tfjs: Error: TensorArray dtype is float32 but tensor has dtype undefined

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TensorFlow.js version

tensorflowjs 0.5.6

Dependency versions:
  keras 2.1.6
  tensorflow 1.9.0

Browser version

Mac + Chrome 68.0.3440.84 64bit (Latest version)

Describe the problem or feature request

With the latest version of tfjs,  I can  succssfully converte 
ssd_mobilenet_v1_coco_2018_01_28 to web model and load it. 
(This is the Object Detection model)
But when I try to run model.executeAsync(), 
the error as below happened.

tf-converter.esm.js?:formatted:6254 Uncaught (in promise) Error: TensorArray dtype is float32 but tensor has dtype undefined
    at e.scatter (tf-converter.esm.js?:formatted:6254)
    at eval (tf-converter.esm.js?:formatted:6388)
    at eval (tf-converter.esm.js?:formatted:144)
    at Object.eval [as next] (tf-converter.esm.js?:formatted:157)
    at eval (tf-converter.esm.js?:formatted:64)
    at new Promise (<anonymous>)
    at __awaiter (tf-converter.esm.js?:formatted:43)
    at executeOp$2 (tf-converter.esm.js?:formatted:6295)
    at executeOp$15 (tf-converter.esm.js?:formatted:6772)
    at eval (tf-converter.esm.js?:formatted:7070)

Code to reproduce the bug / link to feature request

The reproduce procedure is simple.
1. converte ssd_mobilenet_v1_coco_2018_01_28
2. load and run executeAsync()
 
My code is as below, it's written by React JSX:

 componentDidMount = async () => {
    this.model = new Model()
    await this.model.load()
    const tensor = tf.fromPixels(this.image).toFloat().expandDims(0)
    this.model.model.executeAsync({
      image_tensor: tensor,
    }).then((result) => {
     // TODO
    })
  }

@dsmilkov

I tried to read the sourcecode and find the error may happened in 
tfjs-converter/src/executor/tensor_array.ts
  scatter(indices: number[], tensor: Tensor) {
    if (tensor.dtype !== this.dtype) {
      throw new Error(`TensorArray dtype is ${
          this.dtype} but tensor has dtype ${tensor.dtype}`);
    }
    // something else......
  }

I set the breakpoint here and find the input parameter 'tensor' is not ts.Tensor but the Array.
So tensor.dtype is undefined.
Is this caused by my misuse or bugs? 
Please help, thanks.