Evolve in CSV format (#4307)

* Update evolution to CSV format

* Update

* Update

* Update

* Update

* Update

* reset args

* reset args

* reset args

* plot_results() fix

* Cleanup

* Cleanup2

utils/loggers/__init__.py

@@ -95,9 +95,8 @@ class Loggers():
             files = sorted(self.save_dir.glob('val*.jpg'))
             self.wandb.log({"Validation": [wandb.Image(str(f), caption=f.name) for f in files]})
 
-    def on_fit_epoch_end(self, mloss, results, lr, epoch, best_fitness, fi):
+    def on_fit_epoch_end(self, vals, epoch, best_fitness, fi):
         # Callback runs at the end of each fit (train+val) epoch
-        vals = list(mloss) + list(results) + lr
         x = {k: v for k, v in zip(self.keys, vals)}  # dict
         if self.csv:
             file = self.save_dir / 'results.csv'
@@ -123,7 +122,7 @@ class Loggers():
     def on_train_end(self, last, best, plots, epoch):
         # Callback runs on training end
         if plots:
-            plot_results(dir=self.save_dir)  # save results.png
+            plot_results(file=self.save_dir / 'results.csv')  # save results.png
         files = ['results.png', 'confusion_matrix.png', *[f'{x}_curve.png' for x in ('F1', 'PR', 'P', 'R')]]
         files = [(self.save_dir / f) for f in files if (self.save_dir / f).exists()]  # filter