fix no_grad context error in train mode when using save/load (#36434)

* fix no_grad context error in train mode when using save/load

* change net to train mode in test case

python/paddle/fluid/dygraph/io.py

@@ -844,6 +844,8 @@ def _run_dygraph(instance, input, program_holder):
             continue
         persistable_var._set_grad_type(grad_var.type())
 
+    drop_scope_if_no_grad(instance, tmp_scope_vec)
+
     # 3. prepare output, keep same form with inputs
     outs = output_vars
     if len(output_vars) == 1:
@@ -851,6 +853,12 @@ def _run_dygraph(instance, input, program_holder):
     return outs
 
 
+def drop_scope_if_no_grad(instance, scope_vec):
+    tracer = framework._dygraph_tracer()
+    if (not instance._is_test) and (not tracer._has_grad):
+        scope_vec.value().get_scope().drop_kids()
+
+
 def _run_static_graph(input, program_holder, trace_program):
     main_program = framework.default_main_program()
     param_var_names = _get_persistable_var_names(trace_program)

python/paddle/fluid/tests/unittests/test_io_save_load.py

@@ -15,6 +15,7 @@
 from __future__ import print_function
 
 import unittest
+import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
 
@@ -69,5 +70,22 @@ class TestSaveInferenceModelAPIError(unittest.TestCase):
                 main_program=main_prog)
 
 
+class TestWhenTrainWithNoGrad(unittest.TestCase):
+    def test_when_train_with_no_grad(self):
+        paddle.disable_static()
+        net = paddle.nn.Linear(1024, 1)
+        net = paddle.jit.to_static(net)
+        x = paddle.rand([1024], 'float32')
+        net(x)
+        save_path = './train_with_no_grad'
+        paddle.jit.save(net, save_path)
+        net = paddle.jit.load(save_path)
+        net.train()
+
+        with paddle.no_grad():
+            x = paddle.rand([1024], 'float32')
+            net(x)
+
+
 if __name__ == '__main__':
     unittest.main()