fix log

deepspeech/exps/deepspeech2/model.py

@@ -55,7 +55,7 @@ class DeepSpeech2Trainer(Trainer):
         losses_np = {
             'train_loss': float(loss),
         }
-        msg += "time: {:>.3f}s, ".format(iteration_time)
+        msg += "train time: {:>.3f}s, ".format(iteration_time)
         msg += "batch size: {}, ".format(self.config.data.batch_size)
         msg += ', '.join('{}: {:>.6f}'.format(k, v)
                          for k, v in losses_np.items())

deepspeech/exps/u2/model.py

@@ -96,7 +96,7 @@ class U2Trainer(Trainer):
         iteration_time = time.time() - start
 
         if (batch_index + 1) % train_conf.log_interval == 0:
-            msg += "time: {:>.3f}s, ".format(iteration_time)
+            msg += "train time: {:>.3f}s, ".format(iteration_time)
             msg += "batch size: {}, ".format(self.config.data.batch_size)
             msg += "accum: {}, ".format(train_conf.accum_grad)
             msg += ', '.join('{}: {:>.6f}'.format(k, v)
@@ -177,7 +177,7 @@ class U2Trainer(Trainer):
                     msg += "batch : {}/{}, ".format(batch_index + 1,
                                                     len(self.train_loader))
                     msg += "lr: {:>.8f}, ".format(self.lr_scheduler())
-                    msg += "dataloader time: {:>.3f}s, ".format(dataload_time)
+                    msg += "data time: {:>.3f}s, ".format(dataload_time)
                     self.train_batch(batch_index, batch, msg)
                     data_start_time = time.time()
             except Exception as e:
@@ -275,6 +275,7 @@ class U2Trainer(Trainer):
         if self.parallel:
             model = paddle.DataParallel(model)
 
+        logger.info(f"{model}")
         layer_tools.print_params(model, logger.info)
 
         train_config = config.training

deepspeech/training/trainer.py

@@ -194,7 +194,7 @@ class Trainer():
                     msg += "batch : {}/{}, ".format(batch_index + 1,
                                                     len(self.train_loader))
                     msg += "lr: {:>.8f}, ".format(self.lr_scheduler())
-                    msg += "dataloader time: {:>.3f}s, ".format(dataload_time)
+                    msg += "data time: {:>.3f}s, ".format(dataload_time)
                     self.train_batch(batch_index, batch, msg)
                     data_start_time = time.time()
             except Exception as e: