update the BLIP operator.

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

README.md

@@ -77,6 +77,38 @@ Create the operator via the following factory method
 
 An image-text embedding operator takes a [towhee image](link/to/towhee/image/api/doc) or string as input and generate an embedding in ndarray.
 
+***save_model(format='pytorch', path='default')***
+
+Save model to local with specified format.
+
+**Parameters:**
+
+***format***: *str*
+
+​	The format of saved model, defaults to 'pytorch'.
+
+***path***: *str*
+
+​	The path where model is saved to. By default, it will save model to the operator directory.
+
+
+```python
+from towhee import ops
+
+op = ops.image_text_embedding.blip(model_name='blip_itm_base', modality='image').get_op()
+op.save_model('onnx', 'test.onnx')
+```
+<br />
+
+
+
+**Parameters:**
+
+​	***data:*** *towhee.types.Image (a sub-class of numpy.ndarray)*  or *str*
+
+​  The data (image or text based on specified modality) to generate embedding.	
+
+
 
 **Parameters:**
 

__init__.py

@@ -15,5 +15,5 @@
 from .blip import Blip
 
 
-def blip(model_name: str, modality: str):
-    return Blip(model_name, modality)
+def blip(model_name: str, modality: str, device:str = None, checkpoint_path:str = None):
+    return Blip(model_name, modality, device, checkpoint_path)

blip.py

@@ -76,7 +76,7 @@ class BLIPModelText(nn.Module):
         return text_features    
 
 class Model:
-    def __init__(self, model_name, modality, checkpoint_path, device):
+    def __init__(self, model_name, modality, device, checkpoint_path):
         self.model = create_model(model_name, modality, checkpoint_path, device)
         self.device = device
 
@@ -165,10 +165,11 @@ class Blip(NNOperator):
 
     @staticmethod
     def supported_model_names(format: str = None):
-        if format == 'pytorch' or format == 'torchscript' or format == 'onnx':
-            model_list = [
-                'blip_itm_base',
-            ]
+        full_list = ['blip_itm_base']
+        if format == None:
+            model_list = full_list
+        elif format == 'pytorch' or format == 'torchscript' or format == 'onnx':
+            model_list = full_list
         else:
             log.error(f'Invalid format "{format}". Currently supported formats: "pytorch", "torchscript".')
         return model_list