fix copyslice grad bug

mindspore/ccsrc/pipeline/pynative/forward/forward.cc

@@ -265,7 +265,7 @@ void UpdateStubTensor(const FrontendOpRunInfoPtr &op_run_info) {
 }
 
 KernelTaskType GetViewOpTaskType(const std::string &op_name) {
-  if (op_name == kCopyWithScileOpName) {
+  if (op_name == kCopyWithSliceOpName) {
     return KernelTaskType::kCOPY_TASK;
   }
   return KernelTaskType::kNORMAL_VIEW_TASK;

mindspore/ccsrc/pybind_api/ir/tensor_index_py.cc

@@ -1276,7 +1276,7 @@ static inline py::object SetitemCopyView(std::vector<pynative::SliceOpInfoPtr> *
   (void)slice_op_infos->emplace_back(broadcastto_op_info);
 
   auto copy_op_info = std::make_shared<pynative::SliceOpInfo>();
-  copy_op_info->slice_op_name = kCopyWithScileOpName;
+  copy_op_info->slice_op_name = kCopyWithSliceOpName;
   copy_op_info->data_indexs = {0, 1};
   (void)slice_op_infos->emplace_back(copy_op_info);
   ValuePtr rdata_value;
@@ -1830,13 +1830,16 @@ TypeId GetStubAbsTypeId(const AbstractBasePtr &abs) {
   }
 }
 
-bool EnableView(bool is_pack_node, const TypeId &type_id, const py::bool_ &is_ascend) {
+bool EnableView(bool is_pack_node, const TypeId &type_id, const py::bool_ &is_ascend, bool is_setitem = false) {
   if (is_pack_node || pynative::PyNativeExecutor::GetInstance()->grad_executor()->is_high_order_top_cell()) {
     // 1. pack node will slice failed with view.
     // 2. SelectView and CopyWithSlice has no kernel, can not enable view in high order cell.
     return false;
   }
 
+  // For setitem, the grad of CopyWithSlice is erroneous. If we are in setitem and requires grad, disable view.
+  if (is_setitem && pynative::PyNativeExecutor::GetInstance()->grad_executor()->RequiresGrad()) return false;
+
   if (is_ascend && (type_id == kNumberTypeComplex128 || type_id == kNumberTypeFloat64)) {
     // AsStrided and ViewCopy is not support Complex128 and Float64, disable view
     return false;
@@ -2187,13 +2190,13 @@ py::object TensorIndex::SetItemIndexInfo(const py::object &py_data, const py::ob
     MS_EXCEPTION_IF_NULL(data_type);
 
     const auto &type_id = GetStubAbsTypeId(abs);
-    if (EnableView(value_info.second, type_id, is_ascend)) {
+    if (EnableView(value_info.second, type_id, is_ascend, true)) {
       data_value = value_info.first;
     }
   } else {
     TensorPtr data = py_data.cast<TensorPtr>();
     MS_EXCEPTION_IF_NULL(data);
-    if (EnableView(false, data->data_type(), is_ascend)) {
+    if (EnableView(false, data->data_type(), is_ascend, true)) {
       data_value = data;
     }
     data_shape = data->shape();

mindspore/core/ops/array_op_name.h

@@ -174,7 +174,7 @@ constexpr auto kUnsortedSegmentMinOpName = "UnsortedSegmentMin";
 constexpr auto kUnsortedSegmentMinDOpName = "UnsortedSegmentMinD";
 constexpr auto kUpdateCacheOpName = "UpdateCache";
 constexpr auto kBroadcastOpName = "Broadcast";
-constexpr auto kCopyWithScileOpName = "CopyWithSlice";
+constexpr auto kCopyWithSliceOpName = "CopyWithSlice";
 }  // namespace mindspore
 
 #endif  // MINDSPORE_CORE_BASE_ARRAY_OP_NAME_H_

tests/st/pynative/test_tensor_setitem.py

@@ -16,7 +16,7 @@
 import numpy as np
 import pytest
 
-from mindspore import Tensor, context
+from mindspore import Tensor, context, ops
 from mindspore.nn import Cell
 from mindspore import dtype as mstype
 
@@ -57,6 +57,46 @@ class NumpySetItemByList():
         return x
 
 
+class SetitemNet(Cell):
+    def construct(self, x, y):
+        z = x * 2
+        z[:, 1:] += y[:, 1:]
+        return z
+
+
+class SetitemGradNet(Cell):
+    def __init__(self, net):
+        super().__init__()
+        self.net = net
+        self.grad_op = ops.GradOperation(get_all=True)
+
+    def construct(self, x, y):
+        gradient_func = self.grad_op(self.net)
+        return gradient_func(x, y)
+
+
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_setitem_grad():
+    """
+    Feature: Test setitem grad
+    Description: setitem should return correct grad
+    Expectation: success
+    """
+    net = SetitemNet()
+    a = Tensor(np.random.randn(2, 2, 2, 2), mstype.float32)
+    b = Tensor(np.random.randn(2, 2, 2, 2), mstype.float32)
+    b = ops.zeros_like(b)
+    output = SetitemGradNet(net)(a, b)
+    x_grad = np.ones((2, 2, 2, 2), np.float32) * 2
+    y_grad = np.array([[[[0, 0], [0, 0]], [[1, 1], [1, 1]]], [[[0, 0], [0, 0]], [[1, 1], [1, 1]]]], np.float32)
+    assert np.array_equal(output[0].asnumpy(), x_grad)
+    assert np.array_equal(output[1].asnumpy(), y_grad)
+
+
 @pytest.mark.level0
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training