Method GetInputs

tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc:1716–1755

}

Status Converter::GetInputs(const NodeDef& node_def,
                            std::vector<TRT_TensorOrWeights>* inputs) const {
  for (auto const& input_name : node_def.input()) {
    /*************************************************************************
     * TODO(jie): handle case 1) here.
     * Normalizes the inputs and extracts associated metadata:
     * 1) Inputs can contain a colon followed by a suffix of characters.
     *    That suffix may be a single number (e.g. inputName:1) or several
     *    word characters separated from a number by a colon
     *    (e.g. inputName:foo:1). The
     *    latter case is used to denote inputs and outputs of functions.
     * 2) Control dependency inputs contain caret at the beginning and we
     *    remove this and annotate the edge as a control dependency.
     ************************************************************************/
    // skip control nodes
    if (input_name[0] == '^') continue;
    string name = input_name;
    auto last = name.find_last_of(':');
    // TODO(aaroey): use TensorId
    if (last != string::npos && last + 2 == name.size() &&
        name[last + 1] == '0') {
      name.erase(last);
    }

    if (trt_tensors_.count(name)) {
      TRT_TensorOrWeights input = trt_tensors_.at(name);
      inputs->push_back(input);
      VLOG(2) << "Retrieved input " << name << ": " << input.DebugString();
    } else {
      // TODO(aaroey): this should not happen, make it a CHECK.
      // TODO(aaroey): use StrCat for pattern like this.
      string msg("Node ");
      StrAppend(&msg, node_def.name(), " should have an input named '", name,
                "' but it is not available");
      LOG(ERROR) << msg;
      return errors::InvalidArgument(msg);
    }
  }
  return Status::OK();
}

// Checks that the number of inputs match, and enforces that the inputs marked
// as true are constant weights. true means that the input must be a weight,