Fix accidental double logging of successful ML Service call

This function is called by both TfNative and MlService codepaths, and ML
Service code path was already logging success.

Moved the logging out of the common function and made it explicit in
each codepath.

Bug: 935838
Test: no
Change-Id: I8a9a5882f339866ffd309e7ffa87945adf455c7a
Reviewed-on: https://chromium-review.googlesource.com/c/1488391
Auto-Submit: Andrew Moylan <amoylan@chromium.org>
Reviewed-by: Jia Meng <jiameng@chromium.org>
Commit-Queue: Andrew Moylan <amoylan@chromium.org>
Cr-Commit-Position: refs/heads/master@{#635458}

chrome/browser/chromeos/power/ml/smart_dim/ml_service_client.cc

@@ -118,10 +118,10 @@ void MlServiceClientImpl::ExecuteCallback(
     prediction.set_response(UserActivityEvent::ModelPrediction::MODEL_ERROR);
     LogPowerMLSmartDimModelResult(SmartDimModelResult::kOtherError);
   } else {
-    LogPowerMLSmartDimModelResult(SmartDimModelResult::kSuccess);
     float inactivity_score =
         (outputs.value())[0]->data->get_float_list()->value[0];
     prediction = get_prediction_callback.Run(inactivity_score);
+    LogPowerMLSmartDimModelResult(SmartDimModelResult::kSuccess);
   }
 
   std::move(decision_callback).Run(prediction);

chrome/browser/chromeos/power/ml/smart_dim/model_impl.cc

@@ -326,7 +326,6 @@ SmartDimModelImpl::CreatePredictionFromInactivityScore(float inactivity_score) {
     prediction.set_response(UserActivityEvent::ModelPrediction::NO_DIM);
   }
 
-  LogPowerMLSmartDimModelResult(SmartDimModelResult::kSuccess);
   return prediction;
 }
 
@@ -345,8 +344,7 @@ UserActivityEvent::ModelPrediction SmartDimModelImpl::ShouldDimTfNative(
     return prediction;
   }
 
-  // Logging for the success case will take place in
-  // CreatePredictionFromInactivityScore().
+  LogPowerMLSmartDimModelResult(SmartDimModelResult::kSuccess);
   return CreatePredictionFromInactivityScore(inactivity_score);
 }
 

chrome/browser/chromeos/power/ml/smart_dim/model_impl.h

@@ -91,12 +91,6 @@ class SmartDimModelImpl : public SmartDimModel {
 
   // Takes an |inactivity_score| returned from the ML model and, using that,
   // returns a ModelPrediction.
-  //
-  // NOTE: This function is only expected to be called after successful
-  // inference executions, and therefore does not have an error path.
-  // As a corollary, it also performs the logging of a successful inference
-  // call to UMA (doing this here allows the logging to take place in a Mojo
-  // callback in case the ML service was used).
   UserActivityEvent::ModelPrediction CreatePredictionFromInactivityScore(
       float inactivity_score);