nnvm graph

class Graph {
 public:
  // outputs of the computation graph.
  std::vector<NodeEntry> outputs;
  std::unordered_map<std::string, std::shared_ptr<any> > attrs;

 private:
  // internal structure of indexed graph
  std::shared_ptr<const IndexedGraph> indexed_graph_;
};

class IndexedGraph {
 private:
  // Node pointers in CSR structure.
  std::vector<Node> nodes_;
  // Index to all input nodes.
  std::vector<uint32_t> input_nodes_;
  // Index to all mutable input nodes.
  std::unordered_set<uint32_t> mutable_input_nodes_;
  // space to store the outputs entries
  std::vector<NodeEntry> outputs_;
  // mapping from node to index.
  std::unordered_map<const nnvm::Node*, uint32_t> node2index_;
  // CSR pointer of node entries
  std::vector<size_t> entry_rptr_;
  // space to store input entries of each
  std::vector<NodeEntry> input_entries_;
  // control flow dependencies
  std::vector<uint32_t> control_deps_;
};

int NNGraphCreate(SymbolHandle symbol, GraphHandle *graph) {
  Graph* g = new Graph();
  g->outputs = static_cast<Symbol*>(symbol)->outputs;
  *graph = g;
}

int NNGraphGetSymbol(GraphHandle graph, SymbolHandle *symbol) {
  Symbol* s = new Symbol();
  s->outputs = static_cast<Graph*>(graph)->outputs;
  *symbol = s;
}

class Symbol {
  std::vector<NodeEntry> outputs;
};

inline void DFSVisit(const std::vector<NodeEntry>& heads, FVisit fvisit);

import mxnet as mx

a = mx.sym.Variable('a')
b = mx.sym.Variable('b')
c = a + b

print c.tojson()

{
  "nodes": [
    {
      "op": "null", 
      "name": "a", 
      "inputs": []
    }, 
    {
      "op": "null", 
      "name": "b", 
      "inputs": []
    }, 
    {
      "op": "elemwise_add", 
      "name": "_plus0", 
      "inputs": [[0, 0, 0], [1, 0, 0]]
    }
  ], 
  "arg_nodes": [0, 1], 
  "node_row_ptr": [0, 1, 2, 3], 
  "heads": [[2, 0, 0]], 
  "attrs": {"mxnet_version": ["int", 1000]}
}

import mxnet as mx
data = mx.symbol.Variable('data')
fc1 = mx.symbol.FullyConnected(data=data, name='fc1', num_hidden=128)
mlp = mx.symbol.SoftmaxOutput(data=fc1, name='softmax')
print mlp.tojson()

{
  "nodes": [
    {
      "op": "null", 
      "name": "data", 
      "inputs": []
    }, 
    {
      "op": "null", 
      "name": "fc1_weight", 
      "attr": {"num_hidden": "128"}, 
      "inputs": []
    }, 
    {
      "op": "null", 
      "name": "fc1_bias", 
      "attr": {"num_hidden": "128"}, 
      "inputs": []
    }, 
    {
      "op": "FullyConnected", 
      "name": "fc1", 
      "attr": {"num_hidden": "128"}, 
      "inputs": [[0, 0, 0], [1, 0, 0], [2, 0, 0]]
    }, 
    {
      "op": "null", 
      "name": "softmax_label", 
      "inputs": []
    }, 
    {
      "op": "SoftmaxOutput", 
      "name": "softmax", 
      "inputs": [[3, 0, 0], [4, 0, 0]]
    }
  ], 
  "arg_nodes": [0, 1, 2, 4], 
  "node_row_ptr": [0, 1, 2, 3, 4, 5, 6], 
  "heads": [[5, 0, 0]], 
  "attrs": {"mxnet_version": ["int", 1000]}
}