fix dependency

Dockerfile

@@ -8,7 +8,7 @@ WORKDIR /home/user/app
 
 RUN sed -i 's http://deb.debian.org http://cdn-aws.deb.debian.org g' /etc/apt/sources.list && sed -i 's http://archive.ubuntu.com http://us-east-1.ec2.archive.ubuntu.com g' /etc/apt/sources.list && sed -i '/security/d' /etc/apt/sources.list && apt-get update && apt-get install -y 	git 	git-lfs 	ffmpeg 	libsm6 	libxext6 	cmake 	libgl1-mesa-glx 	&& rm -rf /var/lib/apt/lists/* 	&& git lfs install
 
-RUN pip install --no-cache-dir Cython "gradio==3.28.3" "torch==1.10.1"  jieba subword-nmt sacremoses
+RUN pip install --no-cache-dir Cython "gradio==3.28.3" "torch==1.10.1"  jieba subword-nmt sacremoses transformers
 
 RUN git clone --recurse-submodules https://github.com/thu-coai/DA-Transformer.git && cd DA-Transformer && pip install -e . && cd dag_search && python3 setup.py build_ext --inplace && pip install -e . && cd ../..
 

app.py

@@ -15,8 +15,6 @@ import matplotlib.pyplot as plt
 import fairseq
 
 logger = logging.getLogger(__name__)
-logger.info("start init")
-
 
 fairseq_path = os.path.dirname(os.path.dirname(fairseq.__file__))
 
@@ -202,6 +200,7 @@ def generate_detail(model, model_input):
 
 def load_model(model_name):
     assert model_name in available_models
+    logger.info(f"start loading {model_name}")
     model = available_models[model_name]['class'].from_pretrained(**available_models[model_name]['args'])
     return model
 
@@ -513,7 +512,6 @@ def build_tab_detail():
     return load
 
 def build_demo():
-    logger.info(f"build enter")
     with gr.Blocks(title="DA-Transformer Demo", theme=gr.themes.Base(), css=css) as demo:
         gr.Markdown(notice_markdown)
 
@@ -543,8 +541,6 @@ if __name__ == "__main__":
 
     workers = concurrent.futures.ThreadPoolExecutor(max_workers=1)
     demo = build_demo()
-    logger.info(f"build over")
-
     demo.queue(concurrency_count=args.concurrency_count, status_update_rate=10,
                api_open=False).launch(server_name=args.host, server_port=args.port,
                                       share=args.share, max_threads=5)