convert pynative mode to graph mode when loading mindir

mindspore/ccsrc/pipeline/jit/action.cc

@@ -1242,6 +1242,12 @@ std::vector<ActionItem> BackendPipeline() {
   return actions;
 }
 std::vector<ActionItem> MindIRPipeline() {
+  auto context_ptr = MsContext::GetInstance();
+  if (context_ptr->get_param<int>(MS_CTX_EXECUTION_MODE) == kPynativeMode) {
+    MS_LOG(EXCEPTION)
+      << "The graph generated form MindIR is not support to execute in the PynativeMode, please convert "
+         "to the GraphMode.";
+  }
   std::vector<ActionItem> actions;
   // Set funcGraph loaded from MindIR to resource.
   (void)actions.emplace_back(std::make_pair("load_mindir", SetMindIRGraphAction));

mindspore/python/mindspore/train/serialization.py

@@ -972,6 +972,8 @@ def _spilt_save(net_dict, model, file_name, is_encrypt, **kwargs):
 
 def _save_mindir(net, file_name, *inputs, **kwargs):
     """Save MindIR format file."""
+    if context._get_mode() == context.PYNATIVE_MODE:
+        raise RuntimeError("MindIR export is not support in the Pynative mode, please convert to the Graph Mode.")
     model = mindir_model()
 
     phase_name = "predict" if net._auto_parallel_mode else "export.mindir"

tests/st/control/test_while_mindir.py

@@ -52,12 +52,13 @@ def test_single_while():
     outputs_after_load = loaded_net(x, y)
     assert origin_out == outputs_after_load
 
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
 def test_ms_function_while():
-    context.set_context(mode=context.PYNATIVE_MODE)
+    context.set_context(mode=context.GRAPH_MODE)
     network = SingleWhileNet()
 
     x = Tensor(np.array([1]).astype(np.float32))
@@ -71,10 +72,13 @@ def test_ms_function_while():
 
     graph = load(mindir_name)
     loaded_net = nn.GraphCell(graph)
+    context.set_context(mode=context.PYNATIVE_MODE)
+
     @ms_function
     def run_graph(x, y):
         outputs = loaded_net(x, y)
         return outputs
+
     outputs_after_load = run_graph(x, y)
     assert origin_out == outputs_after_load
 
@@ -122,6 +126,7 @@ def test_single_while_inline_load():
     assert os.path.exists(mindir_name)
     load(mindir_name)
 
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training

tests/st/export_and_load/test_bgcf.py

@@ -196,6 +196,7 @@ class ForwardBGCF(nn.Cell):
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_onecard
 def test_export_bgcf():
+    context.set_context(mode=context.GRAPH_MODE)
     num_user, num_item = 7068, 3570
     network = BGCF([64, num_user, num_item], 64, "tanh",
                    [0.0, 0.0, 0.0], num_user, num_item, 64)

tests/st/export_and_load/test_get_and_init_graph_cell_parameters.py

@@ -94,18 +94,3 @@ def test_get_and_init_graph_cell_parameters_in_graph_mode():
     """
     context.set_context(mode=context.GRAPH_MODE)
     get_and_init_graph_cell_parameters()
-
-
-@pytest.mark.level0
-@pytest.mark.platform_x86_cpu
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
-@pytest.mark.platform_x86_gpu_training
-@pytest.mark.env_onecard
-def test_get_and_init_graph_cell_parameters_in_pynative_mode():
-    """
-    Description: load mind ir and update parameters in pynative mode.
-    Expectation: generate a graph with updated parameters.
-    """
-    context.set_context(mode=context.PYNATIVE_MODE)
-    get_and_init_graph_cell_parameters()

tests/ut/python/mindir/test_init_graph_cell_parameters_with_illegal_data.py

@@ -99,7 +99,7 @@ def test_init_graph_cell_parameters_with_wrong_value_shape():
     Description: load mind ir and update parameters with wrong tensor shape.
     Expectation: raise a ValueError indicating the update value shape error.
     """
-    context.set_context(mode=context.PYNATIVE_MODE)
+    context.set_context(mode=context.GRAPH_MODE)
     net = Net()
     mindir_name = "net_2.mindir"
     export(net, input_a, input_b, file_name=mindir_name[:-7], file_format='MINDIR')