def test_feedback(self):
        test_file = "test_feedback.txt"
        feedback_file = MachineLoader.feedback(machines.number_recognizer,
                                               None,
                                               file_name=test_file)
        if os.path.isfile(feedback_file):
            os.remove(feedback_file)

        data = [0] * 64
        target = [0]
        feedback = target + data
        # create file
        MachineLoader.feedback(machines.number_recognizer,
                               feedback,
                               file_name=test_file)
        # append file
        MachineLoader.feedback(machines.number_recognizer,
                               feedback,
                               file_name=test_file)

        with open(feedback_file, mode="rb") as r:
            lines = r.readlines()
            self.assertEqual(2, len(lines))

        os.remove(feedback_file)
예제 #2
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            MachineLoader.feedback(machines.number_recognizer, feedback)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
예제 #3
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            MachineLoader.feedback(machines.number_recognizer, feedback)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
예제 #4
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            # save feedback to file
            MachineLoader.feedback(machines.number_recognizer, feedback)

            # online training
            machine = MachineLoader.load(machines.number_recognizer)
            machine.partial_fit(feedback[1:], [feedback[0]])
            MachineLoader.save(machines.number_recognizer, machine)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
예제 #5
0
    def post(self):
        data = self.get_arguments("data[]")
        result = ""

        feedback = Validator.validate_feedback(data)
        if len(feedback) > 0:
            # save feedback to file
            MachineLoader.feedback(machines.number_recognizer, feedback)

            # online training
            machine = MachineLoader.load(machines.number_recognizer)
            machine.partial_fit(feedback[1:], [feedback[0]])
            MachineLoader.save(machines.number_recognizer, machine)
        else:
            result = "feedback format is wrong."

        resp = {"result": result}
        self.write(resp)
    def test_feedback(self):
        test_file = "test_feedback.txt"
        feedback_file = MachineLoader.feedback(machines.number_recognizer, None, file_name=test_file)
        if os.path.isfile(feedback_file):
            os.remove(feedback_file)

        data = [0] * 64
        target = [0]
        feedback = target + data
        # create file
        MachineLoader.feedback(machines.number_recognizer, feedback, file_name=test_file)
        # append file
        MachineLoader.feedback(machines.number_recognizer, feedback, file_name=test_file)

        with open(feedback_file, mode="rb") as r:
            lines = r.readlines()
            self.assertEqual(2, len(lines))

        os.remove(feedback_file)