[AutoParallel]Fix insert error for the mirror

mindspore/ccsrc/frontend/parallel/device_manager.cc

@@ -236,7 +236,7 @@ RankList DeviceManager::GetDeviceListBetweenStage() const {
   if (stage_num < 1) {
     MS_LOG(EXCEPTION) << "Stage num got " << stage_num << ", expected a positive integer.";
   }
-  auto device_num = parallel::ParallelContext::GetInstance()->device_num();
+  auto device_num = DeviceNum();
   auto per_stage_rank_num = device_num / stage_num;
   for (int64_t i = 0; i < stage_num; ++i) {
     rank_list.push_back(rank_id + per_stage_rank_num * (i - stage_id));

mindspore/ccsrc/frontend/parallel/pipeline_transformer/pipeline_transformer.cc

@@ -179,16 +179,7 @@ void PipelineTransformer::LabelMicroBatch() {
 }
 
 void PipelineTransformer::CreateForwardGroup() {
-  std::vector<int64_t> rank_list;
-  auto rank_id = g_device_manager->global_rank();
-  auto stage_id = g_device_manager->stage_id();
-  auto stage_num = g_device_manager->stage_num();
-  if (stage_num < 1) {
-    MS_LOG(EXCEPTION) << "Stage num got " << stage_num << ", expected a positive integer.";
-  }
-  for (int64_t i = 0; i < stage_num; ++i) {
-    rank_list.push_back(rank_id + per_stage_rank_num_ * (i - stage_id));
-  }
+  std::vector<int64_t> rank_list = g_device_manager->GetDeviceListBetweenStage();
   auto dev_list = g_device_manager->CreateDeviceListByRankList(rank_list);
   auto g = g_device_manager->CreateGroup(rank_list);
   auto g_back_name = g.name() + BACKWARD;

mindspore/ccsrc/frontend/parallel/step_parallel.cc

@@ -208,20 +208,12 @@ void InsertNode(const Operator &op, const CNodePtr &node, size_t index, const An
                 const FuncGraphPtr &root = nullptr) {
   // insert new node before the node
   FuncGraphManagerPtr manager = func_graph->manager();
-  auto node_user_map = manager->node_users();
   MS_EXCEPTION_IF_NULL(manager);
   ScopePtr scope = node->scope();
   MS_EXCEPTION_IF_NULL(scope);
   std::vector<AnfNodePtr> node_input;
-  AnfNodePtr pre_node_ = pre_node;
   if (root && !param_name.empty()) {
-    TypePtr next_node_dtype = FindChildCastWithFP32ToFP16(node, node_user_map);
-    if (next_node_dtype) {
-      MS_LOG(INFO) << "Inserting Cast from float32 to float16 for node " << node->fullname_with_scope() << " for saving"
-                   << " communication.";
-      pre_node_ = CreateFP16Cast(node, pre_node, next_node_dtype);
-    }
-    node_input = CreateMirrorInput(root, op, pre_node_, instance_name, param_name);
+    node_input = CreateMirrorInput(root, op, pre_node, instance_name, param_name);
   } else {
     node_input = CreateInput(op, pre_node, instance_name);
   }
@@ -1572,7 +1564,16 @@ static void InsertAllGatherOp(const FuncGraphPtr &root, const std::string &group
     allgather = ReplaceNode(op, cast_node, graph, PARALLEL_OPTIMIZER_ALLGATHER_NOT_COMPUTE, param_name, root);
     MS_LOG(INFO) << "Parallel optimizer is applied before Cast for " << param_name;
   } else {
-    InsertNode(op, cnode, IntToSize(res.second), node, graph, PARALLEL_OPTIMIZER_ALLGATHER_NOT_COMPUTE, param_name,
+    auto pre_node = node;
+    AnfNodePtr pre_node_ = node;
+    auto node_user_map = manager->node_users();
+    TypePtr next_node_dtype = FindChildCastWithFP32ToFP16(cnode, node_user_map);
+    if (next_node_dtype) {
+      MS_LOG(INFO) << "Inserting Cast from float32 to float16 for node " << node->fullname_with_scope() << " for saving"
+                   << " communication.";
+      pre_node_ = CreateFP16Cast(cnode, pre_node, next_node_dtype);
+    }
+    InsertNode(op, cnode, IntToSize(res.second), pre_node_, graph, PARALLEL_OPTIMIZER_ALLGATHER_NOT_COMPUTE, param_name,
                root);
     allgather = cnode->input(IntToSize(res.second))->cast<CNodePtr>();
     MS_LOG(INFO) << "Parallel optimizer is applied before " << GetPrimName(cnode) << " for " << param_name;
@@ -3188,7 +3189,7 @@ static void InsertAllReduceForNormValue(const AnfNodePtr &res_node) {
   }
 }
 
-AnfNodePtr FindPrimitiveWithAtrribute(const AnfNodePtr &node_ptr, const NodeUsersMap &node_users_map, uint32_t limits) {
+AnfNodePtr FindExpanDimsWIthGradScale(const AnfNodePtr &node_ptr, const NodeUsersMap &node_users_map, uint32_t limits) {
   std::queue<AnfNodePtr> visited;
   AnfNodePtr queue_node = nullptr;
   CNodePtr cnode = nullptr;
@@ -3239,7 +3240,7 @@ static void InsertDivAndAllReduceForNorm(const NodeUsersMap &node_user_map, cons
     if (cnode->in_forward_flag()) {
       continue;
     }
-    expand_dims_node = FindPrimitiveWithAtrribute(cnode, node_user_map, MAX_BFS_DEPTH);
+    expand_dims_node = FindExpanDimsWIthGradScale(cnode, node_user_map, MAX_BFS_DEPTH);
     if (!expand_dims_node) {
       continue;
     }

mindspore/ccsrc/plugin/device/ascend/hal/device/ascend_stream_assign.cc

@@ -124,8 +124,8 @@ uint32_t GetHcomTaskNum(const CNodePtr &cnode) {
     return kTaskNumPerHcomSendRecvNode;
   }
 
-  MS_EXCEPTION_IF_NULL(parallel::ParallelContext::GetInstance());
-  auto device_num = parallel::ParallelContext::GetInstance()->device_num();
+  MS_EXCEPTION_IF_NULL(parallel::g_device_manager);
+  auto device_num = parallel::g_device_manager->DeviceNum();
   auto group_name = common::AnfAlgo::GetNodeAttr<std::string>(cnode, kAttrGroup);
   auto group_info = parallel::g_device_manager->group_info();
   for (const auto &info : group_info) {

tests/ut/python/parallel/test_parallel_optimizer_shared_cast.py

@@ -117,7 +117,7 @@ class TestSharedParameterCast:
         """
         auto_parallel_compile_net("semi_auto_parallel", 8, Net, ((8, 1), (1, 1)), ((8, 1), (1, 1)),
                                   interleaved_batch=1)
-        self.cat_fp16_from_ir(target_count=28)
+        self.cat_fp16_from_ir(target_count=23)
 
     def test_optimizer_fp16_micro_batch(self):
         """
@@ -127,7 +127,7 @@ class TestSharedParameterCast:
         """
         auto_parallel_compile_net("semi_auto_parallel", 8, Net, ((8, 1), (1, 1)), ((8, 1), (1, 1)),
                                   interleaved_batch=2)
-        self.cat_fp16_from_ir(target_count=42)
+        self.cat_fp16_from_ir(target_count=39)
 
     def test_optimizer_fp16_pipeline(self):
         """
@@ -138,7 +138,7 @@ class TestSharedParameterCast:
         auto_parallel_compile_net("semi_auto_parallel", 8, Net, ((8, 1), (1, 1)), ((8, 1), (1, 1)),
                                   interleaved_batch=1,
                                   stages=1, micro_size=1)
-        self.cat_fp16_from_ir(target_count=28)
+        self.cat_fp16_from_ir(target_count=23)
 
     def test_optimizer_fp16_pipeline_micro_batch(self):
         """
@@ -149,4 +149,4 @@ class TestSharedParameterCast:
         auto_parallel_compile_net("semi_auto_parallel", 8, Net, ((8, 1), (1, 1)), ((8, 1), (1, 1)),
                                   interleaved_batch=2,
                                   stages=1, micro_size=1)
-        self.cat_fp16_from_ir(target_count=42)
+        self.cat_fp16_from_ir(target_count=39)

tests/ut/python/parallel/test_pipeline_split.py

@@ -419,7 +419,7 @@ class TestPipelineSplitWithNoOptimizer:
         self.cat_fp16_from_ir(pattern='grad_mirror_MirrorMicroStepOperator',
                               target_count=2)
         self.cat_fp16_from_ir(pattern='Cast(',
-                              target_count=16)
+                              target_count=14)
 
     def test_pipeline_with_micro_batch_no_parallel_optimizer(self):
         """
@@ -438,4 +438,4 @@ class TestPipelineSplitWithNoOptimizer:
         self.cat_fp16_from_ir(pattern='grad_mirror_MirrorMicroStepOperator',
                               target_count=2)
         self.cat_fp16_from_ir(pattern='Cast(',
-                              target_count=28)
+                              target_count=26)