fix trainer bug

demo/image_classification/train.py

@@ -5,14 +5,18 @@ from paddlehub.finetune.trainer import Trainer
 from paddlehub.datasets import Flowers
 
 if __name__ == '__main__':
-    transforms = T.Compose([T.Resize((256, 256)), 
-                            T.CenterCrop(224), 
-                            T.Normalize(mean=[0.485, 0.456, 0.406], std = [0.229, 0.224, 0.225])], 
-                            to_rgb=True)
-                            
+    transforms = T.Compose(
+        [T.Resize((256, 256)),
+         T.CenterCrop(224),
+         T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])],
+        to_rgb=True)
+
     flowers = Flowers(transforms)
     flowers_validate = Flowers(transforms, mode='val')
-    model = hub.Module(name='resnet50_vd_imagenet_ssld', label_list=["roses", "tulips", "daisy", "sunflowers", "dandelion"], load_checkpoint=None)
+    model = hub.Module(
+        name='resnet50_vd_imagenet_ssld',
+        label_list=["roses", "tulips", "daisy", "sunflowers", "dandelion"],
+        load_checkpoint=None)
     optimizer = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())
-    trainer = Trainer(model, optimizer, checkpoint_dir='img_classification_ckpt')
-    trainer.train(flowers, epochs=100, batch_size=32, eval_dataset=flowers_validate, save_interval=10)
\ No newline at end of file
+    trainer = Trainer(model, optimizer, checkpoint_dir='img_classification_ckpt', use_gpu=True)
+    trainer.train(flowers, epochs=100, batch_size=32, eval_dataset=flowers_validate, save_interval=10)

paddlehub/datasets/chnsenticorp.py

@@ -57,7 +57,7 @@ class ChnSentiCorp(TextClassificationDataset):
             data_file = 'test.tsv'
         else:
             data_file = 'dev.tsv'
-        super(ChnSentiCorp, self).__init__(
+        super().__init__(
             base_path=base_path,
             tokenizer=tokenizer,
             max_seq_len=max_seq_len,

paddlehub/finetune/trainer.py

@@ -18,6 +18,7 @@ import time
 from collections import defaultdict
 from typing import Any, Callable, Generic, List
 
+import numpy as np
 import paddle
 from visualdl import LogWriter
 
@@ -223,6 +224,8 @@ class Trainer(object):
                         if self.use_vdl:
                             self.log_writer.add_scalar(
                                 tag='TRAIN/{}'.format(metric), step=timer.current_step, value=value)
+                        if isinstance(value, np.ndarray):
+                            value = value.item()
                         print_msg += ' {}={:.4f}'.format(metric, value)
 
                     print_msg += ' lr={:.6f} step/sec={:.2f} | ETA {}'.format(lr, timer.timing, timer.eta)