def config_with_file(configs: dict):
'''
Config `cv_module_info` and `nlp_module_info` by configs.
Args:
configs(dict): Module info and configs
Examples:
.. code-block:: python
configs = {'lac': {'version': 1.0.0, 'category': nlp}}
config_with_file(configs=configs)
'''
for key, value in configs.items():
if "CV" == value["category"]:
cv_module_info.add_module(key, {key: value})
elif "NLP" == value["category"]:
nlp_module_info.add_module(key, {key: value})
v2_module_info.add_module(key, {key: value})
logger = log.get_file_logger(filename)
logger.info("%s==%s" % (key, value["version"]))
def run(configs: dict = None, port: int = 8866):
'''
Run flask instance for PaddleHub-Serving
Args:
configs(dict): module info and configs
port(int): the port of the webserver
Examples:
.. code-block:: python
configs = {'lac': {'version': 1.0.0, 'category': nlp}}
run(configs=configs, port=8866)
'''
logger = log.get_file_logger(filename)
if configs is not None:
config_with_file(configs)
else:
logger.error("Start failed cause of missing configuration.")
return
my_app = create_app(init_flag=True)
my_app.run(host="0.0.0.0", port=port, debug=False, threaded=False)
log.logger.info("PaddleHub-Serving has been stopped.")
def __init__(self):
self.frontend = None
self.backend = None
filename = 'HubServing-%s.log' % time.strftime("%Y_%m_%d",
time.localtime())
self.logger = log.get_file_logger(filename)
if __name__ == '__main__':
argv = sys.argv
modules_info = json.loads(argv[1])
gpu_index = argv[2]
addr = argv[3]
os.environ['CUDA_VISIBLE_DEVICES'] = gpu_index
import paddlehub as hub
from paddlehub.serving.http_server import package_result
from paddlehub.utils import log
filename = 'HubServing-%s.log' % time.strftime("%Y_%m_%d",
time.localtime())
logger = log.get_file_logger(filename)
logger.logger.handlers = logger.logger.handlers[0:1]
modules_pred_info = {}
for module_name, module_info in modules_info.items():
init_args = module_info.get('init_args', {})
init_args.update({'name': module_name})
module = hub.Module(**init_args)
method_name = module.serving_func_name
serving_method = getattr(module, method_name)
predict_args = module_info.get('predict_args', {})
modules_pred_info.update({
module_name: {
'predict_args': predict_args,
'serving_method': serving_method
}
def create_app(init_flag: bool = False, configs: dict = None):
'''
Start one flask instance and ready for HTTP requests.
Args:
init_flag(bool): Whether the instance need to be initialized with
`configs` or not
configs(dict): Module configs for initializing.
Returns:
One flask instance.
Examples:
.. code-block:: python
create_app(init_flag=False, configs=None)
'''
if init_flag is False:
if configs is None:
raise RuntimeError("Lack of necessary configs.")
config_with_file(configs)
app_instance = Flask(__name__)
app_instance.config["JSON_AS_ASCII"] = False
app_instance.logger = log.get_file_logger(filename)
@app_instance.route("/", methods=["GET", "POST"])
def index():
'''
Provide index page.
'''
return '暂不提供可视化界面，请直接使用脚本进行请求。<br/>No visual ' \
'interface is provided for the time being, please use the' \
' python script to make a request directly.'
@app_instance.before_request
def before_request():
'''
Add id info to `request.data` before request.
'''
request.data = {"id": utils.md5(request.remote_addr + str(time.time()))}
@app_instance.route("/predict/<module_name>", methods=["POST"])
def predict_serving_v2(module_name: str):
'''
Http api for predicting.
Args:
module_name(str): Module name for predicting.
Returns:
Result of predicting after packaging.
'''
if module_name in v2_module_info.modules:
module_info = v2_module_info.get_module_info(module_name)
else:
msg = "Module {} is not available.".format(module_name)
return package_result("111", msg, "")
inputs = request.json
if inputs is None:
results = "This usage is out of date, please use 'application/json' as content-type to post to /predict/%s. See 'https://github.com/PaddlePaddle/PaddleHub/blob/release/v1.6/docs/tutorial/serving.md' for more details." % (
module_name)
return package_result("112", results, "")
results = predict_v2(module_info, inputs)
return results
return app_instance
def create_app(client_port: int = 5559, modules_name: list = []):
'''
Start one flask instance and ready for HTTP requests.
Args:
client_port(str): port of zmq backend address
modules_name(list): the name list of modules
Returns:
One flask instance.
Examples:
.. code-block:: python
create_app(client_port='5559')
'''
app_instance = Flask(__name__)
app_instance.config["JSON_AS_ASCII"] = False
app_instance.logger = log.get_file_logger(filename)
pid = os.getpid()
@app_instance.route("/", methods=["GET", "POST"])
def index():
'''
Provide index page.
'''
return '暂不提供可视化界面，请直接使用脚本进行请求。<br/>No visual ' \
'interface is provided for the time being, please use the' \
' python script to make a request directly.'
@app_instance.before_request
def before_request():
'''
Add id info to `request.data` before request.
'''
request.data = {
"id": utils.md5(request.remote_addr + str(time.time()))
}
@app_instance.route("/predict/<module_name>", methods=["POST"])
def predict_serving_v3(module_name: str):
'''
Http api for predicting.
Args:
module_name(str): Module name for predicting.
Returns:
Result of predicting after packaging.
'''
if module_name not in modules_name:
msg = "Module {} is not available.".format(module_name)
return package_result("111", "", msg)
inputs = request.json
if inputs is None:
results = "This usage is out of date, please use 'application/json' as content-type to post to /predict/%s. See 'https://github.com/PaddlePaddle/PaddleHub/blob/release/v1.6/docs/tutorial/serving.md' for more details." % (
module_name)
return package_result("112", results, "")
inputs = {'module_name': module_name, 'inputs': inputs}
port_str = 'tcp://localhost:%s' % client_port
client = InferenceClientProxy.get_client(pid, port_str)
results = client.send_req(inputs)
return package_result("000", results, "")
return app_instance