update the operator.

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

__init__.py

@@ -0,0 +1,19 @@
+# Copyright 2021 Zilliz. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .taiyi import Taiyi
+
+
+def taiyi(model_name: str, modality: str):
+    return Taiyi(model_name, modality)

taiyi.py

@@ -15,6 +15,16 @@ import torch
 from transformers import BertForSequenceClassification, BertConfig, BertTokenizer
 from transformers import CLIPProcessor, CLIPModel
 
+import sys
+from pathlib import Path
+import torch
+from torchvision import transforms
+
+from towhee.types.image_utils import to_pil
+from towhee.operator.base import NNOperator, OperatorFlag
+from towhee.types.arg import arg, to_image_color
+from towhee import register
+
 @register(output_schema=['vec'])
 class Taiyi(NNOperator): 
     """
@@ -23,10 +33,13 @@ class Taiyi(NNOperator):
     def __init__(self, model_name: str, modality: str):
         self.modality = modality
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
-        self.text_tokenizer = BertTokenizer.from_pretrained("IDEA-CCNL/Taiyi-CLIP-Roberta-large-326M-Chinese")
-        self.text_encoder = BertForSequenceClassification.from_pretrained("IDEA-CCNL/Taiyi-CLIP-Roberta-large-326M-Chinese").eval()
-        self.clip_model = CLIPModel.from_pretrained("openai/clip-vit-large-patch14")
-        self.processor = CLIPProcessor.from_pretrained("openai/clip-vit-large-patch14")
+        config = self._configs()[model_name]
+
+        self.text_tokenizer = BertTokenizer.from_pretrained(config['tokenizer'])
+        self.text_encoder = BertForSequenceClassification.from_pretrained(config['text_encoder']).eval()
+
+        self.clip_model = CLIPModel.from_pretrained(config['clip_model'])
+        self.processor = CLIPProcessor.from_pretrained(config['processor'])
 
     def inference_single_data(self, data):
         if self.modality == 'image':
@@ -52,14 +65,29 @@ class Taiyi(NNOperator):
             return results
 
     def _inference_from_text(self, text):
-        self.text = self.text_tokenizer(text, return_tensors='pt', padding=True)['input_ids'].to(self.device)
-        text_features = text_encoder(text).logits
+        tokens = self.text_tokenizer(text, return_tensors='pt', padding=True)['input_ids'].to(self.device)
+        text_features = self.text_encoder(tokens).logits
         return text_features
 
     @arg(1, to_image_color('RGB'))
     def _inference_from_image(self, img):
-        image = to_pil(image)
-        image = self.processor(images=image.raw), return_tensors="pt")
-        image_features = clip_model.get_image_features(**image)
+        image = to_pil(img)
+        image = self.processor(images=image, return_tensors="pt")
+        image_features = self.clip_model.get_image_features(**image)
         return image_features
  
+    def _configs(self):
+        config = {}
+        config['taiyi-clip-roberta-102m-chinese'] = {}
+        config['taiyi-clip-roberta-102m-chinese']['tokenizer'] = 'IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese'
+        config['taiyi-clip-roberta-102m-chinese']['text_encoder'] = 'IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese'
+        config['taiyi-clip-roberta-102m-chinese']['clip_model'] = 'openai/clip-vit-base-patch32'
+        config['taiyi-clip-roberta-102m-chinese']['processor'] = 'openai/clip-vit-base-patch32'
+
+        config['taiyi-clip-roberta-large-326m-chinese'] = {}
+        config['taiyi-clip-roberta-large-326m-chinese']['tokenizer'] = 'IDEA-CCNL/Taiyi-CLIP-Roberta-large-326M-Chinese'
+        config['taiyi-clip-roberta-large-326m-chinese']['text_encoder'] = 'IDEA-CCNL/Taiyi-CLIP-Roberta-large-326M-Chinese' 
+        config['taiyi-clip-roberta-large-326m-chinese']['clip_model'] = 'openai/clip-vit-large-patch14'
+        config['taiyi-clip-roberta-large-326m-chinese']['processor'] = 'openai/clip-vit-large-patch14'
+        return config
+