# Copyright (c) 2020 PaddlePaddle Authors. 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. # pylint: disable=doc-string-missing import grpc import numpy as np from numpy import * import logging from .proto import pipeline_service_pb2 from .proto import pipeline_service_pb2_grpc _LOGGER = logging.getLogger(__name__) class PipelineClient(object): def __init__(self): self._channel = None def connect(self, endpoint): self._channel = grpc.insecure_channel(endpoint) self._stub = pipeline_service_pb2_grpc.PipelineServiceStub( self._channel) def _pack_data_for_infer(self, feed_dict): req = pipeline_service_pb2.Request() for key, value in feed_dict.items(): if not isinstance(value, str): raise TypeError("only str type is supported.") req.key.append(key) req.value.append(value) return req def predict(self, feed_dict, fetch): if not isinstance(feed_dict, dict): raise TypeError( "feed must be dict type with format: {name: value}.") if not isinstance(fetch, list): raise TypeError( "fetch_with_type must be list type with format: [name].") req = self._pack_data_for_infer(feed_dict) resp = self._stub.inference(req) if resp.ecode != 0: return {"ecode": resp.ecode, "error_info": resp.error_info} fetch_map = {"ecode": resp.ecode} for idx, key in enumerate(resp.key): if key not in fetch: continue data = resp.value[idx] try: data = eval(resp.value[idx]) except Exception as e: pass fetch_map[key] = data return fetch_map