add error judgment, and add testing for 0-size tensor. (#55952)

paddle/fluid/eager/to_static/run_program_op_node.h

@@ -130,7 +130,8 @@ static void ShareTensorsIntoScope(const std::vector<Tensor> &tensors,
                                   paddle::framework::Scope *scope) {
   for (size_t i = 0; i < tensors.size(); ++i) {
     auto name = tensors[i].name();
-    if (name == paddle::framework::kFakeVarName) {
+    if (name == paddle::framework::kFakeVarName ||
+        name == paddle::framework::kEmptyVarName) {
       continue;
     }
     auto *var = scope->Var(name);

paddle/fluid/operators/run_program_op.h

@@ -143,7 +143,8 @@ static void ShareVarsIntoScope(const std::vector<Variable *> &vars,
                                const std::vector<std::string> &var_names,
                                framework::Scope *scope) {
   for (size_t i = 0; i < vars.size(); ++i) {
-    if (var_names[i] == framework::kFakeVarName) {
+    if (var_names[i] == framework::kFakeVarName ||
+        var_names[i] == paddle::framework::kEmptyVarName) {
       continue;
     }
     auto *var = scope->Var(var_names[i]);

test/dygraph_to_static/test_backward_without_params.py

@@ -41,5 +41,28 @@ class TestBackwardWithoutParams(unittest.TestCase):
         np.testing.assert_equal(x.grad.numpy(), np.full(x.shape, 0.25))
 
 
+class ZeroSizeNet(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    @paddle.jit.to_static
+    def forward(self, x):
+        y = paddle.randn((0,))
+        out = paddle.nn.functional.relu(x)
+        y.stop_gradient = True
+        return y, out
+
+
+class TestZeroSizeNet(unittest.TestCase):
+    def test_run(self):
+        net = ZeroSizeNet()
+        x = paddle.ones([2, 2])
+        x.stop_gradient = False
+        _, out = net(x)
+        loss = paddle.mean(out)
+        loss.backward()
+        np.testing.assert_equal(x.grad.numpy(), np.full(x.shape, 0.25))
+
+
 if __name__ == '__main__':
     unittest.main()