fix reduce ops axis multiple bug in GPU

mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/array_reduce_gpu_kernel.h

@@ -116,6 +116,8 @@ class ArrayReduceGpuKernel : public GpuKernel {
           axis < 0 ? axis_.push_back(axis + input_dim_length) : axis_.push_back(axis);
         }
         std::sort(axis_.begin(), axis_.end());
+        auto multiple_pos = std::unique(axis_.begin(), axis_.end());
+        axis_.erase(multiple_pos, axis_.end());
       }
     } else if (prim->GetAttr("axis")->isa<Int64Imm>()) {
       int axis = static_cast<int>(GetAttr<int64_t>(kernel_node, "axis"));

mindspore/common/tensor.py

@@ -508,7 +508,7 @@ class Tensor(Tensor_):
         Check all tensor elements along a given axis evaluate to True.
 
         Args:
-            axis (Union[None, int, tuple(int)): Dimensions of reduction,
+            axis (Union[None, int, tuple(int)]): Dimensions of reduction,
                 when the axis is None or empty tuple, reduce all dimensions. Default: ().
             keep_dims (bool): Whether to keep the reduced dimensions. Default: False.
 
@@ -540,7 +540,7 @@ class Tensor(Tensor_):
         Check any tensor element along a given axis evaluate to True.
 
         Args:
-            axis (Union[None, int, tuple(int)): Dimensions of reduction,
+            axis (Union[None, int, tuple(int)]): Dimensions of reduction,
                 when the axis is None or empty tuple, reduce all dimensions. Default: ().
             keep_dims (bool): Whether to keep the reduced dimensions. Default: False.
 

mindspore/ops/operations/math_ops.py

@@ -480,10 +480,11 @@ class _Reduce(PrimitiveWithInfer):
             if np_reduce_func is not None:
                 value = input_x['value'].asnumpy()
                 if isinstance(axis_v, int):
-                    axis_v = (axis_v,)
-                elif not axis_v:
-                    axis_v = [i for i in range(len(input_x['shape']))]
-                    axis_v = tuple(axis_v)
+                    pass
+                elif axis_v:
+                    axis_v = tuple(set(axis_v))
+                else:
+                    axis_v = tuple(range(len(input_x['shape'])))
                 value = np_reduce_func(value, axis_v, keepdims=self.keep_dims)
                 value = np.array(value)
                 value = Tensor(value)

tests/st/ops/gpu/test_reduce_sum_op.py

@@ -58,7 +58,7 @@ axis7 = (1, 2)
 keep_dims7 = True
 
 x8 = np.random.rand(2, 1, 1, 4).astype(np.float32)
-axis8 = (1, 2)
+axis8 = (1, 2, 2, 1, 1, 2)
 keep_dims8 = True
 
 x9 = np.random.rand(2, 1, 1, 4).astype(np.float32)
@@ -70,7 +70,7 @@ axis10 = (0, 1, 2, 3)
 keep_dims10 = False
 
 x11 = np.random.rand(1, 1, 1, 1).astype(np.float32)
-axis11 = (0, 1, 2, 3)
+axis11 = (0, 1, 1, 2, 3, 2, 2, 0, 3)
 keep_dims11 = False
 
 x12 = np.random.rand(2, 3, 4, 4).astype(np.float32)
@@ -226,7 +226,7 @@ def test_ReduceSum():
     assert np.all(diff7 < error7)
     assert output[7].shape == expect7.shape
 
-    expect8 = np.sum(x8, axis=axis8, keepdims=keep_dims8)
+    expect8 = np.sum(x8, axis=tuple(set(axis8)), keepdims=keep_dims8)
     diff8 = abs(output[8].asnumpy() - expect8)
     error8 = np.ones(shape=expect8.shape) * 1.0e-5
     assert np.all(diff8 < error8)
@@ -244,7 +244,7 @@ def test_ReduceSum():
     assert np.all(diff10 < error10)
     assert output[10].shape == expect10.shape
 
-    expect11 = np.sum(x11, axis=axis11, keepdims=keep_dims11)
+    expect11 = np.sum(x11, axis=tuple(set(axis11)), keepdims=keep_dims11)
     diff11 = abs(output[11].asnumpy() - expect11)
     error11 = np.ones(shape=expect11.shape) * 1.0e-5
     assert np.all(diff11 < error11)