Function GetArrayLabel

tensorflow/lite/toco/dump_graphviz.cc:248–353

}

string GetArrayLabel(const Model& model, const string& array_id) {
  string html;

  // Use HTML-like labels (http://www.graphviz.org/doc/info/shapes.html#html)
  html += "<";

  // Begin Table
  html += R"CODE(<FONT POINT-SIZE="10" FACE="Courier">)CODE";
  html += R"CODE(<TABLE BORDER="0" CELLSPACING="2" CELLPADDING="0">)CODE";

  auto& array = model.GetArray(array_id);
  if (array.buffer) {
    // "cylinder" shapes require some extra head room.
    html += R"CODE(<TR><TD COLSPAN="2"> </TD></TR>)CODE";
  }

  // "Primary" name of array (last non-slash delimited group of characters).
  html += R"CODE(<TR><TD COLSPAN="2" ALIGN="CENTER">)CODE";
  html += R"CODE(<FONT POINT-SIZE="16" FACE="Helvetica"><I>)CODE";
  AppendF(&html, R"CODE(%s)CODE",
          std::vector<string>(absl::StrSplit(array_id, '/')).back());
  html += R"CODE(</I></FONT>)CODE";
  html += "</TD></TR>";

  // Array data type and dimensions
  html += R"CODE(<TR><TD COLSPAN="2" ALIGN="CENTER">)CODE";
  html += R"CODE(<FONT POINT-SIZE="14" FACE="Courier"><B>)CODE";
  // Type
  html += ArrayDataTypeName(array.data_type);
  // Shape
  if (array.has_shape()) {
    auto& array_shape = array.shape();
    html += "[";
    for (int dim = 0; dim < array_shape.dimensions_count(); dim++) {
      AppendF(&html, "%d", array_shape.dims(dim));
      if (dim + 1 < array_shape.dimensions_count()) {
        html += kUnicodeMult;
      }
    }
    html += "]";
  }

  // Small buffer sample
  int buffer_size = 0;
  if (array.buffer) {
    buffer_size = RequiredBufferSizeForShape(array.shape());
  }
  if ((buffer_size > 0) && (buffer_size <= 4)) {
    html += " = ";
    if (array.shape().dimensions_count() > 0) {
      html += "{";
    }
    for (int i = 0; i < buffer_size; i++) {
      AppendArrayVal(&html, array, i);
      if (i + 1 < buffer_size) {
        html += ", ";
      }
    }