diff --git a/mindspore/ccsrc/minddata/dataset/api/execute.cc b/mindspore/ccsrc/minddata/dataset/api/execute.cc
index e1ee279dd7..c999398321 100644
--- a/mindspore/ccsrc/minddata/dataset/api/execute.cc
+++ b/mindspore/ccsrc/minddata/dataset/api/execute.cc
@@ -226,6 +226,7 @@ Execute::~Execute() {
 Status Execute::operator()(const mindspore::MSTensor &input, mindspore::MSTensor *output) {
   // Validate input tensor
   CHECK_FAIL_RETURN_UNEXPECTED(input.DataSize() > 0, "Input Tensor has no data.");
+  CHECK_FAIL_RETURN_UNEXPECTED(output != nullptr, "Output Tensor can not be nullptr.");
   CHECK_FAIL_RETURN_UNEXPECTED(ValidateDevice(), "Device Type should be 'Ascend310' or 'CPU'.");
 
   // Parse TensorTransform transforms_ into TensorOperation ops_
@@ -311,6 +312,8 @@ Status Execute::operator()(const mindspore::MSTensor &input, mindspore::MSTensor
 Status Execute::operator()(const std::vector<MSTensor> &input_tensor_list, std::vector<MSTensor> *output_tensor_list) {
   // Validate input tensor
   CHECK_FAIL_RETURN_UNEXPECTED(!input_tensor_list.empty(), "Input Tensor is not valid.");
+  CHECK_FAIL_RETURN_UNEXPECTED(output_tensor_list != nullptr, "Output Tensor can not be nullptr.");
+  output_tensor_list->clear();
   for (auto &tensor : input_tensor_list) {
     CHECK_FAIL_RETURN_UNEXPECTED(tensor.DataSize() > 0, "Input Tensor has no data.");
   }
diff --git a/mindspore/ccsrc/minddata/dataset/text/kernels/sentence_piece_tokenizer_op.cc b/mindspore/ccsrc/minddata/dataset/text/kernels/sentence_piece_tokenizer_op.cc
index dc9db992dd..3f87339af9 100644
--- a/mindspore/ccsrc/minddata/dataset/text/kernels/sentence_piece_tokenizer_op.cc
+++ b/mindspore/ccsrc/minddata/dataset/text/kernels/sentence_piece_tokenizer_op.cc
@@ -55,7 +55,7 @@ SentencePieceTokenizerOp::SentencePieceTokenizerOp(const std::string &model_path
 Status SentencePieceTokenizerOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) {
   IO_CHECK(input, output);
   if (!model_status_.IsOk()) {
-    return model_status_;
+    return Status(StatusCode::kMDUnexpectedError, __LINE__, __FILE__, model_status_.GetErrDescription());
   }
 
   if (input->Rank() != 0 || input->type() != DataType::DE_STRING) {
diff --git a/mindspore/dataset/callback/ds_callback.py b/mindspore/dataset/callback/ds_callback.py
index d395290733..e675f922f9 100644
--- a/mindspore/dataset/callback/ds_callback.py
+++ b/mindspore/dataset/callback/ds_callback.py
@@ -238,6 +238,12 @@ class WaitedDSCallback(Callback, DSCallback):
         return c_cb
 
     def end(self, run_context):
+        """
+        Internal method, release the wait if training is ended.
+
+        Args:
+          run_context: Include some information of the model.
+        """
         self.epoch_end(run_context)
         self.step_end(run_context)
         self.training_ended = True
diff --git a/mindspore/dataset/engine/__init__.py b/mindspore/dataset/engine/__init__.py
index ac104f232d..8c530d0c5f 100644
--- a/mindspore/dataset/engine/__init__.py
+++ b/mindspore/dataset/engine/__init__.py
@@ -30,6 +30,7 @@ from .graphdata import GraphData, SamplingStrategy, OutputFormat
 from .iterators import *
 from .samplers import *
 from .serializer_deserializer import compare, deserialize, serialize, show
+from ..utils import imshow_det_bbox
 
 __all__ = ["CelebADataset", "Cifar100Dataset", "Cifar10Dataset", "CLUEDataset", "CocoDataset", "CSVDataset",
            "GeneratorDataset", "GraphData", "ImageFolderDataset", "ManifestDataset", "MindDataset", "MnistDataset",
@@ -37,4 +38,4 @@ __all__ = ["CelebADataset", "Cifar100Dataset", "Cifar10Dataset", "CLUEDataset",
            "DistributedSampler", "PKSampler", "RandomSampler", "SequentialSampler", "SubsetRandomSampler",
            "WeightedRandomSampler", "SubsetSampler",
            "DatasetCache", "DSCallback", "Schema", "WaitedDSCallback", "compare", "deserialize",
-           "serialize", "show", "zip"]
+           "imshow_det_bbox", "serialize", "show", "zip"]