Function ConvertPlaceholderOperator

tensorflow/lite/toco/import_tensorflow.cc:1503–1541

}

tensorflow::Status ConvertPlaceholderOperator(
    const NodeDef& node, const TensorFlowImportFlags& tf_import_flags,
    const ModelFlags& model_flags, Model* model) {
  CHECK(node.op() == "Placeholder" || node.op() == "LegacyFedInput");
  if (node.op() == "Placeholder") {
    TF_QCHECK_OK(CheckInputsCount(node, tf_import_flags, 0));
  }

  bool inside_input_arrays = false;
  for (const auto& input_array : model_flags.input_arrays()) {
    if (node.name() == input_array.name()) {
      inside_input_arrays = true;
      break;
    }
  }

  if (!inside_input_arrays) {
    model->AddInvalidInputArray(node.name());
  }

  auto& array = model->GetOrCreateArray(node.name());
  if (node.attr().count("dtype")) {
    array.data_type = ConvertDataType(GetDataTypeAttr(node, "dtype"));
  }
  if (node.attr().count("shape")) {
    const auto& shape = GetShapeAttr(node, "shape");
    auto num_dims = shape.dim_size();
    // TODO(b/62716978): This logic needs to be revisited.  During dims
    // refactoring it is an interim fix.
    if (num_dims > 0 && !HasWildcardDimension(shape)) {
      auto& dst_array_dims = *array.mutable_shape()->mutable_dims();
      dst_array_dims.resize(num_dims);
      for (std::size_t i = 0; i < num_dims; i++) {
        dst_array_dims[i] = shape.dim(i).size();
      }
    }
  }
  return tensorflow::Status::OK();
}

tensorflow::Status ConvertNoOpOperator(
    const NodeDef& node, const TensorFlowImportFlags& tf_import_flags,