; j < total_dim_size; ++j) {
          output.add_float_val(flat(j));
        }
        break;
      }
      case DT_DOUBLE: {
        output.set_dtype(eas::DT_DOUBLE);
        auto flat = outputs[i].flat<double>();
        for (int64 j = 0; j < total_dim_size; ++j) {
          output.add_double_val(flat(j));
        }
        break;
      }
      case DT_INT32: {
        output.set_dtype(eas::DT_INT32);
        auto flat = outputs[i].flat<int>();
        for (int64 j = 0; j < total_dim_size; ++j) {
          output.add_int_val(flat(j));
        }
        break;
      }
      case DT_UINT8: {
        output.set_dtype(eas::DT_UINT8);
        auto flat = outputs[i].flat<uint8>();
        for (int64 j = 0; j < total_dim_size; ++j) {
          output.add_int_val((int)flat(j));
        }
        break;
      }
      case DT_INT16: {
        output.set_dtype(eas::DT_INT16);
        auto flat = outputs[i].flat<int16>();
        for (int64 j = 0; j < total_dim_size; ++j) {
          output.add_int_val((int)flat(j));
        }
        break;
      }