!10411 minor fix, change warning log to info , validate num_worker if it exceeds num_cpu_core

From: @ziruiwu
Reviewed-by: @mikef,@nsyca
Signed-off-by: @nsyca

mindspore/ccsrc/minddata/dataset/engine/datasetops/batch_op.cc

@@ -389,8 +389,8 @@ Status BatchOp::InvokeBatchMapFunc(TensorTable *input, TensorTable *output, CBat
         TensorRow output_batch;
         // If user returns a type that is neither a list nor an array, issue a error msg.
         if (py::isinstance<py::array>(ret_tuple[i])) {
-          MS_LOG(WARNING) << "column: " << out_col_names_[i]
-                          << " returned by per_batch_map is a np.array. Please use list instead.";
+          MS_LOG(INFO) << "column: " << out_col_names_[i]
+                       << " returned by per_batch_map is a np.array. Please use list instead.";
         } else if (!py::isinstance<py::list>(ret_tuple[i])) {
           MS_LOG(ERROR) << "column: " << out_col_names_[i]
                         << " returned by per_batch_map is not a list, this could lead to conversion failure.";

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

@@ -420,10 +420,13 @@ Status DatasetNode::GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &siz
   }
 }
 Status DatasetNode::ValidateParams() {
+  int32_t num_threads = GlobalContext::config_manager()->num_cpu_threads();
+  // in case std::thread::hardware_concurrency returns 0, use an artificial upper limit
+  num_threads = num_threads > 0 ? num_threads : std::numeric_limits<uint16_t>::max();
   CHECK_FAIL_RETURN_UNEXPECTED(
-    num_workers_ > 0 && num_workers_ < std::numeric_limits<uint16_t>::max(),
-    Name() + "'s num_workers=" + std::to_string(num_workers_) + ", this value is less than 1 or too large.");
-
+    num_workers_ > 0 && num_workers_ <= num_threads,
+    Name() + "'s num_workers=" + std::to_string(num_workers_) +
+      ", this value is not within the required range of [1, cpu_thread_cnt=" + std::to_string(num_threads) + "].");
   return Status::OK();
 }
 

mindspore/ccsrc/minddata/dataset/engine/runtime_context.cc

@@ -23,16 +23,16 @@ void RuntimeContext::AssignConsumer(std::shared_ptr<TreeConsumer> tree_consumer)
   tree_consumer_ = std::move(tree_consumer);
 }
 Status NativeRuntimeContext::Terminate() {
-  MS_LOG(INFO) << "Terminating a NativeRuntime";
+  MS_LOG(INFO) << "Terminating a NativeRuntime.";
   if (tree_consumer_ != nullptr) {
     return TerminateImpl();
   }
-  MS_LOG(WARNING) << "TreeConsumer was not initialized";
+  MS_LOG(WARNING) << "TreeConsumer was not initialized.";
   return Status::OK();
 }
 
 Status NativeRuntimeContext::TerminateImpl() {
-  CHECK_FAIL_RETURN_UNEXPECTED(tree_consumer_ != nullptr, " Tree Consumer is not initialized");
+  CHECK_FAIL_RETURN_UNEXPECTED(tree_consumer_ != nullptr, " TreeConsumer is not initialized.");
   return tree_consumer_->Terminate();
 }
 

tests/ut/cpp/dataset/c_api_dataset_ops_test.cc

@@ -1839,7 +1839,7 @@ TEST_F(MindDataTestPipeline, TestNumWorkersValidate) {
 
   // Create an ImageFolder Dataset
   std::string folder_path = datasets_root_path_ + "/testPK/data/";
-  std::shared_ptr<Dataset> ds = ImageFolder(folder_path);
+  std::shared_ptr<Dataset> ds = ImageFolder(folder_path, false, SequentialSampler(0, 1));
 
   // ds needs to be non nullptr otherwise, the subsequent logic will core dump
   ASSERT_NE(ds, nullptr);
@@ -1849,4 +1849,14 @@ TEST_F(MindDataTestPipeline, TestNumWorkersValidate) {
 
   // test if set num_workers can be very large
   EXPECT_EQ(ds->SetNumWorkers(INT32_MAX)->CreateIterator(), nullptr);
-}
+
+  int32_t cpu_core_cnt = GlobalContext::config_manager()->num_cpu_threads();
+
+  // only do this test if cpu_core_cnt can be successfully obtained
+  if (cpu_core_cnt > 0) {
+    EXPECT_EQ(ds->SetNumWorkers(cpu_core_cnt + 1)->CreateIterator(), nullptr);
+    // verify setting num_worker to 1 or cpu_core_cnt is allowed
+    ASSERT_OK(ds->SetNumWorkers(cpu_core_cnt)->IRNode()->ValidateParams());
+    ASSERT_OK(ds->SetNumWorkers(1)->IRNode()->ValidateParams());
+  }
+}