add logging for clip.

Signed-off-by: jinlingxu06 <jinling.xu@zilliz.com>

clip.py

@@ -12,18 +12,26 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import sys
+import os
 from pathlib import Path
 import torch
 from torch import nn
 from torchvision import transforms
 
+import logging
+import warnings
 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
 from transformers import CLIPTokenizer, CLIPTextModel ,CLIPModel,CLIPProcessor
+from transformers import logging as t_logging
 # from towhee.dc2 import accelerate
 
+log = logging.getLogger('run_op')
+warnings.filterwarnings('ignore')
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+t_logging.set_verbosity_error()
 
 def create_model(model_name, modality, checkpoint_path, device):
     hf_clip_model = CLIPModel.from_pretrained(model_name)
@@ -159,13 +167,16 @@ class Clip(NNOperator):
 
     @staticmethod
     def supported_model_names(format: str = None):
-        if format == 'pytorch' or format == 'torchscript' or format == 'onnx':
-            model_list = [
-                'clip_vit_base_patch16',
-                'clip_vit_base_patch32',
-                'clip_vit_large_patch14',
-                'clip_vit_large_patch14_336'
-            ]
+        full_list = [
+            'clip_vit_base_patch16',
+            'clip_vit_base_patch32',
+            'clip_vit_large_patch14',
+            'clip_vit_large_patch14_336'
+        ]
+        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