!799 fix tensor dirty flag setting

Merge pull request !799 from dinghao/dirty_flag

mindspore/ccsrc/ir/meta_tensor.cc

@@ -164,8 +164,9 @@ Tensor::Tensor(const py::float_ &input, const TypePtr &data_type) { init(py::arr
 Tensor::Tensor(const py::int_ &input, const TypePtr &data_type) { init(py::array(input), data_type); }
 
 Tensor::Tensor(const Tensor &tensor, const TypePtr &data_type)
-    : MetaTensor(tensor), dirty_(tensor.dirty_), device_address_(tensor.device_address_) {
+    : MetaTensor(tensor), device_address_(tensor.device_address_) {
   init(tensor.data_, data_type);
+  dirty_ = tensor.is_dirty();
 }
 
 Tensor &Tensor::operator=(const Tensor &tensor) {
@@ -291,6 +292,7 @@ void Tensor::init(const py::array &input, const TypeId &data_type) {
   } else {
     data_ = input;
   }
+  dirty_ = true;
 }
 
 void Tensor::init(TypeId data_type, const std::vector<int> &shape, py::array *const data) {

mindspore/ccsrc/session/session_basic.cc

@@ -127,6 +127,7 @@ BaseRef CreateOneTensor(const AnfNodePtr &node, size_t output_index, const Kerne
   MS_EXCEPTION_IF_NULL(ms_context);
   if (ms_context->execution_mode() == kPynativeMode) {
     tensor->set_device_address(AnfAlgo::GetMutableOutputAddr(node, output_index));
+    tensor->set_dirty(false);
   } else if (!address->SyncDeviceToHost(trans::GetRuntimePaddingShape(node, output_index),
                                         LongToSize(tensor->data().nbytes()), tensor->data_type(),
                                         tensor->data_c(true))) {
@@ -491,7 +492,7 @@ void SessionBasic::LoadInputData(const std::shared_ptr<KernelGraph> &kernel_grap
           need_sync = true;
         }
       } else {
-        if (tensor->is_dirty() || !AnfAlgo::IsParameterWeight(pk_node)) {
+        if (tensor->is_dirty()) {
           need_sync = true;
         } else if (tensor->device_address() != device_address) {
           (void)tensor->data_sync();

tests/st/ops/gpu/test_assign_add_op.py

@@ -51,19 +51,22 @@ def test_assign_add():
                          [[54, 57, 60],
                           [63, 66, 69],
                           [72, 75, 78]]]])
-    x = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
-    y = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
+    x1 = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
+    y1 = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
+
+    x2 = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
+    y2 = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
 
     context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
     add = AssignAdd()
-    output1 = add(x, y)
+    output1 = add(x1, y1)
     assert (output1.asnumpy() == expect1).all()
-    output2 = add(output1, y)
+    output2 = add(output1, y1)
     assert (output2.asnumpy() == expect2).all()
 
     context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
     add = AssignAdd()
-    output1 = add(x, y)
+    output1 = add(x2, y2)
     assert (output1.asnumpy() == expect1).all()
-    output2 = add(output1, y)
+    output2 = add(output1, y2)
     assert (output2.asnumpy() == expect2).all()