fix codex and code check

mindspore/ccsrc/minddata/dataset/api/execute.cc

@@ -673,7 +673,8 @@ Status Execute::Run(const std::vector<std::shared_ptr<dataset::Execute>> &data_g
 extern "C" {
 // ExecuteRun_C has C-linkage specified, but returns user-defined type 'mindspore::Status' which is incompatible with C
 void ExecuteRun_C(const std::vector<std::shared_ptr<dataset::Execute>> &data_graph,
-                  std::vector<mindspore::MSTensor> &inputs, std::vector<mindspore::MSTensor> *outputs, Status *s) {
+                  const std::vector<mindspore::MSTensor> &inputs, std::vector<mindspore::MSTensor> *outputs,
+                  Status *s) {
   Status ret = Execute::Run(data_graph, inputs, outputs);
   if (s == nullptr) {
     return;

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/allpass_biquad_ir.h

@@ -36,7 +36,7 @@ class AllpassBiquadOperation : public TensorOperation {
  public:
   AllpassBiquadOperation(int32_t sample_rate, float central_freq, float Q);
 
-  ~AllpassBiquadOperation() = default;
+  ~AllpassBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/amplitude_to_db_ir.h

@@ -34,7 +34,7 @@ class AmplitudeToDBOperation : public TensorOperation {
  public:
   AmplitudeToDBOperation(ScaleType stype, float ref_value, float amin, float top_db);
 
-  ~AmplitudeToDBOperation();
+  ~AmplitudeToDBOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/angle_ir.h

@@ -36,7 +36,7 @@ class AngleOperation : public TensorOperation {
  public:
   AngleOperation();
 
-  ~AngleOperation() = default;
+  ~AngleOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/band_biquad_ir.h

@@ -36,7 +36,7 @@ class BandBiquadOperation : public TensorOperation {
  public:
   BandBiquadOperation(int32_t sample_rate, float central_freq, float Q, bool noise);
 
-  ~BandBiquadOperation() = default;
+  ~BandBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/bandpass_biquad_ir.h

@@ -36,7 +36,7 @@ class BandpassBiquadOperation : public TensorOperation {
  public:
   BandpassBiquadOperation(int32_t sample_rate, float central_freq, float Q, bool const_skirt_gain);
 
-  ~BandpassBiquadOperation() = default;
+  ~BandpassBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/bandreject_biquad_ir.h

@@ -36,7 +36,7 @@ class BandrejectBiquadOperation : public TensorOperation {
  public:
   BandrejectBiquadOperation(int32_t sample_rate, float central_freq, float Q);
 
-  ~BandrejectBiquadOperation() = default;
+  ~BandrejectBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/bass_biquad_ir.h

@@ -36,7 +36,7 @@ class BassBiquadOperation : public TensorOperation {
  public:
   BassBiquadOperation(int32_t sample_rate, float gain, float central_freq, float Q);
 
-  ~BassBiquadOperation() = default;
+  ~BassBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/biquad_ir.h

@@ -36,7 +36,7 @@ class BiquadOperation : public TensorOperation {
  public:
   BiquadOperation(float b0, float b1, float b2, float a0, float a1, float a2);
 
-  ~BiquadOperation() = default;
+  ~BiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/complex_norm_ir.h

@@ -33,7 +33,7 @@ class ComplexNormOperation : public TensorOperation {
  public:
   explicit ComplexNormOperation(float power);
 
-  ~ComplexNormOperation();
+  ~ComplexNormOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/compute_deltas_ir.h

@@ -32,7 +32,7 @@ class ComputeDeltasOperation : public TensorOperation {
  public:
   ComputeDeltasOperation(int32_t win_length, BorderType pad_mode);
 
-  ~ComputeDeltasOperation() = default;
+  ~ComputeDeltasOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/contrast_ir.h

@@ -34,7 +34,7 @@ class ContrastOperation : public TensorOperation {
  public:
   explicit ContrastOperation(float enhancement_amount);
 
-  ~ContrastOperation() = default;
+  ~ContrastOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/db_to_amplitude_ir.h

@@ -35,7 +35,7 @@ class DBToAmplitudeOperation : public TensorOperation {
  public:
   DBToAmplitudeOperation(float ref, float power);
 
-  ~DBToAmplitudeOperation() = default;
+  ~DBToAmplitudeOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/dc_shift_ir.h

@@ -34,7 +34,7 @@ class DCShiftOperation : public TensorOperation {
  public:
   DCShiftOperation(float shift, float limiter_gain);
 
-  ~DCShiftOperation() = default;
+  ~DCShiftOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/deemph_biquad_ir.h

@@ -35,7 +35,7 @@ class DeemphBiquadOperation : public TensorOperation {
  public:
   explicit DeemphBiquadOperation(int32_t sample_rate);
 
-  ~DeemphBiquadOperation() = default;
+  ~DeemphBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/detect_pitch_frequency_ir.h

@@ -37,7 +37,7 @@ class DetectPitchFrequencyOperation : public TensorOperation {
   DetectPitchFrequencyOperation(int32_t sample_rate, float frame_time, int32_t win_length, int32_t freq_low,
                                 int32_t freq_high);
 
-  ~DetectPitchFrequencyOperation() = default;
+  ~DetectPitchFrequencyOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/dither_ir.h

@@ -35,7 +35,7 @@ class DitherOperation : public TensorOperation {
  public:
   DitherOperation(DensityFunction density_function, bool noise_shaping);
 
-  ~DitherOperation() = default;
+  ~DitherOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/equalizer_biquad_ir.h

@@ -35,7 +35,7 @@ class EqualizerBiquadOperation : public TensorOperation {
  public:
   EqualizerBiquadOperation(int32_t sample_rate, float center_freq, float gain, float Q);
 
-  ~EqualizerBiquadOperation() = default;
+  ~EqualizerBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/fade_ir.h

@@ -33,7 +33,7 @@ class FadeOperation : public TensorOperation {
  public:
   FadeOperation(int32_t fade_in_len, int32_t fade_out_len, FadeShape fade_shape);
 
-  ~FadeOperation() = default;
+  ~FadeOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/flanger_ir.h

@@ -37,7 +37,7 @@ class FlangerOperation : public TensorOperation {
   explicit FlangerOperation(int32_t sample_rate, float delay, float depth, float regen, float width, float speed,
                             float phase, Modulation modulation, Interpolation interpolation);
 
-  ~FlangerOperation() = default;
+  ~FlangerOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/frequency_masking_ir.h

@@ -32,7 +32,7 @@ class FrequencyMaskingOperation : public TensorOperation {
  public:
   FrequencyMaskingOperation(bool iid_masks, int32_t frequency_mask_param, int32_t mask_start, float mask_value);
 
-  ~FrequencyMaskingOperation();
+  ~FrequencyMaskingOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 
@@ -43,9 +43,9 @@ class FrequencyMaskingOperation : public TensorOperation {
   Status to_json(nlohmann::json *out_json) override;
 
  private:
+  bool iid_masks_;
   int32_t frequency_mask_param_;
   int32_t mask_start_;
-  bool iid_masks_;
   float mask_value_;
 };  // class FrequencyMaskingOperation
 }  // namespace audio

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/gain_ir.h

@@ -35,7 +35,7 @@ class GainOperation : public TensorOperation {
  public:
   explicit GainOperation(float gain_db);
 
-  ~GainOperation() = default;
+  ~GainOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/highpass_biquad_ir.h

@@ -36,7 +36,7 @@ class HighpassBiquadOperation : public TensorOperation {
  public:
   HighpassBiquadOperation(int32_t sample_rate, float cutoff_freq, float Q);
 
-  ~HighpassBiquadOperation() = default;
+  ~HighpassBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/lfilter_ir.h

@@ -36,7 +36,7 @@ class LFilterOperation : public TensorOperation {
  public:
   LFilterOperation(const std::vector<float> &a_coeffs, const std::vector<float> &b_coeffs, bool clamp);
 
-  ~LFilterOperation() = default;
+  ~LFilterOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/lowpass_biquad_ir.h

@@ -37,7 +37,7 @@ class LowpassBiquadOperation : public TensorOperation {
  public:
   LowpassBiquadOperation(int32_t sample_rate, float cutoff_freq, float Q);
 
-  ~LowpassBiquadOperation() = default;
+  ~LowpassBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/magphase_ir.h

@@ -34,7 +34,7 @@ class MagphaseOperation : public TensorOperation {
  public:
   explicit MagphaseOperation(float power);
 
-  ~MagphaseOperation() = default;
+  ~MagphaseOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/mu_law_decoding_ir.h

@@ -32,7 +32,7 @@ class MuLawDecodingOperation : public TensorOperation {
  public:
   explicit MuLawDecodingOperation(int32_t quantization_channels);
 
-  ~MuLawDecodingOperation();
+  ~MuLawDecodingOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/mu_law_encoding_ir.h

@@ -32,7 +32,7 @@ class MuLawEncodingOperation : public TensorOperation {
  public:
   explicit MuLawEncodingOperation(int32_t quantization_channels);
 
-  ~MuLawEncodingOperation();
+  ~MuLawEncodingOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/overdrive_ir.h

@@ -37,7 +37,7 @@ class OverdriveOperation : public TensorOperation {
  public:
   explicit OverdriveOperation(float gain, float color);
 
-  ~OverdriveOperation() = default;
+  ~OverdriveOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/phaser_ir.h

@@ -38,7 +38,7 @@ class PhaserOperation : public TensorOperation {
   PhaserOperation(int32_t sample_rate, float gain_in, float gain_out, float delay_ms, float decay, float mod_speed,
                   bool sinusoidal);
 
-  ~PhaserOperation() = default;
+  ~PhaserOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/riaa_biquad_ir.h

@@ -36,7 +36,7 @@ class RiaaBiquadOperation : public TensorOperation {
  public:
   explicit RiaaBiquadOperation(int32_t sample_rate);
 
-  ~RiaaBiquadOperation() = default;
+  ~RiaaBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/sliding_window_cmn_ir.h

@@ -32,7 +32,7 @@ class SlidingWindowCmnOperation : public TensorOperation {
  public:
   SlidingWindowCmnOperation(int32_t cmn_window, int32_t min_cmn_window, bool center, bool norm_vars);
 
-  ~SlidingWindowCmnOperation();
+  ~SlidingWindowCmnOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/spectral_centroid_ir.h

@@ -33,7 +33,7 @@ class SpectralCentroidOperation : public TensorOperation {
   SpectralCentroidOperation(int32_t sample_rate, int32_t n_fft, int32_t win_length, int32_t hop_length, int32_t pad,
                             WindowType window);
 
-  ~SpectralCentroidOperation() = default;
+  ~SpectralCentroidOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/spectrogram_ir.h

@@ -33,7 +33,7 @@ class SpectrogramOperation : public TensorOperation {
   SpectrogramOperation(int32_t n_fft, int32_t win_length, int32_t hop_length, int32_t pad, WindowType window,
                        float power, bool normalized, bool center, BorderType pad_mode, bool onesided);
 
-  ~SpectrogramOperation() = default;
+  ~SpectrogramOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/time_masking_ir.h

@@ -32,7 +32,7 @@ class TimeMaskingOperation : public TensorOperation {
  public:
   TimeMaskingOperation(bool iid_masks, int32_t time_mask_param, int32_t mask_start, float mask_value);
 
-  ~TimeMaskingOperation();
+  ~TimeMaskingOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/time_stretch_ir.h

@@ -32,7 +32,7 @@ class TimeStretchOperation : public TensorOperation {
  public:
   TimeStretchOperation(float hop_length, int n_freq, float fixed_rate);
 
-  ~TimeStretchOperation();
+  ~TimeStretchOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/treble_biquad_ir.h

@@ -37,7 +37,7 @@ class TrebleBiquadOperation : public TensorOperation {
  public:
   TrebleBiquadOperation(int32_t sample_rate, float gain, float central_freq, float Q);
 
-  ~TrebleBiquadOperation() = default;
+  ~TrebleBiquadOperation() override = default;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/ir/kernels/vol_ir.h

@@ -33,7 +33,7 @@ class VolOperation : public TensorOperation {
  public:
   VolOperation(float gain, GainType gain_type);
 
-  ~VolOperation();
+  ~VolOperation() override;
 
   std::shared_ptr<TensorOp> Build() override;
 

mindspore/ccsrc/minddata/dataset/audio/kernels/audio_utils.cc

@@ -36,7 +36,7 @@ Status ComplexAngle(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor
   TensorShape input_shape = input->shape();
   TensorShape out_shape({input_shape[0], input_shape[1], input_shape[2]});
   std::vector<T> phase(input_shape[0] * input_shape[1] * input_shape[2]);
-  int ind = 0;
+  size_t ind = 0;
 
   for (auto itr = input->begin<T>(); itr != input->end<T>(); itr++, ind++) {
     auto x = (*itr);
@@ -64,7 +64,7 @@ Status ComplexAbs(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor>
   TensorShape input_shape = input->shape();
   TensorShape out_shape({input_shape[0], input_shape[1], input_shape[2]});
   std::vector<T> abs(input_shape[0] * input_shape[1] * input_shape[2]);
-  int ind = 0;
+  size_t ind = 0;
   for (auto itr = input->begin<T>(); itr != input->end<T>(); itr++, ind++) {
     T x = (*itr);
     itr++;
@@ -96,7 +96,7 @@ Status Polar(const std::shared_ptr<Tensor> &abs, const std::shared_ptr<Tensor> &
   TensorShape input_shape = abs->shape();
   TensorShape out_shape({input_shape[0], input_shape[1], input_shape[2], 2});
   std::vector<T> complex_vec(input_shape[0] * input_shape[1] * input_shape[2] * 2);
-  int ind = 0;
+  size_t ind = 0;
   auto itr_abs = abs->begin<T>();
   auto itr_angle = angle->begin<T>();
 
@@ -118,7 +118,7 @@ Status Polar(const std::shared_ptr<Tensor> &abs, const std::shared_ptr<Tensor> &
 /// \param[out] output - Complex tensor, <channel, freq, time, complex=2>.
 /// \return Status return code.
 template <typename T>
-Status PadComplexTensor(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int length, int dim) {
+Status PadComplexTensor(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, int length, size_t dim) {
   TensorShape input_shape = input->shape();
   std::vector<int64_t> pad_shape_vec = {input_shape[0], input_shape[1], input_shape[2], input_shape[3]};
   pad_shape_vec[dim] += static_cast<int64_t>(length);
@@ -128,7 +128,7 @@ Status PadComplexTensor(const std::shared_ptr<Tensor> &input, std::shared_ptr<Te
   auto itr_input = input->begin<T>();
   int64_t input_cnt = 0;
   /*lint -e{446} ind is modified in the body of the for loop */
-  for (int ind = 0; ind < static_cast<int>(in_vect.size()); ind++) {
+  for (auto ind = 0; ind < static_cast<int>(in_vect.size()); ind++) {
     in_vect[ind] = (*itr_input);
     input_cnt = (input_cnt + 1) % (input_shape[2] * input_shape[3]);
     itr_input++;
@@ -174,7 +174,7 @@ Status Phase(const std::shared_ptr<Tensor> &angle_0, const std::shared_ptr<Tenso
   }
 
   // concat phase time 0
-  int64_t ind = 0;
+  size_t ind = 0;
   auto itr_p0 = phase_time0->begin<T>();
   (void)phase.insert(phase.begin(), (*itr_p0));
   itr_p0++;
@@ -374,7 +374,7 @@ Status Mag(const std::shared_ptr<Tensor> &abs_0, const std::shared_ptr<Tensor> &
   std::vector<T> mag(mag_shape[0] * mag_shape[1] * mag_shape[2]);
   auto itr_abs_0 = abs_0->begin<T>();
   auto itr_abs_1 = abs_1->begin<T>();
-  for (int ind = 0; itr_abs_0 != abs_0->end<T>(); itr_abs_0++, itr_abs_1++, ind++) {
+  for (auto ind = 0; itr_abs_0 != abs_0->end<T>(); itr_abs_0++, itr_abs_1++, ind++) {
     mag[ind] = alphas[ind % mag_shape[2]] * (*itr_abs_1) + (1 - alphas[ind % mag_shape[2]]) * (*itr_abs_0);
   }
   std::shared_ptr<Tensor> mag_tensor;
@@ -385,7 +385,7 @@ Status Mag(const std::shared_ptr<Tensor> &abs_0, const std::shared_ptr<Tensor> &
 
 template <typename T>
 Status TimeStretch(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output, float rate,
-                   std::shared_ptr<Tensor> phase_advance) {
+                   const std::shared_ptr<Tensor> &phase_advance) {
   // pack <..., freq, time, complex>
   TensorShape input_shape = input->shape();
   TensorShape toShape({input->Size() / (input_shape[-1] * input_shape[-2] * input_shape[-3]), input_shape[-3],
@@ -399,11 +399,11 @@ Status TimeStretch(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *outpu
   std::vector<dsize_t> time_steps_0, time_steps_1;
   std::vector<T> alphas;
   for (int ind = 0;; ind++) {
-    auto val = ind * rate;
+    T val = static_cast<float>(ind) * rate;
     if (val >= input_shape[-2]) {
       break;
     }
-    int val_int = static_cast<int>(val);
+    auto val_int = static_cast<dsize_t>(val);
     time_steps_0.push_back(val_int);
     time_steps_1.push_back(val_int + 1);
     alphas.push_back(fmod(val, 1));
@@ -458,7 +458,7 @@ Status TimeStretch(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *outpu
 }
 
 Status TimeStretch(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, float rate, float hop_length,
-                   float n_freq) {
+                   int32_t n_freq) {
   std::shared_ptr<Tensor> phase_advance;
   switch (input->type().value()) {
     case DataType::DE_FLOAT32:
@@ -502,15 +502,15 @@ Status Dct(std::shared_ptr<Tensor> *output, int n_mfcc, int n_mels, NormMode nor
   TensorShape dct_shape({n_mels, n_mfcc});
   Tensor::CreateEmpty(dct_shape, DataType(DataType::DE_FLOAT32), output);
   auto iter = (*output)->begin<float>();
-  const float sqrt_2 = 1 / sqrt(2);
-  float sqrt_2_n_mels = sqrt(2.0 / n_mels);
+  const float sqrt_2 = 1 / sqrt(2.0f);
+  auto sqrt_2_n_mels = static_cast<float>(sqrt(2.0 / n_mels));
   for (int i = 0; i < n_mels; i++) {
     for (int j = 0; j < n_mfcc; j++) {
       // calculate temp:
       // 1. while norm = None, use 2*cos(PI*(i+0.5)*j/n_mels)
       // 2. while norm = Ortho, divide the first row by sqrt(2),
       //    then using sqrt(2.0 / n_mels)*cos(PI*(i+0.5)*j/n_mels)
-      float temp = PI / n_mels * (i + 0.5) * j;
+      auto temp = static_cast<float>(PI / n_mels * (i + 0.5) * j);
       temp = cos(temp);
       if (norm == NormMode::kOrtho) {
         if (j == 0) {
@@ -566,11 +566,11 @@ Status MaskAlongAxis(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tenso
       std::to_string(mask_start) + ", 'mask_width' " + std::to_string(mask_width) + " and length " +
       std::to_string(input_shape[check_dim_ind]));
 
-  int32_t cell_size = input->type().SizeInBytes();
+  size_t cell_size = input->type().SizeInBytes();
 
   if (axis == 1) {
     // freq
-    for (int ind = 0; ind < input->Size() / input_shape[-2] * mask_width; ind++) {
+    for (auto ind = 0; ind < input->Size() / input_shape[-2] * mask_width; ind++) {
       int block_num = ind / (mask_width * input_shape[-1]);
       auto start_pos = ind % (mask_width * input_shape[-1]) + mask_start * input_shape[-1] +
                        input_shape[-1] * input_shape[-2] * block_num;
@@ -616,7 +616,7 @@ template <typename T>
 Status Norm(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, float power) {
   // calculate the output dimension
   auto input_size = input->shape().AsVector();
-  int32_t dim_back = static_cast<int32_t>(input_size.back());
+  auto dim_back = input_size.back();
   RETURN_IF_NOT_OK(
     ValidateTensorShape("ComplexNorm", input->IsComplex(), "<..., complex=2>", std::to_string(dim_back)));
   input_size.pop_back();
@@ -657,8 +657,8 @@ Status ComplexNorm(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor>
 }
 
 template <typename T>
-float sgn(T val) {
-  return static_cast<float>(static_cast<T>(0) < val) - static_cast<float>(val < static_cast<T>(0));
+inline float sgn(T val) {
+  return (val > 0) ? 1 : ((val < 0) ? -1 : 0);
 }
 
 template <typename T>
@@ -810,10 +810,10 @@ Status Fade(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *outpu
             int32_t fade_out_len, FadeShape fade_shape) {
   RETURN_IF_NOT_OK(Tensor::CreateFromTensor(input, output));
   const TensorShape input_shape = input->shape();
-  int32_t waveform_length = static_cast<int32_t>(input_shape[-1]);
+  auto waveform_length = static_cast<int32_t>(input_shape[-1]);
   RETURN_IF_NOT_OK(ValidateNoGreaterThan("Fade", "fade_in_len", fade_in_len, "length of waveform", waveform_length));
   RETURN_IF_NOT_OK(ValidateNoGreaterThan("Fade", "fade_out_len", fade_out_len, "length of waveform", waveform_length));
-  int32_t num_waveform = static_cast<int32_t>(input->Size() / waveform_length);
+  auto num_waveform = static_cast<int32_t>(input->Size() / waveform_length);
   TensorShape toShape = TensorShape({num_waveform, waveform_length});
   RETURN_IF_NOT_OK((*output)->Reshape(toShape));
   TensorPtr fade_in;
@@ -960,7 +960,7 @@ Status GenerateWaveTable(std::shared_ptr<Tensor> *output, const DataType &type,
   RETURN_UNEXPECTED_IF_NULL(output);
   CHECK_FAIL_RETURN_UNEXPECTED(table_size > 0,
                                "table_size must be more than 0, but got: " + std::to_string(table_size));
-  int32_t phase_offset = static_cast<int32_t>(phase / PI / 2 * table_size + 0.5);
+  auto phase_offset = static_cast<int32_t>(phase / PI / 2 * table_size + 0.5);
   // get the offset of the i-th
   std::vector<int32_t> point;
   for (auto i = 0; i < table_size; i++) {
@@ -982,7 +982,7 @@ Status GenerateWaveTable(std::shared_ptr<Tensor> *output, const DataType &type,
       // change phase
       *iter = point[i] * 2.0 / table_size;
       // get complete offset
-      int32_t value = static_cast<int>(4 * point[i] / table_size);
+      auto value = static_cast<int>(4 * point[i] / table_size);
       // change the value of the square wave according to the number of complete offsets
       if (value == 0) {
         *iter = *iter + 0.5;
@@ -1027,7 +1027,7 @@ Status ReadWaveFile(const std::string &wav_file_dir, std::vector<float> *wavefor
   std::ifstream in(file_path.ToString(), std::ios::in | std::ios::binary);
   CHECK_FAIL_RETURN_UNEXPECTED(in.is_open(), "Invalid file, failed to open waveform file: " + file_path.ToString() +
                                                ", make sure the file not damaged or permission denied.");
-  WavHeader *header = new WavHeader();
+  auto *header = new WavHeader();
   in.read(reinterpret_cast<char *>(header), sizeof(WavHeader));
   *sample_rate = header->sample_rate;
   float bytes_per_sample = header->bits_per_sample / 8;
@@ -1180,7 +1180,7 @@ Status SlidingWindowCmnHelper(const std::shared_ptr<Tensor> &input, std::shared_
   RETURN_IF_NOT_OK(
     input->Reshape(TensorShape({static_cast<int>(first_index / (num_frames * num_feats)), num_frames, num_feats})));
 
-  int32_t num_channels = static_cast<int32_t>(input->shape()[0]);
+  auto num_channels = static_cast<int32_t>(input->shape()[0]);
   TensorPtr cmn_waveform;
   RETURN_IF_NOT_OK(
     Tensor::CreateEmpty(TensorShape({num_channels, num_frames, num_feats}), input->type(), &cmn_waveform));
@@ -1227,7 +1227,7 @@ Status Pad(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output
   RETURN_IF_NOT_OK(ValidateNonNegative("Pad", "pad_right", pad_right));
   TensorShape input_shape = input->shape();
   int32_t wave_length = input_shape[-1];
-  int32_t num_wavs = static_cast<int32_t>(input->Size() / wave_length);
+  auto num_wavs = static_cast<int32_t>(input->Size() / wave_length);
   TensorShape to_shape = TensorShape({num_wavs, wave_length});
   RETURN_IF_NOT_OK(input->Reshape(to_shape));
   int32_t pad_length = wave_length + pad_left + pad_right;
@@ -1721,7 +1721,7 @@ Status SpectralCentroidImpl(const std::shared_ptr<Tensor> &input, std::shared_pt
       }
     }
     specgram.push_back(tmp);
-    specgram_sum.push_back(specgram[k].colwise().sum());
+    specgram_sum.emplace_back(specgram[k].colwise().sum());
   }
   for (int k = 0; k < k_num; k++) {
     for (int i = 0; i < channals; ++i) {
@@ -1729,7 +1729,7 @@ Status SpectralCentroidImpl(const std::shared_ptr<Tensor> &input, std::shared_pt
         tmp(i, j) = freqs_r(i, 0) * specgram[k](i, j);
       }
     }
-    specgram_result.push_back((tmp).colwise().sum());
+    specgram_result.emplace_back((tmp).colwise().sum());
   }
   auto itr_output = output_tensor->begin<T>();
   for (int k = 0; k < k_num; k++) {

mindspore/ccsrc/minddata/dataset/audio/kernels/audio_utils.h

@@ -58,8 +58,8 @@ Status AmplitudeToDB(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tenso
   RETURN_IF_NOT_OK(input->Reshape(to_shape));
 
   std::vector<T> max_val;
-  int step = to_shape[-3] * input_shape[-2] * input_shape[-1];
-  int cnt = 0;
+  uint64_t step = to_shape[-3] * input_shape[-2] * input_shape[-1];
+  uint64_t cnt = 0;
   T temp_max = std::numeric_limits<T>::lowest();
   for (auto itr = input->begin<T>(); itr != input->end<T>(); itr++) {
     // do clamp
@@ -75,10 +75,10 @@ Status AmplitudeToDB(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tenso
   }
 
   if (!std::isnan(top_db)) {
-    int ind = 0;
+    uint64_t ind = 0;
     for (auto itr = input->begin<T>(); itr != input->end<T>(); itr++, ind++) {
-      float lower_bound = max_val[ind / step] - top_db;
-      *itr = std::max((*itr), static_cast<T>(lower_bound));
+      T lower_bound = max_val[ind / step] - top_db;
+      *itr = std::max((*itr), lower_bound);
     }
   }
   RETURN_IF_NOT_OK(input->Reshape(input_shape));
@@ -149,10 +149,9 @@ Status Contrast(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *o
   RETURN_IF_NOT_OK(Tensor::CreateEmpty(output_shape, input->type(), &out));
   auto itr_out = out->begin<T>();
   for (auto itr_in = input->begin<T>(); itr_in != input->end<T>(); itr_in++) {
-    T temp1, temp2 = 0;
     // PI / 2 is half of the constant PI
-    temp1 = static_cast<T>(*itr_in) * (PI / TWO);
-    temp2 = enhancement_amount_value * std::sin(temp1 * 4);
+    T temp1 = static_cast<T>(*itr_in) * (PI / TWO);
+    T temp2 = enhancement_amount_value * std::sin(temp1 * 4);
     *itr_out = std::sin(temp1 + temp2);
     itr_out++;
   }
@@ -244,8 +243,8 @@ Status LFilter(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *ou
   TensorShape input_shape = input->shape();
   TensorShape toShape({input->Size() / input_shape[-1], input_shape[-1]});
   input->Reshape(toShape);
-  auto shape_0 = input->shape()[0];
-  auto shape_1 = input->shape()[1];
+  auto shape_0 = static_cast<size_t>(input->shape()[0]);
+  auto shape_1 = static_cast<size_t>(input->shape()[1]);
   std::vector<T> signal;
   std::shared_ptr<Tensor> out;
   std::vector<T> out_vect(shape_0 * shape_1);
@@ -328,11 +327,8 @@ Status LFilter(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *ou
 ///     The spacing between the points is (end - start) / (n - 1).
 /// \return Status return code.
 template <typename T>
-Status Linspace(std::shared_ptr<Tensor> *output, T start, T end, int n) {
-  if (start > end) {
-    std::string err = "Linspace: input param end must be greater than start.";
-    RETURN_STATUS_UNEXPECTED(err);
-  }
+Status Linspace(std::shared_ptr<Tensor> *output, T start, T end, int32_t n) {
+  RETURN_IF_NOT_OK(ValidateNoGreaterThan("Linspace", "start", start, "end", end));
   int hundred = 100;
   n = std::isnan(n) ? hundred : n;
   CHECK_FAIL_RETURN_UNEXPECTED(n >= 0, "Linspace: input param n must be non-negative.");
@@ -443,7 +439,7 @@ Status SpectralCentroid(const std::shared_ptr<Tensor> &input, std::shared_ptr<Te
 /// \param output: Tensor after stretch in time domain.
 /// \return Status code.
 Status TimeStretch(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output, float rate, float hop_length,
-                   float n_freq);
+                   int32_t n_freq);
 
 /// \brief Stretch STFT in time at a given rate, without changing the pitch.
 /// \param[in] input Tensor of shape <..., freq, time, 2>.

mindspore/ccsrc/minddata/dataset/audio/kernels/lfilter_op.cc

@@ -29,20 +29,20 @@ Status LFilterOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<
   } else if (input->type() == DataType(DataType::DE_FLOAT64)) {
     std::vector<double> a_coeffs_double;
     std::vector<double> b_coeffs_double;
-    for (int i = 0; i < a_coeffs_.size(); i++) {
+    for (auto i = 0; i < a_coeffs_.size(); i++) {
       a_coeffs_double.push_back(static_cast<double>(a_coeffs_[i]));
     }
-    for (int i = 0; i < b_coeffs_.size(); i++) {
+    for (auto i = 0; i < b_coeffs_.size(); i++) {
       b_coeffs_double.push_back(static_cast<double>(b_coeffs_[i]));
     }
     return LFilter(input, output, a_coeffs_double, b_coeffs_double, clamp_);
   } else {
     std::vector<float16> a_coeffs_float16;
     std::vector<float16> b_coeffs_float16;
-    for (int i = 0; i < a_coeffs_.size(); i++) {
+    for (auto i = 0; i < a_coeffs_.size(); i++) {
       a_coeffs_float16.push_back(static_cast<float16>(a_coeffs_[i]));
     }
-    for (int i = 0; i < b_coeffs_.size(); i++) {
+    for (auto i = 0; i < b_coeffs_.size(); i++) {
       b_coeffs_float16.push_back(static_cast<float16>(b_coeffs_[i]));
     }
     return LFilter(input, output, a_coeffs_float16, b_coeffs_float16, clamp_);

mindspore/ccsrc/minddata/dataset/audio/kernels/lfilter_op.h

@@ -29,18 +29,18 @@ namespace dataset {
 
 class LFilterOp : public TensorOp {
  public:
-  LFilterOp(std::vector<float> a_coeffs, std::vector<float> b_coeffs, bool clamp)
+  LFilterOp(const std::vector<float> &a_coeffs, const std::vector<float> &b_coeffs, bool clamp)
       : a_coeffs_(a_coeffs), b_coeffs_(b_coeffs), clamp_(clamp) {}
 
   ~LFilterOp() override = default;
 
   void Print(std::ostream &out) const override {
     out << Name() << ": a_coeffs: ";
-    for (int i = 0; i < a_coeffs_.size(); i++) {
+    for (auto i = 0; i < a_coeffs_.size(); i++) {
       out << a_coeffs_[i] << " ";
     }
     out << "b_coeffs: ";
-    for (int i = 0; i < b_coeffs_.size(); i++) {
+    for (auto i = 0; i < b_coeffs_.size(); i++) {
       out << b_coeffs_[i] << " ";
     }
     out << "clamp: " << clamp_ << std::endl;

mindspore/ccsrc/minddata/dataset/audio/kernels/time_stretch_op.cc

@@ -68,7 +68,7 @@ Status TimeStretchOp::OutputShape(const std::vector<TensorShape> &inputs, std::v
     std::vector<dsize_t> s_vec = s.AsVector();
     s_vec.pop_back();
     s_vec.pop_back();
-    s_vec.push_back(std::ceil(s[-2] / fixed_rate_));
+    s_vec.push_back(std::ceil(s[-2] / static_cast<dsize_t>(fixed_rate_)));
     // push back complex
     s_vec.push_back(2);
     outputs.emplace_back(TensorShape(s_vec));

mindspore/ccsrc/minddata/dataset/callback/callback_manager.h

@@ -74,8 +74,8 @@ class CallbackManager {
   Status StepEnd(const CallbackParam &);
 
  private:
-  bool enabled_;   // flag to enable callback, if false, all functions would return immediately
-  DatasetOp *op_;  // back pointer to DatasetOp, raw pointer to avoid circular ownership
+  bool enabled_;             // flag to enable callback, if false, all functions would return immediately
+  DatasetOp *op_ = nullptr;  // back pointer to DatasetOp, raw pointer to avoid circular ownership
   std::vector<std::shared_ptr<DSCallback>> callbacks_;  // list of callbacks the  DatasetOp needs to call
   std::vector<size_t> begin_indices_;
   std::vector<size_t> end_indices_;

mindspore/ccsrc/minddata/dataset/callback/ds_callback.h

@@ -34,7 +34,7 @@ class DSCallback {
   explicit DSCallback(int32_t step_size = 1) : step_size_(step_size) {}
 
   /// \brief Destructor
-  ~DSCallback() = default;
+  virtual ~DSCallback() = default;
 
   /// \brief actual callback function for begin, needs to be overridden in the derived class
   /// \param cb_param, callback parameter passed in from DatasetOp when calling the callback

mindspore/ccsrc/minddata/dataset/callback/py_ds_callback.h

@@ -42,7 +42,7 @@ class PyDSCallback : public DSCallback {
         epoch_end_needed_(false),
         step_end_needed_(false) {}
 
-  ~PyDSCallback() = default;
+  ~PyDSCallback() override = default;
 
   void SetBegin(const py::function &f);
   void SetEnd(const py::function &f);
@@ -128,5 +128,4 @@ class PyDSCallback : public DSCallback {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_PY_DS_CALLBACK_H

mindspore/ccsrc/minddata/dataset/core/config_manager.h

@@ -63,7 +63,7 @@ class ConfigManager {
 
   // Another debug print helper.  Converts the print info to a string for you.
   // @return The string version of the debug print
-  std::string ToString() {
+  std::string ToString() const {
     std::stringstream ss;
     ss << *this;
     return ss.str();
@@ -178,7 +178,7 @@ class ConfigManager {
 
   // getter function
   // @return The interval of monitor sampling
-  int32_t monitor_sampling_interval() const { return monitor_sampling_interval_; }
+  uint32_t monitor_sampling_interval() const { return monitor_sampling_interval_; }
 
   // setter function
   // @param auto_num_workers - whether assign threads to each op automatically
@@ -200,13 +200,13 @@ class ConfigManager {
 
   // getter function
   // @return The timeout DSWaitedCallback would wait for before raising an error
-  int32_t callback_timeout() const { return callback_timout_; }
+  uint32_t callback_timeout() const { return callback_timout_; }
 
   // getter function
   // E.g. 0 would corresponds to a 1:1:1 ratio of num_worker among leaf batch and map.
   // please refer to AutoWorkerPass for detail on what each option is.
   // @return The experimental config used by AutoNumWorker, each 1 refers to a different setup configuration
-  uint8_t get_auto_worker_config() { return auto_worker_config_; }
+  uint8_t get_auto_worker_config() const { return auto_worker_config_; }
 
   // setter function
   // E.g. set the value of 0 would corresponds to a 1:1:1 ratio of num_worker among leaf batch and map.
@@ -220,7 +220,7 @@ class ConfigManager {
 
   // getter function
   // @return - Flag to indicate whether shared memory for multi-processing is enabled
-  bool enable_shared_mem() { return enable_shared_mem_; }
+  bool enable_shared_mem() const { return enable_shared_mem_; }
 
   // setter function
   // @param offload - To enable automatic offloading of dataset ops
@@ -228,7 +228,7 @@ class ConfigManager {
 
   // getter function
   // @return - Flag to indicate whether automatic offloading is enabled for the dataset
-  bool get_auto_offload() { return auto_offload_; }
+  bool get_auto_offload() const { return auto_offload_; }
 
   // setter function
   // @param enable - To enable autotune
@@ -236,11 +236,11 @@ class ConfigManager {
 
   // getter function
   // @return - Flag to indicate whether autotune is enabled
-  bool enable_autotune() { return enable_autotune_; }
+  bool enable_autotune() const { return enable_autotune_; }
 
   // getter function
   // @return - autotune interval in steps
-  int64_t autotune_interval() { return autotune_interval_; }
+  int64_t autotune_interval() const { return autotune_interval_; }
 
   // setter function
   // @param interval - autotune interval in steps
@@ -277,5 +277,4 @@ class ConfigManager {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_CORE_CONFIG_MANAGER_H_

mindspore/ccsrc/minddata/dataset/core/device_tensor.h

@@ -32,7 +32,7 @@ class DeviceTensor : public Tensor {
  public:
   DeviceTensor(const TensorShape &shape, const DataType &type);
 
-  ~DeviceTensor() {}
+  ~DeviceTensor() override = default;
 
   Status SetAttributes(uint8_t *data_ptr, const uint32_t &dataSize, const uint32_t &width, const uint32_t &widthStride,
                        const uint32_t &height, const uint32_t &heightStride);

mindspore/ccsrc/minddata/dataset/core/tensor.cc

@@ -85,10 +85,12 @@ Tensor &Tensor::operator=(Tensor &&other) noexcept {
     data_ = other.GetMutableBuffer();
     data_end_ = other.data_end_;
     data_allocator_ = std::move(other.data_allocator_);
+    yuv_shape_ = other.yuv_shape_;
     other.Invalidate();
   }
   return *this;
 }
+
 Status Tensor::CreateEmpty(const TensorShape &shape, const DataType &type, TensorPtr *out) {
   CHECK_FAIL_RETURN_UNEXPECTED(shape.known(), "Invalid shape.");
   CHECK_FAIL_RETURN_UNEXPECTED(type != DataType::DE_UNKNOWN, "Invalid data type.");
@@ -111,6 +113,7 @@ Status Tensor::CreateEmpty(const TensorShape &shape, const DataType &type, Tenso
   }
   return Status::OK();
 }
+
 Status Tensor::CreateFromMemory(const TensorShape &shape, const DataType &type, const uchar *src, TensorPtr *out) {
   RETURN_IF_NOT_OK(CreateEmpty(shape, type, out));
   if (src != nullptr && out != nullptr) {
@@ -680,7 +683,7 @@ Status Tensor::to_json(nlohmann::json *out_json) {
     RETURN_IF_NOT_OK(to_json_convert<double>(&args));
   } else if (type_ == DataType::DE_STRING) {
     std::vector<std::string> data_out;
-    for (auto it = this->begin<std::string_view>(); it != this->end<std::string_view>(); it++) {
+    for (auto it = this->begin<std::string_view>(); it != this->end<std::string_view>(); ++it) {
       data_out.emplace_back(*it);
     }
     args["data"] = data_out;
@@ -739,7 +742,8 @@ Status Tensor::from_json(nlohmann::json op_params, std::shared_ptr<Tensor> *tens
 }
 
 template <typename T>
-Status Tensor::from_json_convert(nlohmann::json json_data, TensorShape shape, std::shared_ptr<Tensor> *tensor) {
+Status Tensor::from_json_convert(const nlohmann::json &json_data, const TensorShape &shape,
+                                 std::shared_ptr<Tensor> *tensor) {
   std::vector<T> data = json_data;
   RETURN_IF_NOT_OK(CreateFromVector(data, shape, tensor));
   return Status::OK();

mindspore/ccsrc/minddata/dataset/core/tensor.h

@@ -225,7 +225,8 @@ class Tensor {
   static Status from_json(nlohmann::json op_params, std::shared_ptr<Tensor> *tensor);
 
   template <typename T>
-  static Status from_json_convert(nlohmann::json json_data, TensorShape shape, std::shared_ptr<Tensor> *tensor);
+  static Status from_json_convert(const nlohmann::json &json_data, const TensorShape &shape,
+                                  std::shared_ptr<Tensor> *tensor);
 
   /// Get item located at `index`, caller needs to provide the type.
   /// \tparam T
@@ -481,6 +482,9 @@ class Tensor {
     ~TensorIterator() = default;
 
     TensorIterator<T> &operator=(const TensorIterator<T> &rhs) {
+      if (this == &rhs) {
+        return *this;
+      }
       ptr_ = rhs.ptr_;
       return *this;
     }
@@ -565,7 +569,7 @@ class Tensor {
     using pointer = std::string_view *;
     using reference = std::string_view &;
 
-    explicit TensorIterator(uchar *data = nullptr, dsize_t index = 0) {
+    explicit TensorIterator(const uchar *data = nullptr, dsize_t index = 0) {
       data_ = reinterpret_cast<const char *>(data);
       index_ = index;
     }
@@ -795,7 +799,7 @@ inline Status Tensor::CreateFromVector<std::string>(const std::vector<std::strin
   *out = std::allocate_shared<Tensor>(*alloc, TensorShape({static_cast<dsize_t>(items.size())}),
                                       DataType(DataType::DE_STRING));
   CHECK_FAIL_RETURN_UNEXPECTED(out != nullptr, "Allocate memory failed.");
-  if (items.size() == 0) {
+  if (items.empty()) {
     if (shape.known()) {
       return (*out)->Reshape(shape);
     }

mindspore/ccsrc/minddata/dataset/engine/connector.h

@@ -195,7 +195,7 @@ class Connector {
   int32_t expect_consumer_;
 
   // The index to the queues_ where the next data should be popped.
-  int32_t pop_from_;
+  size_t pop_from_;
 
   int32_t num_producers_;
   int32_t num_consumers_;

mindspore/ccsrc/minddata/dataset/engine/execution_tree.h

@@ -64,23 +64,28 @@ class ExecutionTree {
       ++ind_;
       return *this;
     }  // prefix ++ overload
+
     Iterator operator++(int) {
       Iterator it = *this;
       it.ind_ = ind_;
       ind_++;
       return it;
     }  // post-fix ++ overload
+
     Iterator &operator--() {
       --ind_;
       return *this;
     }  // prefix -- overload
+
     Iterator operator--(int) {
       Iterator it = *this;
       it.ind_ = ind_;
       ind_--;
       return it;
-    }                                                 // post-fix -- overload
+    }  // post-fix -- overload
+
     DatasetOp &operator*() { return *nodes_[ind_]; }  // dereference operator
+
     std::shared_ptr<DatasetOp> operator->() { return nodes_[ind_]; }
 
     // getter function
@@ -91,10 +96,10 @@ class ExecutionTree {
 
     bool operator!=(const Iterator &rhs) { return nodes_[ind_] != rhs.nodes_[rhs.ind_]; }
 
-    int32_t NumNodes() { return nodes_.size(); }
+    size_t NumNodes() const { return nodes_.size(); }
 
    private:
-    int32_t ind_;                                    // the cur node our Iterator points to
+    size_t ind_;                                     // the cur node our Iterator points to
     std::vector<std::shared_ptr<DatasetOp>> nodes_;  // store the nodes in post order
     void PostOrderTraverse(const std::shared_ptr<DatasetOp> &);
   };
@@ -140,7 +145,7 @@ class ExecutionTree {
   /// \param out - reference to the output stream being overloaded
   /// \param exe_tree - reference to the execution tree to display
   /// \return - the output stream must be returned
-  friend std::ostream &operator<<(std::ostream &out, ExecutionTree &exe_tree) {
+  friend std::ostream &operator<<(std::ostream &out, const ExecutionTree &exe_tree) {
     exe_tree.Print(out);
     return out;
   }
@@ -164,8 +169,10 @@ class ExecutionTree {
   /// \return Status The status code returned
   Status LaunchWorkers(int32_t num_workers, std::function<Status(uint32_t)> func, std::vector<Task *> *worker_tasks,
                        std::string name = "", int32_t operator_id = -1);
+
   Status LaunchWorkers(int32_t num_workers, std::function<Status(uint32_t)> func, std::string name = "",
                        int32_t operator_id = -1);
+
   /// \brief Getter method
   /// \return shared_ptr to the root operator
   std::shared_ptr<DatasetOp> root() const { return root_; }
@@ -233,5 +240,4 @@ class ExecutionTree {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_EXECUTION_TREE_H_

mindspore/ccsrc/minddata/dataset/engine/gnn/edge.h

@@ -28,7 +28,6 @@ namespace mindspore {
 namespace dataset {
 namespace gnn {
 using EdgeType = int8_t;
-using EdgeIdType = int32_t;
 
 class Edge {
  public:
@@ -38,7 +37,8 @@ class Edge {
   // @param WeightType weight - edge weight
   // @param std::shared_ptr<Node> src_node - source node
   // @param std::shared_ptr<Node> dst_node - destination node
-  Edge(EdgeIdType id, EdgeType type, WeightType weight, std::shared_ptr<Node> src_node, std::shared_ptr<Node> dst_node)
+  Edge(EdgeIdType id, EdgeType type, WeightType weight, const std::shared_ptr<Node> &src_node,
+       const std::shared_ptr<Node> &dst_node)
       : id_(id), type_(type), weight_(weight), src_node_(src_node), dst_node_(dst_node) {}
 
   virtual ~Edge() = default;

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data.h

@@ -44,6 +44,9 @@ struct MetaInfo {
 
 class GraphData {
  public:
+  // Destructor
+  virtual ~GraphData() = default;
+
   // Get all nodes from the graph.
   // @param NodeType node_type - type of node
   // @param std::shared_ptr<Tensor> *out - Returned nodes id

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data_client.h

@@ -17,13 +17,13 @@
 #define MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_GNN_GRAPH_DATA_CLIENT_H_
 
 #include <algorithm>
+#include <map>
 #include <memory>
 #include <string>
-#include <map>
 #include <unordered_map>
 #include <unordered_set>
-#include <vector>
 #include <utility>
+#include <vector>
 
 #if !defined(_WIN32) && !defined(_WIN64)
 #include "proto/gnn_graph_data.grpc.pb.h"
@@ -48,7 +48,7 @@ class GraphDataClient : public GraphData {
   // @param int32_t num_workers - number of parallel threads
   GraphDataClient(const std::string &dataset_file, const std::string &hostname, int32_t port);
 
-  ~GraphDataClient();
+  ~GraphDataClient() override;
 
   Status Init() override;
 

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data_impl.cc

@@ -28,7 +28,7 @@ namespace mindspore {
 namespace dataset {
 namespace gnn {
 
-GraphDataImpl::GraphDataImpl(std::string dataset_file, int32_t num_workers, bool server_mode)
+GraphDataImpl::GraphDataImpl(const std::string &dataset_file, int32_t num_workers, bool server_mode)
     : dataset_file_(dataset_file),
       num_workers_(num_workers),
       rnd_(GetRandomDevice()),
@@ -38,7 +38,7 @@ GraphDataImpl::GraphDataImpl(std::string dataset_file, int32_t num_workers, bool
   MS_LOG(INFO) << "num_workers:" << num_workers;
 }
 
-GraphDataImpl::~GraphDataImpl() {}
+GraphDataImpl::~GraphDataImpl() = default;
 
 Status GraphDataImpl::GetAllNodes(NodeType node_type, std::shared_ptr<Tensor> *out) {
   RETURN_UNEXPECTED_IF_NULL(out);

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data_impl.h

@@ -44,9 +44,9 @@ class GraphDataImpl : public GraphData {
   // Constructor
   // @param std::string dataset_file -
   // @param int32_t num_workers - number of parallel threads
-  GraphDataImpl(std::string dataset_file, int32_t num_workers, bool server_mode = false);
+  GraphDataImpl(const std::string &dataset_file, int32_t num_workers, bool server_mode = false);
 
-  ~GraphDataImpl();
+  ~GraphDataImpl() override;
 
   // Get all nodes from the graph.
   // @param NodeType node_type - type of node
@@ -150,11 +150,11 @@ class GraphDataImpl : public GraphData {
   Status GraphInfo(py::dict *out) override;
 #endif
 
-  const std::unordered_map<FeatureType, std::shared_ptr<Feature>> *GetAllDefaultNodeFeatures() {
+  const std::unordered_map<FeatureType, std::shared_ptr<Feature>> *GetAllDefaultNodeFeatures() const {
     return &default_node_feature_map_;
   }
 
-  const std::unordered_map<FeatureType, std::shared_ptr<Feature>> *GetAllDefaultEdgeFeatures() {
+  const std::unordered_map<FeatureType, std::shared_ptr<Feature>> *GetAllDefaultEdgeFeatures() const {
     return &default_edge_feature_map_;
   }
 

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data_server.h

@@ -48,9 +48,9 @@ class GraphDataServer {
   Status ClientRegister(int32_t pid);
   Status ClientUnRegister(int32_t pid);
 
-  enum ServerState state() { return state_; }
+  enum ServerState state() const { return state_; }
 
-  bool IsStopped() {
+  bool IsStopped() const {
     if (state_ == kGdsStopped) {
       return true;
     } else {
@@ -86,7 +86,7 @@ class GraphDataServer {
 #if !defined(_WIN32) && !defined(_WIN64)
 class UntypedCall {
  public:
-  virtual ~UntypedCall() {}
+  virtual ~UntypedCall() = default;
 
   virtual Status operator()() = 0;
 
@@ -112,7 +112,7 @@ class CallData : public UntypedCall {
         handle_request_function_(handle_request_function),
         responder_(&ctx_) {}
 
-  ~CallData() = default;
+  ~CallData() override = default;
 
   static Status EnqueueRequest(ServiceImpl *service_impl, AsyncService *async_service, grpc::ServerCompletionQueue *cq,
                                EnqueueFunction enqueue_function, HandleRequestFunction handle_request_function) {

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_shared_memory.h

@@ -50,9 +50,9 @@ class GraphSharedMemory {
 
   Status GetData(uint8_t *data, int64_t data_len, int64_t offset, int64_t get_data_len);
 
-  key_t memory_key() { return memory_key_; }
+  key_t memory_key() const { return memory_key_; }
 
-  int64_t memory_size() { return memory_size_; }
+  int64_t memory_size() const { return memory_size_; }
 
  private:
   Status SharedMemoryImpl(const int &shmflg);

mindspore/ccsrc/minddata/dataset/engine/gnn/local_node.h

@@ -36,7 +36,7 @@ class LocalNode : public Node {
   // @param NodeType type - node type
   LocalNode(NodeIdType id, NodeType type, WeightType weight);
 
-  ~LocalNode() = default;
+  ~LocalNode() override = default;
 
   // Get the feature of a node
   // @param FeatureType feature_type - type of feature

mindspore/ccsrc/minddata/dataset/engine/ir/cache/dataset_cache.h

@@ -23,17 +23,23 @@
 #include "minddata/dataset/util/status.h"
 
 namespace mindspore::dataset {
-
 class DatasetCache {
  public:
+  virtual ~DatasetCache() = default;
+
   virtual Status Build() = 0;
+
   virtual Status ValidateParams() = 0;
+
   virtual Status CreateCacheOp(int32_t num_workers, int32_t connector_queue_size, std::shared_ptr<SamplerObj> sampler,
                                std::shared_ptr<DatasetOp> *ds) = 0;
+
   virtual Status CreateCacheLookupOp(int32_t num_workers, int32_t connector_queue_size,
                                      std::shared_ptr<SamplerObj> sampler, std::shared_ptr<DatasetOp> *ds) = 0;
+
   virtual Status CreateCacheMergeOp(int32_t num_workers, int32_t connector_queue_size,
                                     std::shared_ptr<DatasetOp> *ds) = 0;
+
   virtual Status to_json(nlohmann::json *out_json) { return Status::OK(); }
 
 #ifndef ENABLE_ANDROID
@@ -41,5 +47,4 @@ class DatasetCache {
 #endif
 };
 }  // namespace mindspore::dataset
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_CACHE_DATASET_CACHE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/cache/dataset_cache_impl.h

@@ -75,7 +75,7 @@ class DatasetCacheImpl : public DatasetCache {
 
   Status to_json(nlohmann::json *out_json) override;
 
-  ~DatasetCacheImpl() = default;
+  ~DatasetCacheImpl() override = default;
 
  private:
   std::shared_ptr<CacheClient> cache_client_;

mindspore/ccsrc/minddata/dataset/engine/ir/cache/pre_built_dataset_cache.h

@@ -37,7 +37,7 @@ class PreBuiltDatasetCache : public DatasetCacheImpl {
     cache_client_ = std::move(cc);
   }
 
-  ~PreBuiltDatasetCache() = default;
+  ~PreBuiltDatasetCache() override = default;
 
   /// Method to initialize the DatasetCache by creating an instance of a CacheClient
   /// \return Status Error code
@@ -45,5 +45,4 @@ class PreBuiltDatasetCache : public DatasetCacheImpl {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_CACHE_PRE_BUILT_DATASET_CACHE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/batch_node.h

@@ -28,7 +28,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class BatchNode : public DatasetNode {
  public:
 #ifdef ENABLE_PYTHON
@@ -43,7 +42,7 @@ class BatchNode : public DatasetNode {
   BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder);
 
   /// \brief Destructor
-  ~BatchNode() = default;
+  ~BatchNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -126,7 +125,6 @@ class BatchNode : public DatasetNode {
 #endif
   std::map<std::string, std::pair<TensorShape, std::shared_ptr<Tensor>>> pad_map_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BATCH_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/bucket_batch_by_length_node.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class BucketBatchByLengthNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -38,7 +37,7 @@ class BucketBatchByLengthNode : public DatasetNode {
                           bool pad_to_bucket_boundary = false, bool drop_remainder = false);
 
   /// \brief Destructor
-  ~BucketBatchByLengthNode() = default;
+  ~BucketBatchByLengthNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -81,7 +80,6 @@ class BucketBatchByLengthNode : public DatasetNode {
   bool pad_to_bucket_boundary_;
   bool drop_remainder_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BUCKET_BATCH_BY_LENGTH_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/build_sentence_piece_vocab_node.h

@@ -28,7 +28,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class BuildSentenceVocabNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -37,7 +36,7 @@ class BuildSentenceVocabNode : public DatasetNode {
                          SentencePieceModel model_type, const std::unordered_map<std::string, std::string> &params);
 
   /// \brief Destructor
-  ~BuildSentenceVocabNode() = default;
+  ~BuildSentenceVocabNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -88,7 +87,6 @@ class BuildSentenceVocabNode : public DatasetNode {
   SentencePieceModel model_type_;
   std::unordered_map<std::string, std::string> params_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // #ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BUILD_SENTENCE_PIECE_VOCAB_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/build_vocab_node.h

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class BuildVocabNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -35,7 +34,7 @@ class BuildVocabNode : public DatasetNode {
                  const std::vector<std::string> &special_tokens, bool special_first);
 
   /// \brief Destructor
-  ~BuildVocabNode() = default;
+  ~BuildVocabNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -86,7 +85,6 @@ class BuildVocabNode : public DatasetNode {
   std::vector<std::string> special_tokens_;
   bool special_first_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_BUILD_VOCAB_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/cache_lookup_node.h

@@ -32,7 +32,7 @@ class CacheLookupNode : public DatasetNode, public SamplerObj {
                   std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~CacheLookupNode() = default;
+  ~CacheLookupNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -87,5 +87,4 @@ class CacheLookupNode : public DatasetNode, public SamplerObj {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_CACHE_LOOKUP_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/cache_merge_node.h

@@ -30,7 +30,7 @@ class CacheMergeNode : public DatasetNode {
   CacheMergeNode(std::shared_ptr<DatasetNode> child, std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~CacheMergeNode() = default;
+  ~CacheMergeNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -67,5 +67,4 @@ class CacheMergeNode : public DatasetNode {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_CACHE_MERGE_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/cache_node.h

@@ -31,7 +31,7 @@ class CacheNode : public DatasetNode {
             std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~CacheNode() = default;
+  ~CacheNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -71,5 +71,4 @@ class CacheNode : public DatasetNode {
 };
 }  // namespace dataset
 }  // namespace mindspore
-
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_CACHE_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/concat_node.h

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class ConcatNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -36,7 +35,7 @@ class ConcatNode : public DatasetNode {
                       const std::vector<std::pair<int, int>> &children_start_end_index = {});
 
   /// \brief Destructor
-  ~ConcatNode() = default;
+  ~ConcatNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -89,11 +88,6 @@ class ConcatNode : public DatasetNode {
   const std::vector<std::pair<int, int>> &ChildrenFlagAndNums() const { return children_flag_and_nums_; }
   const std::vector<std::pair<int, int>> &ChildrenStartEndIndex() const { return children_start_end_index_; }
 
- private:
-  std::shared_ptr<SamplerObj> sampler_;
-  std::vector<std::pair<int, int>> children_flag_and_nums_;
-  std::vector<std::pair<int, int>> children_start_end_index_;
-
   /// \brief Base-class override for accepting IRNodePass visitor
   /// \param[in] p The node to visit
   /// \param[out] modified Indicator if the node was modified
@@ -105,8 +99,12 @@ class ConcatNode : public DatasetNode {
   /// \param[out] modified Indicator if the node was modified
   /// \return Status of the node visit
   Status AcceptAfter(IRNodePass *const p, bool *const modified) override;
-};
 
+ private:
+  std::shared_ptr<SamplerObj> sampler_;
+  std::vector<std::pair<int, int>> children_flag_and_nums_;
+  std::vector<std::pair<int, int>> children_start_end_index_;
+};
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_CONCAT_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/dataset_node.cc

@@ -34,7 +34,6 @@ Status ComputeShuffleSize(int64_t num_files, int64_t num_devices, int64_t num_ro
   RETURN_UNEXPECTED_IF_NULL(shuffle_size);
   const int64_t average_files_multiplier = 4;
   const int64_t shuffle_max = 10000;
-  int64_t avg_rows_per_file = 0;
 
   // Adjust the num rows per shard if sharding was given
   if (num_devices > 0) {
@@ -52,7 +51,7 @@ Status ComputeShuffleSize(int64_t num_files, int64_t num_devices, int64_t num_ro
 
   // get the average per file
   CHECK_FAIL_RETURN_UNEXPECTED(num_files != 0, "The size of dataset_files must be greater than 0.");
-  avg_rows_per_file = num_rows / num_files;
+  int64_t avg_rows_per_file = num_rows / num_files;
 
   *shuffle_size = std::max(avg_rows_per_file * average_files_multiplier, shuffle_max);
   return Status::OK();

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/dataset_node.h

@@ -186,7 +186,7 @@ class DatasetNode : public std::enable_shared_from_this<DatasetNode> {
   explicit DatasetNode(const std::shared_ptr<DatasetCache> &dataset_cache);
 
   /// \brief Destructor
-  ~DatasetNode() = default;
+  virtual ~DatasetNode() = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -291,7 +291,7 @@ class DatasetNode : public std::enable_shared_from_this<DatasetNode> {
 
   /// \brief Check if this node is an orphan node
   /// \return True if this node isn't nullptr nor does it have any children and a parent
-  static bool IsOrphanNode(std::shared_ptr<DatasetNode> node) {
+  static bool IsOrphanNode(const std::shared_ptr<DatasetNode> &node) {
     return node != nullptr && node->parent_ == nullptr && node->Children().empty();
   }
 
@@ -299,7 +299,7 @@ class DatasetNode : public std::enable_shared_from_this<DatasetNode> {
   void HasCacheAbove() { descendant_of_cache_ = true; }
 
   /// \brief Getter of the number of workers
-  int32_t NumWorkers() { return num_workers_; }
+  int32_t NumWorkers() const { return num_workers_; }
 
   /// \brief Getter of dataset cache
   std::shared_ptr<DatasetCache> GetDatasetCache() { return cache_; }
@@ -351,7 +351,7 @@ class DatasetNode : public std::enable_shared_from_this<DatasetNode> {
   void SetTotalRepeats(int32_t total_repeats) { total_repeats_ = total_repeats; }
 
   /// \brief Setter function, set the number of epochs for the operator
-  void SetNumEpochs(int32_t num_epochs) { num_epochs_ = num_epochs; }
+  virtual void SetNumEpochs(int32_t num_epochs) { num_epochs_ = num_epochs; }
 
   /// \brief Getter function
   /// \return The number of required repeats for the operator
@@ -404,7 +404,7 @@ class MappableSourceNode : public DatasetNode {
   Status Accept(IRNodePass *const p, bool *const modified) override;
 
   /// \brief Destructor
-  ~MappableSourceNode() = default;
+  virtual ~MappableSourceNode() = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -435,7 +435,7 @@ class NonMappableSourceNode : public DatasetNode {
   Status Accept(IRNodePass *const p, bool *const modified) override;
 
   /// \brief Destructor
-  ~NonMappableSourceNode() = default;
+  virtual ~NonMappableSourceNode() = default;
 
   /// \brief Node name getter
   /// \return Name of the current node

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/epoch_ctrl_node.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class EpochCtrlNode : public RepeatNode {
   // Allow GeneratorNode to access internal members
   friend class GeneratorNode;
@@ -40,7 +39,7 @@ class EpochCtrlNode : public RepeatNode {
   EpochCtrlNode(std::shared_ptr<DatasetNode> child, int32_t num_epochs);
 
   /// \brief Destructor
-  ~EpochCtrlNode() = default;
+  ~EpochCtrlNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -75,7 +74,6 @@ class EpochCtrlNode : public RepeatNode {
   /// \return Status of the node visit
   Status AcceptAfter(IRNodePass *const p, bool *const modified) override;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_EPOCH_CTRL_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/filter_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class FilterNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -33,7 +32,7 @@ class FilterNode : public DatasetNode {
              std::vector<std::string> input_columns = {});
 
   /// \brief Destructor
-  ~FilterNode() = default;
+  ~FilterNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -83,7 +82,6 @@ class FilterNode : public DatasetNode {
   std::shared_ptr<TensorOp> predicate_;
   std::vector<std::string> input_columns_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_FILTER_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/map_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class MapNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -36,7 +35,7 @@ class MapNode : public DatasetNode {
           ManualOffloadMode offload = ManualOffloadMode::kUnspecified);
 
   /// \brief Destructor
-  ~MapNode() = default;
+  ~MapNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -127,7 +126,6 @@ class MapNode : public DatasetNode {
   /// \brief ManualOffloadMode to indicate manual_offload status
   ManualOffloadMode offload_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_MAP_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/project_node.h

@@ -25,14 +25,13 @@
 
 namespace mindspore {
 namespace dataset {
-
 class ProjectNode : public DatasetNode {
  public:
   /// \brief Constructor
   explicit ProjectNode(std::shared_ptr<DatasetNode> child, const std::vector<std::string> &columns);
 
   /// \brief Destructor
-  ~ProjectNode() = default;
+  ~ProjectNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -74,7 +73,6 @@ class ProjectNode : public DatasetNode {
  private:
   std::vector<std::string> columns_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_PROJECT_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/rename_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class RenameNode : public DatasetNode {
  public:
   /// \brief Constructor
@@ -33,7 +32,7 @@ class RenameNode : public DatasetNode {
                       const std::vector<std::string> &output_columns);
 
   /// \brief Destructor
-  ~RenameNode() = default;
+  ~RenameNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -77,7 +76,6 @@ class RenameNode : public DatasetNode {
   std::vector<std::string> input_columns_;
   std::vector<std::string> output_columns_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_RENAME_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/repeat_node.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class RepeatOp;
 
 class RepeatNode : public DatasetNode {
@@ -42,7 +41,7 @@ class RepeatNode : public DatasetNode {
   RepeatNode(std::shared_ptr<DatasetNode> child, int32_t count);
 
   /// \brief Destructor
-  ~RepeatNode() = default;
+  ~RepeatNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -67,7 +66,7 @@ class RepeatNode : public DatasetNode {
 
   /// \brief Getter
   /// \return Number of cycles to repeat the execution
-  const int32_t Count() const { return repeat_count_; }
+  int32_t Count() const { return repeat_count_; }
 
   /// \brief Base-class override for GetDatasetSize
   /// \param[in] size_getter Shared pointer to DatasetSizeGetter
@@ -136,7 +135,6 @@ class RepeatNode : public DatasetNode {
   std::shared_ptr<RepeatNode> reset_ancestor_;  // updated its immediate Repeat/EpochCtrl ancestor in GeneratorNodePass
   int32_t repeat_count_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_REPEAT_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/root_node.h

@@ -35,7 +35,7 @@ class RootNode : public DatasetNode {
   explicit RootNode(std::shared_ptr<DatasetNode> child);
 
   /// \brief Destructor
-  ~RootNode() = default;
+  ~RootNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -55,10 +55,10 @@ class RootNode : public DatasetNode {
   Status Build(std::vector<std::shared_ptr<DatasetOp>> *const node_ops) override;
 
   /// \brief Getter of number of epochs
-  int32_t num_epochs() { return num_epochs_; }
+  int32_t num_epochs() const { return num_epochs_; }
 
   /// \brief Setter of number of epochs
-  void SetNumEpochs(int32_t num_epochs) { num_epochs_ = num_epochs; }
+  void SetNumEpochs(int32_t num_epochs) override { num_epochs_ = num_epochs; }
 
   /// \brief Parameters validation
   /// \return Status Status::OK() if all the parameters are valid
@@ -79,7 +79,6 @@ class RootNode : public DatasetNode {
  private:
   int32_t num_epochs_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_ROOT_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/shuffle_node.h

@@ -27,12 +27,11 @@
 
 namespace mindspore {
 namespace dataset {
-
 class ShuffleNode : public DatasetNode {
  public:
   ShuffleNode(std::shared_ptr<DatasetNode> child, int32_t shuffle_size, bool reset_every_epoch);
 
-  ~ShuffleNode() = default;
+  ~ShuffleNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -76,7 +75,6 @@ class ShuffleNode : public DatasetNode {
   uint32_t shuffle_seed_;
   bool reset_every_epoch_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SHUFFLE_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/skip_node.h

@@ -25,14 +25,13 @@
 
 namespace mindspore {
 namespace dataset {
-
 class SkipNode : public DatasetNode {
  public:
   /// \brief Constructor
   explicit SkipNode(std::shared_ptr<DatasetNode> child, int32_t count);
 
   /// \brief Destructor
-  ~SkipNode() = default;
+  ~SkipNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -57,7 +56,7 @@ class SkipNode : public DatasetNode {
 
   /// \brief Getter
   /// \return Number of rows to skip
-  const int32_t Count() const { return skip_count_; }
+  int32_t Count() const { return skip_count_; }
 
   /// \brief Base-class override for GetDatasetSize
   /// \param[in] size_getter Shared pointer to DatasetSizeGetter
@@ -99,7 +98,6 @@ class SkipNode : public DatasetNode {
  private:
   int32_t skip_count_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SKIP_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/ag_news_node.h

@@ -34,7 +34,7 @@ class AGNewsNode : public NonMappableSourceNode {
              int32_t num_shards, int32_t shard_id, const std::shared_ptr<DatasetCache> &cache);
 
   /// \brief Destructor.
-  ~AGNewsNode() = default;
+  ~AGNewsNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/album_node.cc

@@ -99,7 +99,6 @@ Status AlbumNode::GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_
     *dataset_size = dataset_size_;
     return Status::OK();
   }
-  int64_t sample_size = -1;
   int64_t num_rows = 0;
   // iterate over the files in the directory and count files to initiate num_rows
   Path folder(dataset_dir_);
@@ -118,7 +117,7 @@ Status AlbumNode::GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_
   // give sampler the total number of files and check if num_samples is smaller
   std::shared_ptr<SamplerRT> sampler_rt = nullptr;
   RETURN_IF_NOT_OK(sampler_->SamplerBuild(&sampler_rt));
-  sample_size = sampler_rt->CalculateNumSamples(num_rows);
+  int64_t sample_size = sampler_rt->CalculateNumSamples(num_rows);
   if (sample_size == -1) {
     RETURN_IF_NOT_OK(size_getter->DryRun(shared_from_this(), &sample_size));
   }

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/album_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class AlbumNode : public MappableSourceNode {
  public:
   /// \brief Constructor
@@ -34,7 +33,7 @@ class AlbumNode : public MappableSourceNode {
             const std::shared_ptr<DatasetCache> &cache);
 
   /// \brief Destructor
-  ~AlbumNode() = default;
+  ~AlbumNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -102,7 +101,6 @@ class AlbumNode : public MappableSourceNode {
   bool decode_;
   std::shared_ptr<SamplerObj> sampler_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_ALBUM_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/amazon_review_node.h

@@ -32,7 +32,7 @@ class AmazonReviewNode : public NonMappableSourceNode {
                    int32_t num_shards, int32_t shard_id, const std::shared_ptr<DatasetCache> &cache);
 
   /// \brief Destructor.
-  ~AmazonReviewNode() = default;
+  ~AmazonReviewNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/caltech256_node.h

@@ -37,7 +37,7 @@ class Caltech256Node : public MappableSourceNode {
                  std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor.
-  ~Caltech256Node() = default;
+  ~Caltech256Node() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/celeba_node.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class CelebANode : public MappableSourceNode {
  public:
   /// \brief Constructor
@@ -35,7 +34,7 @@ class CelebANode : public MappableSourceNode {
              const bool &decode, const std::set<std::string> &extensions, const std::shared_ptr<DatasetCache> &cache);
 
   /// \brief Destructor
-  ~CelebANode() = default;
+  ~CelebANode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -104,7 +103,6 @@ class CelebANode : public MappableSourceNode {
   std::set<std::string> extensions_;
   std::shared_ptr<SamplerObj> sampler_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_CELEBA_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/cifar100_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class Cifar100Node : public MappableSourceNode {
  public:
   /// \brief Constructor
@@ -33,7 +32,7 @@ class Cifar100Node : public MappableSourceNode {
                std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~Cifar100Node() = default;
+  ~Cifar100Node() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -98,7 +97,6 @@ class Cifar100Node : public MappableSourceNode {
   std::string usage_;
   std::shared_ptr<SamplerObj> sampler_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_CIFAR100_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/cifar10_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class Cifar10Node : public MappableSourceNode {
  public:
   /// \brief Constructor
@@ -33,7 +32,7 @@ class Cifar10Node : public MappableSourceNode {
               std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~Cifar10Node() = default;
+  ~Cifar10Node() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -98,7 +97,6 @@ class Cifar10Node : public MappableSourceNode {
   std::string usage_;
   std::shared_ptr<SamplerObj> sampler_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_CIFAR10_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/cityscapes_node.cc

@@ -28,14 +28,14 @@ namespace dataset {
 // Constructor for CityscapesNode
 CityscapesNode::CityscapesNode(const std::string &dataset_dir, const std::string &usage,
                                const std::string &quality_mode, const std::string &task, bool decode,
-                               std::shared_ptr<SamplerObj> sampler, std::shared_ptr<DatasetCache> cache)
-    : MappableSourceNode(std::move(cache)),
+                               const std::shared_ptr<SamplerObj> &sampler, const std::shared_ptr<DatasetCache> &cache)
+    : MappableSourceNode(cache),
       dataset_dir_(dataset_dir),
       usage_(usage),
       quality_mode_(quality_mode),
       task_(task),
-      sampler_(sampler),
-      decode_(decode) {}
+      decode_(decode),
+      sampler_(sampler) {}
 
 std::shared_ptr<DatasetNode> CityscapesNode::Copy() {
   std::shared_ptr<SamplerObj> sampler = (sampler_ == nullptr) ? nullptr : sampler_->SamplerCopy();

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/cityscapes_node.h

@@ -25,16 +25,15 @@
 
 namespace mindspore {
 namespace dataset {
-
 class CityscapesNode : public MappableSourceNode {
  public:
   /// \brief Constructor.
   CityscapesNode(const std::string &dataset_dir, const std::string &usage, const std::string &quality_mode,
-                 const std::string &task, bool decode, std::shared_ptr<SamplerObj> sampler,
-                 std::shared_ptr<DatasetCache> cache);
+                 const std::string &task, bool decode, const std::shared_ptr<SamplerObj> &sampler,
+                 const std::shared_ptr<DatasetCache> &cache);
 
   /// \brief Destructor.
-  ~CityscapesNode() = default;
+  ~CityscapesNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.
@@ -105,7 +104,6 @@ class CityscapesNode : public MappableSourceNode {
   bool decode_;
   std::shared_ptr<SamplerObj> sampler_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_CITYSCAPES_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/clue_node.h

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 /// \class CLUENode
 /// \brief A Dataset derived class to represent CLUE dataset
 class CLUENode : public NonMappableSourceNode {
@@ -36,7 +35,7 @@ class CLUENode : public NonMappableSourceNode {
            ShuffleMode shuffle, int32_t num_shards, int32_t shard_id, std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~CLUENode() = default;
+  ~CLUENode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -145,7 +144,6 @@ class CLUENode : public NonMappableSourceNode {
   int32_t num_shards_;
   int32_t shard_id_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_CLUE_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/coco_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class CocoNode : public MappableSourceNode {
  public:
   /// \brief Constructor.
@@ -34,7 +33,7 @@ class CocoNode : public MappableSourceNode {
            const bool &extra_metadata);
 
   /// \brief Destructor.
-  ~CocoNode() = default;
+  ~CocoNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.
@@ -105,7 +104,6 @@ class CocoNode : public MappableSourceNode {
   std::shared_ptr<SamplerObj> sampler_;
   bool extra_metadata_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_COCO_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/conll2000_node.h

@@ -34,7 +34,7 @@ class CoNLL2000Node : public NonMappableSourceNode {
                 int32_t num_shards, int32_t shard_id, std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor.
-  ~CoNLL2000Node() = default;
+  ~CoNLL2000Node() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/csv_node.h

@@ -32,9 +32,12 @@ enum CsvType : uint8_t { INT = 0, FLOAT, STRING };
 class CsvBase {
  public:
   CsvBase() = default;
+
   explicit CsvBase(CsvType t) : type(t) {}
-  virtual ~CsvBase() {}
-  CsvType type;
+
+  virtual ~CsvBase() = default;
+
+  CsvType type{INT};
 };
 
 /// \brief CSV Record that can represent integer, float and string.
@@ -42,8 +45,11 @@ template <typename T>
 class CsvRecord : public CsvBase {
  public:
   CsvRecord() = default;
+
   CsvRecord(CsvType t, T v) : CsvBase(t), value(v) {}
-  ~CsvRecord() {}
+
+  ~CsvRecord() override = default;
+
   T value;
 };
 
@@ -56,7 +62,7 @@ class CSVNode : public NonMappableSourceNode {
           std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor
-  ~CSVNode() = default;
+  ~CSVNode() override = default;
 
   /// \brief Node name getter
   /// \return Name of the current node
@@ -139,7 +145,6 @@ class CSVNode : public NonMappableSourceNode {
   int32_t num_shards_;
   int32_t shard_id_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_CSV_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/dbpedia_node.h

@@ -33,7 +33,7 @@ class DBpediaNode : public NonMappableSourceNode {
               int32_t num_shards, int32_t shard_id, std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor.
-  ~DBpediaNode() = default;
+  ~DBpediaNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/div2k_node.h

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace dataset {
-
 class DIV2KNode : public MappableSourceNode {
  public:
   /// \brief Constructor.
@@ -33,7 +32,7 @@ class DIV2KNode : public MappableSourceNode {
             bool decode, const std::shared_ptr<SamplerObj> &sampler, std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor.
-  ~DIV2KNode() = default;
+  ~DIV2KNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/emnist_node.h

@@ -37,7 +37,7 @@ class EMnistNode : public MappableSourceNode {
              std::shared_ptr<SamplerObj> sampler, std::shared_ptr<DatasetCache> cache);
 
   /// \brief Destructor.
-  ~EMnistNode() = default;
+  ~EMnistNode() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.
@@ -105,7 +105,6 @@ class EMnistNode : public MappableSourceNode {
   std::string usage_;
   std::shared_ptr<SamplerObj> sampler_;
 };
-
 }  // namespace dataset
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_EMNIST_NODE_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/en_wik9_node.h

@@ -40,7 +40,7 @@ class EnWik9Node : public NonMappableSourceNode {
              int32_t shard_id, const std::shared_ptr<DatasetCache> &cache);
 
   /// \brief Destructor.
-  ~EnWik9Node() = default;
+  ~EnWik9Node() override = default;
 
   /// \brief Node name getter.
   /// \return Name of the current node.