!1800 fix cpu StridedSliceGrad bug when different dims between input and output

Merge pull request !1800 from sunsuodong/fix_StrideSliceGrad

mindspore/ccsrc/kernel/cpu/slice_grad_cpu_kernel.cc

@@ -61,11 +61,11 @@ void SliceGradCPUKernel::InitKernel(const CNodePtr &kernel_node) {
       end_.emplace_back(begin_[i] + sizes[i]);
     }
   }
-  CPUKernelUtils::ExpandDimsTo4(&output_dx_shape_);
-  auto input_len = input_dy_shape_.size();
-  if (input_len < 4) {
-    for (size_t i = 0; i < 4 - input_len; ++i) {
-      input_dy_shape_.insert(input_dy_shape_.begin(), 1);
+
+  auto output_len = output_dx_shape_.size();
+  if (output_len < 4) {
+    for (size_t i = 0; i < 4 - output_len; ++i) {
+      output_dx_shape_.insert(output_dx_shape_.begin(), 1);
       begin_.insert(begin_.begin(), 0);
       strides_.insert(strides_.begin(), 1);
       end_.insert(end_.begin(), 1);

tests/st/ops/cpu/test_stridedslice_grad_op.py

@@ -19,6 +19,7 @@ import pytest
 import mindspore.context as context
 import mindspore.nn as nn
 from mindspore import Tensor
+from mindspore.common import dtype as mstype
 from mindspore.common.api import ms_function
 from mindspore.ops import operations as P
 from mindspore.ops.operations import _grad_ops as G
@@ -38,7 +39,7 @@ class StridedSliceGrad(nn.Cell):
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_slice():
     x = Tensor(np.array([[[1., 1., 1.], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]], [[5, 5, 5], [6, 7, 8]]]).astype(np.float32))
@@ -47,3 +48,29 @@ def test_slice():
     output = ssg(dy, x)
     expect = [[[0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0]], [[5, 1, 5], [6, 1, 8]]]
     assert (output.asnumpy() == expect).all()
+
+
+class StridedSliceGrad2(nn.Cell):
+    def __init__(self):
+        super(StridedSliceGrad2, self).__init__()
+        self.ssg = G.StridedSliceGrad()
+        self.shape = P.Shape()
+
+    @ms_function
+    def construct(self, dy, x):
+        return self.ssg(dy, self.shape(x), (0, 0, 0), (1, 4, 2), (1, 1, 1))
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.env_onecard
+def test_slice2():
+    x = Tensor(np.arange(2 * 4 * 2).reshape(2, 4, 2), mstype.float32)
+    dy = Tensor(np.arange(4 * 2).reshape(4, 2), mstype.float32)
+    ssg = StridedSliceGrad2()
+    output = ssg(dy, x)
+    expect = [[[0., 1.], [2., 3.], [4., 5.], [6., 7.]], [[0., 0.], [0., 0.], [0., 0.], [0., 0.]]]
+    assert (output.asnumpy() == expect).all()
+
+if __name__ == '__main__':
+    test_slice()
+    test_slice2()

tests/st/ops/cpu/test_stridedslice_op.py

@@ -34,7 +34,7 @@ class StridedSlice(nn.Cell):
 
 
 @pytest.mark.level0
-@pytest.mark.platform_x86_cpu_training
+@pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
 def test_slice():
     x = Tensor(np.array([[[1., 1., 1.], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]], [[5, 5, 5], [6, 7, 8]]]).astype(np.float32))