diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/nms_with_mask_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/nms_with_mask_cpu_kernel.cc
index 73c5e18adef..f91f7447c1c 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/nms_with_mask_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/nms_with_mask_cpu_kernel.cc
@@ -19,10 +19,10 @@
 
 namespace mindspore {
 namespace kernel {
-size_t NmsRoundUpPower2(int v) {
+uint32_t NmsRoundUpPower2(int v) {
   constexpr uint32_t ONE = 1, TWO = 2, FOUR = 4, EIGHT = 8, SIXTEEN = 16;
   v--;
-  size_t value = IntToSize(v);
+  uint32_t value = IntToUint(v);
   value |= value >> ONE;
   value |= value >> TWO;
   value |= value >> FOUR;
@@ -216,7 +216,7 @@ void NMSWithMaskCPUKernel<T>::InitInputOutputSize(const CNodePtr &kernel_node) {
   CPUKernel::InitInputOutputSize(kernel_node);
   auto input_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
   num_input_ = SizeToInt(input_shape[0]);  //  Get N values in  [N, 5] data.
-  ceil_power_2 = NmsRoundUpPower2(num_input_);
+  ceil_power_2 = static_cast<size_t>(NmsRoundUpPower2(num_input_));
 
   workspace_size_list_.push_back(ceil_power_2 * sizeof(T));                           //  data buff
   workspace_size_list_.push_back(ceil_power_2 * sizeof(int));                         //  index buff
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/random_choice_with_mask_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/random_choice_with_mask_cpu_kernel.cc
index 0e2e716148e..b9e568b8015 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/random_choice_with_mask_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/random_choice_with_mask_cpu_kernel.cc
@@ -118,12 +118,12 @@ void RandomChoiceWithMaskCPUKernel::InitInputOutputSize(const CNodePtr &kernel_n
   CPUKernel::InitInputOutputSize(kernel_node);
 
   GetInputTotalCount(dims_, &input_total_count, input_dim_size);
-  size_t temp_output_length = count_ > 0 ? count_ : input_total_count;
+  int temp_output_length = count_ > 0 ? count_ : input_total_count;
 
   workspace_size_list_.push_back(IntToSize(input_total_count) * sizeof(int));
-  workspace_size_list_.push_back(temp_output_length * sizeof(int));
-  workspace_size_list_.push_back(temp_output_length * sizeof(int));
-  workspace_size_list_.push_back(temp_output_length * IntToSize(input_dim_size) * sizeof(int));
+  workspace_size_list_.push_back(IntToSize(temp_output_length) * sizeof(int));
+  workspace_size_list_.push_back(IntToSize(temp_output_length) * sizeof(int));
+  workspace_size_list_.push_back(IntToSize(temp_output_length) * IntToSize(input_dim_size) * sizeof(int));
 }
 
 bool RandomChoiceWithMaskCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
diff --git a/mindspore/ccsrc/backend/kernel_compiler/cpu/roi_align_grad_cpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/cpu/roi_align_grad_cpu_kernel.cc
index f202469333d..8d3384101a7 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/cpu/roi_align_grad_cpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/cpu/roi_align_grad_cpu_kernel.cc
@@ -23,8 +23,8 @@ template <typename T, typename U>
 void AtomicAddTask(T *const address, const T val) {
   auto *address_as_ull = reinterpret_cast<U *>(address);
   U old = *address_as_ull;
-  U assumed;
-  T desired;
+  U assumed = U(0);
+  T desired = T(0);
   do {
     assumed = old;
     T *assumed_t = reinterpret_cast<T *>(&assumed);
diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index a80c7d828e2..faff37fac32 100755
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -6097,6 +6097,7 @@ class SearchSorted(PrimitiveWithInfer):
         validator.check_tensors_dtypes_same_and_valid(args, mstype.number_type, self.name)
         return mstype.tensor_type(mstype.int32) if self.out_int32 else mstype.tensor_type(mstype.int64)
 
+
 class TensorScatterMax(PrimitiveWithInfer):
     """
     By comparing the value at the position indicated by the index in input_x with the value in the update,
diff --git a/model_zoo/official/nlp/textcnn/src/dataset.py b/model_zoo/official/nlp/textcnn/src/dataset.py
index 192e7ffa9e9..1398b6c6d6a 100644
--- a/model_zoo/official/nlp/textcnn/src/dataset.py
+++ b/model_zoo/official/nlp/textcnn/src/dataset.py
@@ -129,7 +129,7 @@ class MovieReview(DataProcessor):
         self.Pos = []
         self.Neg = []
         for filename in self.files:
-            with codecs.open(filename, 'r') as f:
+            with codecs.open(filename, 'r', 'Latin1') as f:
                 ff = f.read()
             with codecs.open(filename, 'w', 'utf-8') as file_object:
                 file_object.write(ff)