Tensorflow服务于古董数据集的预测

Question

我遵循Tensorflow排名古老的例子Tutorial: TF-Ranking for sparse features，我对使用Tensorflow服务获得预测感兴趣。我首先更改了代码并添加了以下函数

def make_serving_input_fn():
    context_feature_spec = tf.feature_column.make_parse_example_spec(context_feature_columns().values())
    example_feature_spec = tf.feature_column.make_parse_example_spec(example_feature_columns().values())
  
    feature_spec = {}
    feature_spec.update(example_feature_spec)
    feature_spec.update(context_feature_spec)
    return tf.estimator.export.build_parsing_serving_input_receiver_fn(
        feature_spec)

此外，我还添加了一个导出：

eval_spec =  tf.estimator.EvalSpec(
          name="eval",
          input_fn=eval_input_fn,
          exporters=tf.estimator.LatestExporter(
            "latest_exporter",
            serving_input_receiver_fn=make_serving_input_fn()),
          throttle_secs=15)

为了使模型运行，我运行了以下命令：

docker run -it -p 8501:8501 --mount type=bind,source=/home/code/models/antique/export/latest_exporter/1612010189,target=/models/antique/1/ -e MODEL_NAME=antique -t tensorflow/serving

对于预测，我添加了以下代码：

def predict(instances): 
    request = predict_pb2.PredictRequest()
    t_proto = tf.make_tensor_proto(instances)
    request.inputs['examples'].CopyFrom(t_proto)
    request.model_spec.signature_name = 'predict'
    request.model_spec.name = 'antique'

    tf_serve_host ="172.17.0.3:8500"
    timeout_in_secs = 100  
    channel = insecure_channel(tf_serve_host)
    stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)

    result = stub.Predict(request, timeout_in_secs)
    predictions = np.array(result.outputs['output'].float_val)

    return predictions

然而，当我试图获得预测时：

raw_dataset = tf.data.TFRecordDataset([DATA_PATH])
for e in raw_dataset.take(1):
    ELWC = input_pb2.ExampleListWithContext()
    single_example = ELWC.FromString(e.numpy())

然后：

predict([single_example.SerializeToString()])

我得到以下错误：

_InactiveRpcError: <_InactiveRpcError of RPC that terminated with:
    status = StatusCode.INVALID_ARGUMENT
    details = "Could not parse example input, value: '
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谁能帮我解释一下我做错了什么