diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/adam_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/adam_cpu_kernel.cc
index cb0f32d720..33767f560e 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/adam_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/adam_cpu_kernel.cc
@@ -23,7 +23,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 template <typename T>
 void AdamCPUKernel::LaunchAdam(T *var, T *m, T *v, float lr, float beta1, float beta2, float epsilon, const T *gradient,
                                size_t start, size_t end) {
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.cc
index 0f77a362a1..754e38ca0f 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.cc
@@ -22,7 +22,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 template <typename S, typename T>
 void Cast(const S *in, T *out, size_t start, size_t end) {
   for (size_t i = start; i < end; i++) {
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.h
index 5de831af45..996086a571 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.h
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/cast_cpu_kernel.h
@@ -23,7 +23,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 class CastCPUKernel : public CPUKernel {
  public:
   CastCPUKernel() = default;
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/equal_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/equal_cpu_kernel.cc
index d040c4de47..1bd8904926 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/equal_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/equal_cpu_kernel.cc
@@ -95,6 +95,5 @@ void EqualCPUKernel::CheckParam(const CNodePtr &kernel_node) {
     }
   }
 }
-
 }  // namespace kernel
 }  // namespace mindspore
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/map_cache_idx_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/map_cache_idx_cpu_kernel.cc
index f0a962e07f..c815aff9fb 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/map_cache_idx_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/map_cache_idx_cpu_kernel.cc
@@ -81,11 +81,9 @@ void MapCacheIdxCPUKernel::InitKernel(const CNodePtr &kernel_node) {
   MS_EXCEPTION_IF_NULL(kernel_node);
   node_ = kernel_node;
   auto hashmap_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
-
   if (hashmap_shape.size() != 2) {
     MS_LOG(EXCEPTION) << "Dimension of HashMap must be 2, (n, 4)";
   }
-
   hashmap_length_ = hashmap_shape[0];
   dtype_ = AnfAlgo::GetPrevNodeOutputInferDataType(kernel_node, 0);
 }
@@ -121,7 +119,6 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
   auto output_old_emb_idx = reinterpret_cast<T *>(outputs[1]->addr);
   auto output_miss_emb_idx = reinterpret_cast<T *>(outputs[2]->addr);
   auto output_swap_cache_idx = reinterpret_cast<T *>(outputs[3]->addr);
-
   std::vector<T> miss_idx;
   size_t miss_count = 0;
   float total_count = 0;
@@ -134,9 +131,7 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
       output_cache_idx[i] = -1;
       continue;
     }
-
     T tmp_entry = HashFunc(key, hashmap_length_);
-
     size_t count = 1;
     count_size += 1;
     while ((!hashmap[tmp_entry].IsEmpty() && !hashmap[tmp_entry].IsKey(key))) {
@@ -147,7 +142,6 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
       }
       count += 1;
     }
-
     total_count += count;
     if (hashmap[tmp_entry].IsEmpty()) {
       miss_idx.emplace_back(i);
@@ -163,10 +157,8 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
   MS_LOG(INFO) << "Miss count: " << miss_count;
   MS_LOG(INFO) << "Avg search count: " << total_count / count_size;
   MS_LOG(INFO) << "Cache hit rate: " << hit_count / count_size;
-
   float total_insert_count = 0;
   float total_delete_count = 0;
-
   // swap hash map
   for (size_t i = 0; i < miss_count; ++i) {
     T emb_idx = output_miss_emb_idx[i];
@@ -180,11 +172,9 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
       }
       tag_count++;
     }
-
     hashmap[entry].key = emb_idx;
     hashmap[entry].step = step_[0];
     hashmap[entry].tag = tag_count;
-
     T tmp_entry = (entry + 1) % hashmap_length_;
     size_t delete_count = 1;
     while (hashmap[tmp_entry].IsEmpty() || hashmap[tmp_entry].IsUsing(step_[0])) {
@@ -195,7 +185,6 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
       }
       delete_count++;
     }
-
     output_swap_cache_idx[i] = hashmap[tmp_entry].value;
     output_old_emb_idx[i] = hashmap[tmp_entry].key;
     hashmap[entry].value = output_swap_cache_idx[i];
@@ -204,19 +193,15 @@ void MapCacheIdxCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs,
     total_delete_count += (compress_count + delete_count);
     total_insert_count += tag_count;
   }
-
   MS_LOG(INFO) << "Insert count: " << total_insert_count / miss_count;
   MS_LOG(INFO) << "Delete count: " << total_delete_count / miss_count;
-
   // update step
   step_[0] += 1;
-
   // update cache idx
   for (size_t i = 0; i < miss_count; ++i) {
     int idx = miss_idx[i];
     output_cache_idx[idx] = output_swap_cache_idx[i];
   }
-
   std::vector<size_t> out_shape;
   out_shape.emplace_back(miss_count);
   std::vector<TypeId> dtypes;
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/fused_batch_norm_gard_cpu_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/fused_batch_norm_gard_cpu_kernel.h
index 2688191d34..f1717d2732 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/fused_batch_norm_gard_cpu_kernel.h
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/fused_batch_norm_gard_cpu_kernel.h
@@ -54,7 +54,6 @@ MS_REG_CPU_KERNEL(FusedBatchNormGradCPU,
                     .AddOutputAttr(kNumberTypeFloat32)
                     .AddOutputAttr(kNumberTypeFloat32),
                   FusedBatchNormGradCPUKernel)
-
 }  // namespace kernel
 }  // namespace mindspore
 
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/unique_cpu_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/cpu/unique_cpu_kernel.h
index be46c08537..8dfd17027e 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/unique_cpu_kernel.h
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/unique_cpu_kernel.h
@@ -63,6 +63,9 @@ class UniqueCPUKernel : public CPUKernel {
 
   template <typename DataType>
   static size_t BucketId(DataType data, size_t bucket_num) {
+    if (bucket_num < 1) {
+      return static_cast<size_t>(data);
+    }
     return static_cast<size_t>(data) % bucket_num;
   }
 
@@ -73,6 +76,9 @@ class UniqueCPUKernel : public CPUKernel {
     MS_EXCEPTION_IF_NULL(params->input_);
     MS_EXCEPTION_IF_NULL(each_bucket_size);
     size_t bucket_num = each_bucket_size->size();
+    if (params->input_size_ < 1) {
+      return;
+    }
     for (IndexType i = 0; i < params->input_size_; ++i) {
       auto bucket_id = BucketId(params->input_[i], bucket_num);
       each_bucket_size->at(bucket_id)++;
@@ -131,6 +137,9 @@ class UniqueCPUKernel : public CPUKernel {
     MS_EXCEPTION_IF_NULL(segment->input_);
     std::vector<IndexType> bucket_data_num(segment->thread_num_, 0);
     auto bucket_size = buckets.size();
+    if (segment->input_size_ < 1) {
+      return;
+    }
     for (IndexType i = 0; i < segment->input_size_; ++i) {
       DataType data = segment->input_[i];
       auto bucket_id = BucketId(data, segment->thread_num_);
@@ -233,6 +242,9 @@ class UniqueCPUKernel : public CPUKernel {
     MS_EXCEPTION_IF_NULL(output);
     MS_EXCEPTION_IF_NULL(inverse_idx);
     IndexType j = 0;
+    if (params->input_size_ < 1) {
+      return;
+    }
     if (params->need_sort_) {
       for (IndexType i = 0; i < params->input_size_; ++i) {
         input_idx[i] = i;
@@ -296,6 +308,9 @@ class UniqueCPUKernel : public CPUKernel {
     MS_EXCEPTION_IF_NULL(bucket->workspace_idx_);
     MS_EXCEPTION_IF_NULL(result);
     MS_EXCEPTION_IF_NULL(result->inverse_idx_);
+    if (bucket->input_size_ < 1) {
+      return;
+    }
     for (IndexType i = 0; i < bucket->input_size_; ++i) {
       auto origin_idx = bucket->workspace_idx_[i];
       if (origin_idx >= 0 && origin_idx < result->input_size_) {
diff --git a/mindspore/ccsrc/backend/session/session_basic.cc b/mindspore/ccsrc/backend/session/session_basic.cc
index 2b85cab3d1..3f10ea0ae9 100644
--- a/mindspore/ccsrc/backend/session/session_basic.cc
+++ b/mindspore/ccsrc/backend/session/session_basic.cc
@@ -155,8 +155,10 @@ BaseRef CreateNodeOutputTensors(const AnfNodePtr &anf, const KernelGraphPtr &gra
     MS_EXCEPTION_IF_NULL(cnode);
     VectorRef ret;
     for (size_t i = 1; i < cnode->inputs().size(); ++i) {
-      auto out = CreateNodeOutputTensors(cnode->input(i), graph, input_tensors, tensor_to_node);
-      ret.push_back(out);
+      if (!AnfAlgo::CheckPrimitiveType(cnode->input(i), prim::kPrimControlDepend)) {
+        auto out = CreateNodeOutputTensors(cnode->input(i), graph, input_tensors, tensor_to_node);
+        ret.push_back(out);
+      }
     }
     return ret;
   }
diff --git a/mindspore/ccsrc/runtime/device/ascend/ascend_kernel_runtime.cc b/mindspore/ccsrc/runtime/device/ascend/ascend_kernel_runtime.cc
index 524cb6296e..784fb62328 100644
--- a/mindspore/ccsrc/runtime/device/ascend/ascend_kernel_runtime.cc
+++ b/mindspore/ccsrc/runtime/device/ascend/ascend_kernel_runtime.cc
@@ -798,7 +798,6 @@ bool AscendKernelRuntime::DestroyHccl() {
     MS_LOG(ERROR) << "Dynamic Shape Hccl Finalize Failed";
   }
   HcclResult res = hcom_destroy();
-
   if (res != HCCL_SUCCESS) {
     MS_LOG(ERROR) << "Hccl destroy failed";
     return false;
diff --git a/mindspore/ccsrc/runtime/device/ascend/ascend_stream_assign.cc b/mindspore/ccsrc/runtime/device/ascend/ascend_stream_assign.cc
index 6b446b135d..241485b357 100644
--- a/mindspore/ccsrc/runtime/device/ascend/ascend_stream_assign.cc
+++ b/mindspore/ccsrc/runtime/device/ascend/ascend_stream_assign.cc
@@ -1832,7 +1832,6 @@ void AscendStreamAssign::AdjustAtomicAddrCleanOrder(const NotNull<KernelGraphPtr
 
   graph_ptr->set_execution_order(update_orders);
 }
-
 }  // namespace ascend
 }  // namespace device
 }  // namespace mindspore
diff --git a/mindspore/ccsrc/runtime/device/kernel_runtime.cc b/mindspore/ccsrc/runtime/device/kernel_runtime.cc
index ee2f4aa043..f2cb051ea1 100644
--- a/mindspore/ccsrc/runtime/device/kernel_runtime.cc
+++ b/mindspore/ccsrc/runtime/device/kernel_runtime.cc
@@ -1,4 +1,3 @@
-
 /**
  * Copyright 2019 Huawei Technologies Co., Ltd
  *
diff --git a/mindspore/ccsrc/vm/graph_partition.cc b/mindspore/ccsrc/vm/graph_partition.cc
index d98970124c..0eac22774e 100644
--- a/mindspore/ccsrc/vm/graph_partition.cc
+++ b/mindspore/ccsrc/vm/graph_partition.cc
@@ -268,9 +268,11 @@ void AddSegmentDependency(const FuncGraphPtr &graph, const std::string &default_
       node_inputs.insert(node_inputs.end(), ctrl_inputs->second.begin(), ctrl_inputs->second.end());
     }
     GraphSegmentPtr node_segment{nullptr};
-    auto node_iter = node_to_segment.find(node);
-    if (node_iter != node_to_segment.end()) {
-      node_segment = node_iter->second;
+    if (!IsPrimitiveCNode(cnode, prim::kPrimControlDepend)) {
+      auto node_iter = node_to_segment.find(node);
+      if (node_iter != node_to_segment.end()) {
+        node_segment = node_iter->second;
+      }
     }
     for (auto &input : node_inputs) {
       if (node_segment != nullptr && !node_segment->is_cut_ && input->isa<CNode>()) {