clean up code

paddle/gserver/evaluators/Evaluator.cpp

@@ -78,23 +78,24 @@ public:
                                               useGpu(arguments[0].deviceId));
     const MatrixPtr errorMat2 = Matrix::create(output->getHeight(),
                                                1,
-                                               /* trans= */ false, false);
-    // useGpu(arguments[0].deviceId));
+                                               /* trans= */ false,
+                                               false);
+
     errorMat->zeroMem();
 
     if (label != nullptr) {
       errorMat->classificationError(*output, *label);  // top-1 error
       size_t height = output->getHeight();
-      size_t width = 5;  // config_.num_results();
+      size_t width = 5;
 
-      IVector::resizeOrCreate(maxIds_, height * width,
-                              useGpu(arguments[0].deviceId));
-      Matrix::resizeOrCreate(maxValues_, height, width, false,
-                             useGpu(arguments[0].deviceId));
+      IVector::resizeOrCreate(
+          maxIds_, height * width, useGpu(arguments[0].deviceId));
+      Matrix::resizeOrCreate(
+          maxValues_, height, width, false, useGpu(arguments[0].deviceId));
       output->rowMax(*maxIds_, *maxValues_);  // top-5 values
 
-      int* ids;
-      int* lbl;
+      int* ids = nullptr;
+      int* lbl = nullptr;
       if (useGpu(arguments[0].deviceId)) {
         IVectorPtr dest = IVector::create(maxIds_->getSize(), false);
         hl_memcpy_device2host((void*)dest->getData(),
@@ -112,10 +113,8 @@ public:
         lbl = label->getData();
       }
 
-      // real* result = errorMat->getData();
       real* result2 = errorMat2->getData();
       for (size_t i = 0; i < height; ++i) {
-        // result[i] = (ids[i * width] != lbl[i]);  // top-1 error
         result2[i] = (ids[i * width] != lbl[i]);  // initialize top-5 error
         for (size_t j = 1; j < width; ++j) {
           if (result2[i] == 0.0) {
@@ -141,10 +140,8 @@ public:
   }
 
   void printStats(std::ostream& os) const {
-    os << "top_1_error="
-       << (numSamples_ ? totalScore_ / numSamples_ : 0)
-       << " top_5_error="
-       << (numSamples_ ? totalScore2_ / numSamples_ : 0);
+    os << "top_1_error=" << (numSamples_ ? totalScore_ / numSamples_ : 0)
+       << " top_5_error=" << (numSamples_ ? totalScore2_ / numSamples_ : 0);
   }
 
   virtual real evalImp(std::vector<Argument>& arguments) {
@@ -156,7 +153,6 @@ public:
     mergeResultsOfAllClients(client);
   }
 
-
 private:
   IVectorPtr maxIds_;
   MatrixPtr maxValues_;

python/paddle/trainer_config_helpers/evaluators.py

@@ -495,6 +495,7 @@ def gradient_printer_evaluator(
     """
     evaluator_base(name=name, type="gradient_printer", input=input)
 
+
 @evaluator(EvaluatorAttribute.FOR_PRINT)
 @wrap_name_default()
 def maxid_printer_evaluator(