refer to [PR Allow operators with multiple outputs in get_atomic_symbol

apache#15740](apache#15740)

benchmark/python/gluon/benchmark_gluon.py

@@ -46,9 +46,9 @@
                          'By default, use CPU only.')
 parser.add_argument('--type', type=str, default='inference', choices=['all', 'training', 'inference'])
 
-opt = parser.parse_args()
+args = parser.parse_args()
 
-num_batches = opt.num_batches
+num_batches = args.num_batches
 dry_run = 10  # use 10 iterations to warm up
 batch_inf = [1, 32, 64, 128, 256]
 batch_train = [1, 32, 64, 128, 256]
@@ -116,10 +116,10 @@ def train(network, batch_size, ctx):
     return bwd
 
 if __name__ == '__main__':
-    runtype = opt.type
-    bs = opt.batch_size
+    runtype = args.type
+    bs = args.batch_size
 
-    if opt.model == 'all':
+    if args.model == 'all':
         networks = ['alexnet', 'densenet121', 'densenet161', 'densenet169', 'densenet201',
                     'inceptionv3', 'mobilenet0.25', 'mobilenet0.5', 'mobilenet0.75',
                     'mobilenet1.0', 'mobilenetv2_0.25', 'mobilenetv2_0.5', 'mobilenetv2_0.75',
@@ -130,9 +130,9 @@ def train(network, batch_size, ctx):
         logging.info('It may take some time to run all models, '
                      'set --network to run a specific one')
     else:
-        networks = [opt.model]
+        networks = [args.model]
 
-    devs = [mx.gpu(int(i)) for i in opt.gpus.split(',')] if opt.gpus.strip() else [mx.cpu()]
+    devs = [mx.gpu(int(i)) for i in args.gpus.split(',')] if args.gpus.strip() else [mx.cpu()]
     num_gpus = len(devs)
 
     for network in networks:

src/c_api/c_api_symbolic.cc

@@ -854,10 +854,15 @@ int MXGenAtomicSymbolFromSymbol(SymbolHandle sym_handle, SymbolHandle *ret_sym_h
   nnvm::Symbol *s = new nnvm::Symbol();
   API_BEGIN();
   nnvm::Symbol *source = static_cast<nnvm::Symbol *>(sym_handle);
-  CHECK_EQ(source->outputs.size(), 1U)
-    << "Generating atomic symbol from other symbol only works for nongrouped symbol.";
-  const auto& node = source->outputs[0];
-  const auto *op = node.node->op();
+  CHECK_GE(source->outputs.size(), 1) << "Input symbol does not have outputs.";
+      << "Generating atomic symbol from other symbol only works for nongrouped symbol.";    const auto &node = source->outputs[0].node;
+  const auto &node = source->outputs[0];    for (const auto &other_node : source->outputs) {
+  const auto *op = node.node->op();     if (node.get() != other_node.node.get()) {
+      LOG(FATAL)
+        << "Generating atomic symbol from other symbol only works for nongrouped symbol.";
+    }
+  }
+  const auto *op = node->op();
   const auto attrs = source->ListAttrs(nnvm::Symbol::ListAttrOption::kShallow);
   *s = nnvm::Symbol::CreateFunctor(op, attrs);
   *ret_sym_handle = s;

tests/python/unittest/test_symbol.py

@@ -373,6 +373,15 @@ def test_children_same_name():
     for c in b.get_children():
         pass
 
+def test_gen_atomic_symbol_multiple_outputs():
+    data=mx.sym.Variable('data')
+    p = mx.sym.Variable('param')
+    h0 = mx.sym.Variable('h0')
+    h1 = mx.sym.Variable('h1')
+    s = mx.sym.RNN(data, p, h0, h1, state_size=10, num_layers=2, 
+                   bidirectional=True, state_outputs=True, mode='lstm')
+    atomic_sym = s._gen_atomic_symbol()
+
 if __name__ == '__main__':
     import nose
     nose.runmodule()