无法将类型<class'werkzeug.datastructures.File.Storage>的对象转换为张量

jan*_*912 5 python machine-learning werkzeug tensorflow tensorflow-serving

我正在编写一个使用flask框架的客户端python文件,并在docker机器中运行它。因此,这需要一个输入文件并产生输出。但是它引发了无法转换为张量的错误。

tf.app.flags.DEFINE_string('server', 'localhost:9000', 'PredictionService host:port')
FLAGS = tf.app.flags.FLAGS

app = Flask(__name__)

class mainSessRunning():

    def __init__(self):
        host, port = FLAGS.server.split(':')
        channel = implementations.insecure_channel(host, int(port))
        self.stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)

        self.request = predict_pb2.PredictRequest()
        self.request.model_spec.name = 'modelX'
        self.request.model_spec.signature_name = 'prediction'

    def inference(self, val_x):
        data = val_x
        self.request.inputs['input'].CopyFrom(tf.contrib.util.make_tensor_proto(data))
        result = self.stub.Predict(self.request, 5.0)
        return result

run = mainSessRunning()


# Define a route for the default URL, which loads the form
@app.route('/pred', methods=['POST'])
def pred():
    request_data = request.files['file']
    result = run.inference(request_data)
    rs = json_format.MessageToJson(result)
    return jsonify({'result':rs})
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错误提示:

TypeError:无法将类型(类“ werkzeug.datastructures.File.Storage”)的对象转换为张量。内容:(文件存储:u'File.txt'('text / plain'))。考虑将元素强制转换为受支持的类型

这行产生错误:

self.request.inputs ['input']。CopyFrom(tf.contrib.util.make_tensor_proto(data))

图片