TFException:要求arg[0]为字符串，但提供了浮点型(Unity3d)

Question

我使用的是带有Unity3d变量的TensorFlow中的语音命令模型示例：

string WAV_INPUT = "wav_data";
        string SOFTMAX_NAME = "labels_softmax";
        string[] outputScoresNames = new string[] { SOFTMAX_NAME };

然后向模型添加输入，如下所示：

 private void recognize(float[] audioFile)
    {
        //labels_softmax:0 output name 
        //labels wav_data:0 input name from model 
        string WAV_INPUT = "wav_data";
        string SOFTMAX_NAME = "labels_softmax";
        string[] outputScoresNames = new string[] { SOFTMAX_NAME };

        int how_many_labels = 4;
        string[] labels = new string[] { "_silence_" , "_unknown_", "stop","go"};

         TextAsset model = Resources.Load("GoStop") as TextAsset;
         TFGraph  graph = new TFGraph();
         graph.Import(model.bytes);

        TFSession session = new TFSession(graph);

        var runner = session.GetRunner();

        runner.AddInput(graph[WAV_INPUT][0], audioFile);
        runner.AddTarget(outputScoresNames);
        runner.Run();
       // float[] recurrent_tensor = runner.Run()[0].GetValue() as float[];

    }

softmax的例外是这样的：

TFException: Expects arg[0] to be string but float is provided
TensorFlow.TFStatus.CheckMaybeRaise (TensorFlow.TFStatus incomingStatus, System.Boolean last) (at <1fe2de69842a4a4ba15256b83cca05f3>:0)
TensorFlow.TFSession.Run (TensorFlow.TFOutput[] inputs, TensorFlow.TFTensor[] inputValues, TensorFlow.TFOutput[] outputs, TensorFlow.TFOperation[] targetOpers, TensorFlow.TFBuffer runMetadata, TensorFlow.TFBuffer runOptions, TensorFlow.TFStatus status) (at <1fe2de69842a4a4ba15256b83cca05f3>:0)
TensorFlow.TFSession+Runner.Run (TensorFlow.TFStatus status) (at <1fe2de69842a4a4ba15256b83cca05f3>:0)
tensor.recognize (System.Single[] audioFile) (at Assets/tensor.cs:51)
tensor.Start () (at Assets/tensor.cs:23)

这是一个造型问题吗?如何管理它才能与TensorFlowSharp协同工作？

Answer 1

我能够通过简单地将张量中的值转换为字符串来解决这个问题。

 graph.Import(model.bytes);
 var session = new TFSession(graph);
 var runner = session.GetRunner();
 TFTensor tft = TFTensor.CreateString(array);
 runner.AddInput(graph[WAV_INPUT][0], tft);
 runner.Fetch(outputScoresNames);
 var output = runner.Run();