!4064 fix pass fail when ReduceMin's axis set with one int number

Merge pull request !4064 from huanghui/reduce-min-fission-pass

mindspore/ccsrc/backend/optimizer/ascend/ir_fission/reduce_min_fission.cc

@@ -32,7 +32,7 @@ CNodePtr CreateReduceMin(const FuncGraphPtr &graph, const AnfNodePtr &input, con
   return reduce_min;
 }
 
-bool NeedOptmize(const TypeId &dtype, const std::vector<size_t> &shape, const std::vector<int> &axis) {
+bool NeedOptimize(const TypeId &dtype, const std::vector<size_t> &shape, const std::vector<int> &axis) {
   if (dtype != kNumberTypeFloat32) {
     MS_LOG(INFO) << "ReduceMin's input Dtype is not float32, no need optimize!";
     return false;
@@ -84,7 +84,7 @@ std::vector<size_t> GetInferShape(const std::vector<size_t> &shape, const std::v
   for (size_t item = 0; item < shape.size(); ++item) {
     if (axis_first.end() != std::find(axis_first.begin(), axis_first.end(), item)) {
       if (keep_dims) {
-        // If keep_dims is true, curretn dimesion set to 1
+        // If keep_dims is true, current dimension set to 1
         shape_first.push_back(1);
       }
     } else {
@@ -110,28 +110,31 @@ const AnfNodePtr ReduceMinFission::Process(const FuncGraphPtr &graph, const AnfN
   CheckCNodeInputSize(cnode, 2);
   auto shape = AnfAlgo::GetPrevNodeOutputInferShape(cnode, 0);
   auto dtype = AnfAlgo::GetPrevNodeOutputInferDataType(cnode, 0);
-  if (!AnfAlgo::HasNodeAttr(kAttrAxis, cnode)) {
-    MS_LOG(INFO) << "ReduceMin has no axis, no need optimize!";
+  auto prim = AnfAlgo::GetCNodePrimitive(cnode);
+  MS_EXCEPTION_IF_NULL(prim);
+  if (!prim->HasAttr(kAttrAxis) || !prim->HasAttr(kAttrKeepDims)) {
+    MS_LOG(INFO) << "ReduceMin has no axis or keep_dims, no need optimize!";
     return nullptr;
   }
-  auto axis = AnfAlgo::GetNodeAttr<std::vector<int>>(cnode, kAttrAxis);
-  if (!AnfAlgo::HasNodeAttr(kAttrKeepDims, cnode)) {
-    MS_LOG(INFO) << "ReduceMin has no keep_dims, no need optimize!";
+  auto axis_value = prim->GetAttr(kAttrAxis);
+  MS_EXCEPTION_IF_NULL(axis_value);
+  if (!axis_value->isa<ValueSequeue>()) {
     return nullptr;
   }
+  auto axis = AnfAlgo::GetNodeAttr<std::vector<int>>(cnode, kAttrAxis);
   auto keep_dims = AnfAlgo::GetNodeAttr<bool>(cnode, kAttrKeepDims);
 
-  if (!NeedOptmize(dtype, shape, axis)) {
+  if (!NeedOptimize(dtype, shape, axis)) {
     MS_LOG(INFO) << "No need optimize for this ReduceMin. " << cnode->DebugString();
     return nullptr;
   }
 
   // Create reduce_min1
   CNodePtr reduce_min1 = CreateReduceMin(graph, cnode->input(1), cnode);
-  std::vector<int> axis_fisrt = CalFirstAxis(shape, axis);
-  std::vector<size_t> shape_first = GetInferShape(shape, axis_fisrt, keep_dims);
+  std::vector<int> axis_first = CalFirstAxis(shape, axis);
+  std::vector<size_t> shape_first = GetInferShape(shape, axis_first, keep_dims);
   AnfAlgo::SetOutputInferTypeAndShape({dtype}, {shape_first}, reduce_min1.get());
-  AnfAlgo::SetNodeAttr(kAttrAxis, MakeValue(axis_fisrt), reduce_min1);
+  AnfAlgo::SetNodeAttr(kAttrAxis, MakeValue(axis_first), reduce_min1);
 
   // Create reduce_min2
   CNodePtr reduce_min2 = CreateReduceMin(graph, reduce_min1, cnode);