Fix Pynative Sync Bugs

mindspore/ccsrc/backend/session/executor.cc

@@ -20,10 +20,12 @@
 #include "runtime/device/kernel_runtime_manager.h"
 #include "utils/comm_manager.h"
 #include "utils/scoped_long_running.h"
+#include "pybind_api/ir/tensor_py.h"
 #if (ENABLE_CPU && (ENABLE_D || ENABLE_GPU))
 #include "ps/ps_cache/ps_cache_manager.h"
 #endif
 
+using mindspore::tensor::TensorPy;
 namespace mindspore {
 namespace session {
 namespace {
@@ -399,12 +401,36 @@ void Executor::RunOp(const SessionPtr &session, OpRunInfo *op_run_info, const Gr
                      std::vector<tensor::TensorPtr> *input_tensors, VectorRef *outputs,
                      const std::vector<int64_t> &tensors_mask) {
   MS_EXCEPTION_IF_NULL(session);
-  for (auto &tensor : *input_tensors) {
-    if (tensor->NeedWait()) {
-      tensor->Wait();
+  auto ms_context = MsContext::GetInstance();
+  auto target = ms_context->get_param<std::string>(MS_CTX_DEVICE_TARGET);
+  if (target == kGPUDevice) {
+    for (auto &tensor : *input_tensors) {
+      if (tensor->NeedWait()) {
+        tensor->Wait();
+      }
+    }
+    {
+      // Release GIL before calling into (potentially long-running) C++ code
+      if (Py_IsInitialized()) {
+        py::gil_scoped_release release;
+      }
+      session->RunOpImpl(graph_info, op_run_info, input_tensors, outputs, tensors_mask);
     }
+  } else {
+    auto task = std::make_shared<RunOpTask>();
+    task->session_ = session;
+    task->op_run_info_ = op_run_info;
+    task->graph_info_ = graph_info;
+    task->input_tensors_ = input_tensors;
+    task->tensors_mask_ = tensors_mask;
+    for (auto &tensor : *input_tensors) {
+      if (tensor->NeedWait()) {
+        tensor->Wait();
+      }
+    }
+    RunTask(task, true, true);
+    *outputs = task->outputs_;
   }
-  session->RunOpImpl(graph_info, op_run_info, input_tensors, outputs, tensors_mask);
 }
 
 void Executor::RunOpsInGraph(const SessionPtr &session, const GraphId &graph_id,

mindspore/ccsrc/pipeline/pynative/pynative_execute.cc

@@ -1455,11 +1455,7 @@ py::object ForwardExecutor::RunOpInMs(const OpExecInfoPtr &op_exec_info, Pynativ
                                     op_exec_info->next_input_index};
 #endif
   VectorRef outputs;
-  {
-    // Release GIL before calling into (potentially long-running) C++ code
-    py::gil_scoped_release release;
-    session->RunOp(&op_run_info, graph_info, &input_tensors, &outputs, tensors_mask);
-  }
+  session->RunOp(&op_run_info, graph_info, &input_tensors, &outputs, tensors_mask);
   if (op_exec_info->is_dynamic_shape) {
     op_exec_info->abstract = op_run_info.abstract;
   }