终止于 (StatusCode.UNAVAILABLE, Socket closed)> 的 RPC 会合

Rendezvous of RPC that terminated with (StatusCode.UNAVAILABLE, Socket closed)>

我已经部署了一个服务于多个模型的 tensorflow 服务器。 客户端代码就像 client.py 这样,我调用预测函数。

channel = implementations.insecure_channel(host, port)
stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)
request = predict_pb2.PredictRequest()

def predict(data, shape, model_name, signature_name="predict"):
    request.model_spec.name = model_name
    request.model_spec.signature_name = signature_name
    request.inputs['image'].CopyFrom(tf.contrib.util.make_tensor_proto(data, shape=shape))
    result = stub.Predict(request, 10.0)
    return result.outputs['prediction'].float_val[0]

我有大约 100 个具有相同配置的客户端。 这是调用 predict 函数的示例代码:

from client import predict
while True:
    print(predict(data, shape, model_name))
    # time.sleep some while

起初,当我运行客户端代码时,我可以正确收到响应。 但是几个小时后,客户端崩溃并出现错误

_Rendezvous of RPC that terminated with (StatusCode.UNAVAILABLE, Socket closed)

我已尝试将我的客户端代码修改为

def predict(data, shape, model_name, signature_name="predict"):
    channel = implementations.insecure_channel(host, port)
    stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)
    request = predict_pb2.PredictRequest()
    request.model_spec.name = model_name
    request.model_spec.signature_name = signature_name
    request.inputs['image'].CopyFrom(tf.contrib.util.make_tensor_proto(data, shape=shape))
    result = stub.Predict(request, 10.0)
    return result.outputs['prediction'].float_val[0]

这意味着每次调用 predict 函数时,我都会尝试与 tfs 服务器建立连接。但是这段代码也像以前一样失败了。

那么遇到这种情况应该怎么办呢?

最后我在 return 之前添加了一个 channel.close(),它工作正常。