upgrade tensorflow to 1.15 and build gpu docker image

Dockerfile

@@ -1,12 +1,24 @@
-FROM python:3.6-buster
+FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04
 
 WORKDIR /usr/src/app
 
+ENV DISTRO ubuntu1804
+ENV CPU_ARCH x86_64
+RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/$DISTRO/$CPU_ARCH/3bf863cc.pub
+
+RUN apt-get update && apt-get install -y python3 python3-pip
+
 COPY requirements.txt ./
-RUN pip install --no-cache-dir -r requirements.txt
+RUN pip3 install --upgrade "pip < 21.0"
+RUN pip3 install --no-cache-dir -r requirements.txt
 
-COPY . .
+RUN apt-get install -y locales
+RUN locale-gen en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US:en
+ENV LC_ALL en_US.UTF-8
 
+COPY . .
 
-CMD [ "python", "./server.py" ]
+CMD [ "python3", "./server.py" ]
 

requirements.txt

@@ -2,6 +2,6 @@ Flask==1.0.2
 Flask-Cors==3.0.9
 gevent==1.2.2
 greenlet==0.4.13
-numpy==1.14.2
-tensorboard==1.8.0
-tensorflow==1.8.0
+numpy
+tensorboard==1.15
+tensorflow-gpu==1.15

server.py

@@ -1,3 +1,5 @@
+import sys
+
 from gevent import monkey
 monkey.patch_all()
 
@@ -8,6 +10,8 @@
 from logging.handlers import RotatingFileHandler
 import logging
 
+
+
 app = Flask(__name__)
 CORS(app)
 
@@ -31,21 +35,23 @@ def log_setup():
 
 log_setup()
 
-m = Model(
-        None, None, None, None, vocab_file,
-        num_units=1024, layers=4, dropout=0.2,
-        batch_size=32, learning_rate=0.0001,
-        output_dir=model_dir,
-        restore_model=True, init_train=False, init_infer=True)
 
 SPLIT_CHARS = ['，', '、', ',', '.', '。', '!', '！', '?', '？', ' ']
 CENSOR_WORDS_DICT = "/data/censor_words.txt"
 
-with open(CENSOR_WORDS_DICT) as censor_words_file:
+with open(CENSOR_WORDS_DICT, encoding='utf-8') as censor_words_file:
     censor_words = [word[:-1] for word in censor_words_file.readlines()]
 logging.info("Loaded %s censor_words" % (len(censor_words)))
 
 
+m = Model(
+        None, None, None, None, vocab_file,
+        num_units=1024, layers=4, dropout=0.2,
+        batch_size=32, learning_rate=0.0001,
+        output_dir=model_dir,
+        restore_model=True, init_train=False, init_infer=True)
+
+
 def all_same(s):
     if len(s) <= 1:
         return True
@@ -55,7 +61,6 @@ def all_same(s):
     return True
 
 
-
 def manual_correct_result(in_str, outputs, scores):
     is_all_same = all_same(in_str)
     for i in range(len(outputs)):
@@ -116,5 +121,6 @@ def chat_couplet_v2(in_str):
     return jsonify({'output': output, 'score': score})
 
 
+logging.info("Starting server ...")
 http_server = WSGIServer(('', 5000), app)
 http_server.serve_forever()