!3248 Alarm modification

Merge pull request !3248 from shenwei41/sw_master

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

@@ -186,7 +186,7 @@ std::shared_ptr<ProjectDataset> Dataset::Project(const std::vector<std::string>
 
 // Helper function to create default RandomSampler.
 std::shared_ptr<SamplerObj> CreateDefaultSampler() {
-  int32_t num_samples = 0;  // 0 means to sample all ids.
+  const int32_t num_samples = 0;  // 0 means to sample all ids.
   bool replacement = false;
   return std::make_shared<RandomSamplerObj>(replacement, num_samples);
 }

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

@@ -1157,8 +1157,8 @@ Status DEPipeline::ParseTFReaderOp(const py::dict &args, std::shared_ptr<Dataset
   if (sampler) {
     (void)builder->SetSampler(std::move(sampler));
   } else if (cache_client) {
-    int64_t num_samples = 0;
-    int64_t start_index = 0;
+    const int64_t num_samples = 0;
+    const int64_t start_index = 0;
     sampler = std::make_shared<SequentialSampler>(num_samples, start_index);
     (void)builder->SetSampler(std::move(sampler));
   }
@@ -1511,8 +1511,8 @@ Status DEPipeline::ParseRandomDataOp(const py::dict &args, std::shared_ptr<Datas
   if (sampler) {
     (void)builder.SetSampler(std::move(sampler));
   } else if (cache_client) {
-    int64_t num_samples = 0;
-    int64_t start_index = 0;
+    const int64_t num_samples = 0;
+    const int64_t start_index = 0;
     sampler = std::make_shared<SequentialSampler>(num_samples, start_index);
     (void)builder.SetSampler(std::move(sampler));
   }

mindspore/ccsrc/minddata/dataset/engine/cache/cache_request.h

@@ -111,6 +111,7 @@ class BatchFetchRequest : public BaseRequest {
   friend class CacheService;
   BatchFetchRequest(connection_id_type connection_id, const std::vector<row_id_type> &row_id)
       : BaseRequest(connection_id, RequestType::kBatchFetchRows), row_id_(row_id) {}
+  ~BatchFetchRequest() = default;
   Status RestoreRows(TensorTable *out);
 
  private:
@@ -130,6 +131,8 @@ class CreationCacheRequest : public BaseRequest {
                                 CreateCacheFlag flag = CreateCacheFlag::kNone)
       : BaseRequest(connection_id, RequestType::kCreateCache), cache_mem_sz(cache_mem_sz), flag_(flag) {}
 
+  ~CreationCacheRequest() = default;
+
   std::string cookie() const { return cookie_; }
 
  private:
@@ -142,6 +145,8 @@ class PurgeCacheRequest : public BaseRequest {
  public:
   friend class CacheServer;
   explicit PurgeCacheRequest(connection_id_type connection_id) : BaseRequest(connection_id, RequestType::kPurgeCache) {}
+
+  ~PurgeCacheRequest() = default;
 };
 /// \brief Request to destroy a cache
 class DestroyCacheRequest : public BaseRequest {
@@ -149,6 +154,9 @@ class DestroyCacheRequest : public BaseRequest {
   friend class CacheServer;
   explicit DestroyCacheRequest(connection_id_type connection_id)
       : BaseRequest(connection_id, RequestType::kDestroyCache) {}
+
+  /// \brief Destructor
+  ~DestroyCacheRequest() = default;
 };
 /// \brief Obtain the statistics of the current connection
 class GetStatRequest : public BaseRequest {
@@ -156,6 +164,9 @@ class GetStatRequest : public BaseRequest {
   friend class CacheServer;
   friend class CacheService;
   explicit GetStatRequest(connection_id_type connection_id) : BaseRequest(connection_id, RequestType::kGetStat) {}
+
+  ~GetStatRequest() = default;
+
   row_id_type GetMinRowId() const {
     auto *msg = flatbuffers::GetRoot<ServiceStatMsg>(mem_.GetPointer());
     return msg->min_row_id();
@@ -217,6 +228,8 @@ class BuildPhaseDoneRequest : public BaseRequest {
   BuildPhaseDoneRequest(connection_id_type connection_id, const std::string &cookie)
       : BaseRequest(connection_id, RequestType::kBuildPhaseDone), cookie_(cookie) {}
 
+  ~BuildPhaseDoneRequest() = default;
+
  private:
   std::string cookie_;
 };

mindspore/ccsrc/minddata/dataset/engine/opt/post/repeat_pass.h

@@ -35,6 +35,9 @@ class RepeatPass : public NodePass {
   /// \brief Constructor
   RepeatPass();
 
+  /// \brief Destructor
+  ~RepeatPass() = default;
+
   /// \brief Identifies the subtree below this node as being in a repeated path of the tree.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all

mindspore/ccsrc/minddata/dataset/engine/opt/pre/cache_pass.cc

@@ -67,8 +67,8 @@ Status CachePass::RunOnNode(std::shared_ptr<CacheOp> node, bool *modified) {
       MS_LOG(INFO) << "Cache transform pass: Set up cache sampler from non-mappable leaf.";
     } else {
       // We're a cache op but no sampler was saved from leaf, so create a default sampler
-      int64_t num_samples = 0;
-      int64_t start_index = 0;
+      const int64_t num_samples = 0;
+      const int64_t start_index = 0;
       sampler_ = std::make_shared<SequentialSampler>(num_samples, start_index);
       node->SetSampler(std::move(sampler_));
       MS_LOG(INFO) << "Cache transform pass: Creating default sequential sampler for cache op.";

mindspore/ccsrc/minddata/dataset/engine/opt/pre/cache_pass.h

@@ -36,6 +36,9 @@ class CachePass : public NodePass {
   /// \param[in] transform_pass Raw pointer back to controlling tree pass
   explicit CachePass(CacheTransformPass *transform_pass);
 
+  /// \brief Destructor
+  ~CachePass() = default;
+
   /// \brief Identifies the subtree below this node as a cached descendant tree.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all

mindspore/ccsrc/minddata/dataset/engine/opt/pre/cache_transform_pass.h

@@ -37,6 +37,9 @@ class CacheTransformPass : public TreePass {
   /// \brief Constructor
   CacheTransformPass();
 
+  /// \brief Destructor
+  ~CacheTransformPass() = default;
+
   /// \brief Runs a cache_pass first to set up the transformation nodes, and then drives any of these transformations
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.

mindspore/ccsrc/minddata/dataset/kernels/image/image_utils.cc

@@ -664,8 +664,8 @@ Status AutoContrast(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor
           table.push_back(i);
         }
       } else {
-        float scale = 255.0 / (hi - lo);
-        float offset = -1 * lo * scale;
+        const float scale = 255.0 / (hi - lo);
+        const float offset = -1 * lo * scale;
         for (int32_t i = 0; i < 256; i++) {
           int32_t ix = static_cast<int32_t>(i * scale + offset);
           ix = std::max(ix, 0);