Allow partial positional arguments of input symbol

src/symbol/symbol.cc

@@ -246,6 +246,16 @@ Symbol Symbol::operator[] (size_t index) const {
   }
 }
 
+// create a default variable name
+inline std::string DefaultVarName(const std::string &op_name,
+                                  const std::string &arg_name) {
+  if (op_name.length() == 0) {
+    return arg_name;
+  } else {
+    return op_name + '_' + arg_name;
+  }
+}
+
 void Symbol::Compose(const std::vector<Symbol>& args,
                      const std::string& name) {
   CHECK_EQ(NumOutputs(), 1) << "Only composition of value function is supported currently";
@@ -261,13 +271,17 @@ void Symbol::Compose(const std::vector<Symbol>& args,
   if (this->is_atomic()) {
     // atomic symbol do not have place holder for all the arguments
     std::vector<std::string> req_args = heads_[0].source->op->ListArguments();
-    CHECK_EQ(args.size(), req_args.size())
+    CHECK_LE(args.size(), req_args.size())
         << "Incorrect number of arguments, requires " << req_args.size()
         << ", provided " << args.size();
-    heads_[0].source->inputs.resize(args.size());
+    heads_[0].source->inputs.resize(req_args.size());
     for (size_t i = 0; i < args.size(); ++i) {
       heads_[0].source->inputs[i] = args[i].heads_[0];
     }
+    for (size_t i = args.size(); i < req_args.size(); ++i) {
+      heads_[0].source->inputs[i] = DataEntry(
+          std::make_shared<Node>(nullptr, DefaultVarName(name, req_args[i])), 0);
+    }
   } else {
     // find all the place holders
     size_t arg_counter = 0;
@@ -325,15 +339,8 @@ void Symbol::Compose(const std::unordered_map<std::string, Symbol>& kwargs,
         heads_[0].source->inputs[i] = iter->second.heads_[0];
         ++nmatched;
       } else {
-        // create a variable node
-        // TODO(bing): think of naming convention
-        if (name.length() == 0) {
-          heads_[0].source->inputs[i] = DataEntry(
-              std::make_shared<Node>(nullptr, req_args[i]), 0);
-        } else {
-          heads_[0].source->inputs[i] = DataEntry(
-              std::make_shared<Node>(nullptr, name + '_' + req_args[i]), 0);
-        }
+        heads_[0].source->inputs[i] = DataEntry(
+            std::make_shared<Node>(nullptr, DefaultVarName(name, req_args[i])), 0);
       }
     }
     // if things goes wrong recover the old state

tests/python/train/test_mlp.py

@@ -9,12 +9,12 @@
 # symbol net
 batch_size = 100
 data = mx.symbol.Variable('data')
-fc1 = mx.symbol.FullyConnected(data = data, name='fc1', num_hidden=128)
-act1 = mx.symbol.Activation(data = fc1, name='relu1', act_type="relu")
-fc2 = mx.symbol.FullyConnected(data = act1, name = 'fc2', num_hidden = 64)
-act2 = mx.symbol.Activation(data = fc2, name='relu2', act_type="relu")
-fc3 = mx.symbol.FullyConnected(data = act2, name='fc3', num_hidden=10)
-softmax = mx.symbol.Softmax(data = fc3, name = 'sm')
+fc1 = mx.symbol.FullyConnected(data, name='fc1', num_hidden=128)
+act1 = mx.symbol.Activation(fc1, name='relu1', act_type="relu")
+fc2 = mx.symbol.FullyConnected(act1, name = 'fc2', num_hidden = 64)
+act2 = mx.symbol.Activation(fc2, name='relu2', act_type="relu")
+fc3 = mx.symbol.FullyConnected(act2, name='fc3', num_hidden=10)
+softmax = mx.symbol.Softmax(fc3, name = 'sm')
 
 num_round = 4
 prefix = './mlp'