update the readme.

Signed-off-by: wxywb <xy.wang@zilliz.com>

README.md

@@ -17,28 +17,19 @@ This operator generates the caption with [CLIPReward](https://arxiv.org/abs/2205
 
 Load an image from path './animals.jpg' to generate the caption. 
 
- *Write the pipeline in simplified style*:
+*Write a pipeline with explicit inputs/outputs name specifications:*
 
 ```python
-import towhee
+from towhee.dc2 import pipe, ops, DataCollection
 
-towhee.glob('./animals.jpg') \
-      .image_decode() \
-      .image_captioning.clip_caption_reward(model_name='clipRN50_clips_grammar') \
-      .show()
-```
-<img src="./cap.png" alt="result1" style="height:20px;"/>
-
-*Write a same pipeline with explicit inputs/outputs name specifications:*
-
-```python
-import towhee
+p = (
+    pipe.input('url')
+    .map('url', 'img', ops.image_decode.cv2_rgb())
+    .map('img', 'text', ops.image_captioning.clip_caption_reward(model_name='clipRN50_clips_grammar'))
+    .output('img', 'text')
+)
 
-towhee.glob['path']('./animals.jpg') \
-      .image_decode['path', 'img']() \
-      .image_captioning.clip_caption_reward['img', 'text'](model_name='clipRN50_clips_grammar') \
-      .select['img', 'text']() \
-      .show()
+DataCollection(p('./animals.jpg')).show()
 ```
 <img src="./tabular.png" alt="result2" style="height:60px;"/>
 

clip_caption_reward.py

@@ -80,6 +80,7 @@ class ClipCaptionReward(NNOperator):
 
         self.model = TransformerModel(opt)
         self.model.load_state_dict(raw_state_dict)
+        self.model.to(self.device)
 
         self.image_mean  = (
             torch.Tensor([0.48145466, 0.4578275, 0.40821073])