Method Initialize

tensorflow/cc/framework/gradients.cc:249–340

}

Status SymbolicGradientBuilder::Initialize() {
  if (outputs_.size() != grad_inputs_.size()) {
    return errors::InvalidArgument(
        "Must specify a gradient input for each output.");
  }
  std::vector<bool> reachable_nodes = GetReachableNodes();
  for (const Output& input : inputs_) {
    if (!reachable_nodes[input.node()->id()]) {
      return errors::InvalidArgument(
          "Cannot compute the partial derivative for node '",
          input.node()->name(),
          "' as it's unreachable from the output node(s).");
    }
  }
  grad_outputs_->clear();
  grad_outputs_->resize(inputs_.size());

  std::unordered_set<int> output_nodes;
  output_nodes.reserve(outputs_.size());
  for (size_t i = 0; i < outputs_.size(); ++i) {
    output_nodes.insert(outputs_[i].node()->id());
  }

  std::unordered_set<int> stop_backprop_nodes =
      GetStopBackpropNodes(reachable_nodes, output_nodes);

  // Populate `input_nodes_` from Outputs in `inputs_`.
  input_nodes_.reserve(inputs_.size());
  for (size_t i = 0; i < inputs_.size(); ++i) {
    input_nodes_.insert({inputs_[i], i});
  }

  // TODO(andydavis) Consider a more efficient data structure for `pending_` to
  // handle computing gradients over small subgraphs from a very large graph.
  pending_.resize(scope_.graph()->num_node_ids(), 0);
  {
    backprops_.clear();
    std::unordered_set<Node*> visited;
    std::deque<Node*> queue;
    for (const Output& nout : inputs_) {
      auto const& pair = visited.insert(nout.node());
      if (pair.second) {
        queue.push_back(nout.node());
      }
    }

    // Going forward to figure out which endpoints need backprop-ed.
    // A node's endpoints need to be backprop-ed only if one of the
    // arg node can reach the node via data edges.
    while (!queue.empty()) {
      Node* n = queue.front();
      queue.pop_front();
      for (int i = 0; i < n->num_outputs(); ++i) {
        backprops_[{n, i}].clear();
      }
      int num_expected_backprops = 0;
      if (stop_backprop_nodes.find(n->id()) == stop_backprop_nodes.end()) {
        // Internal node: continue BFS along connected outputs.