title: Error while inferencing a LSTM model with the help of onnx-runtime . Invalid Argument Error
body: <p>I have exported a LSTM model from pytorch to onnx . The model takes sequences of length 200. It has hidden state size 256 , number of layers = 2.The forward function takes input size of (batches , sequencelength) as input along with a tuple consisting of hidden state and cell state. I am getting an error while inferencing the model with onnx runtime. hidden state and cell state dimensions are same.</p>
  <pre><code>ioio1 = np.random.rand(1,200)
  ioio2 = np.zeros((2,1,256),dtype = np.float)
  pred = runtime_session.run([output_name],{runtime_session.get_inputs()[0].name:ioio1,
                                            runtime_session.get_inputs()[1].name :ioio2,
                                            runtime_session.get_inputs()[2].name : ioio2})
  </code></pre>
  <pre><code>InvalidArgument                           Traceback (most recent call last)
  &lt;ipython-input-204-3928823f661e&gt; in &lt;module&gt;()
        1 pred = runtime_session.run([output_name],{runtime_session.get_inputs()[0].name:ioio1,
        2                                           runtime_session.get_inputs()[1].name :ioio2,
  ----&gt; 3                                           runtime_session.get_inputs()[2].name : ioio2})
  
  /usr/local/lib/python3.6/dist-packages/onnxruntime/capi/session.py in run(self, output_names, input_feed, run_options)
      109             output_names = [output.name for output in self._outputs_meta]
      110         try:
  --&gt; 111             return self._sess.run(output_names, input_feed, run_options)
      112         except C.EPFail as err:
      113             if self._enable_fallback:
  
  InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Unexpected input data type. Actual: (N11onnxruntime17PrimitiveDataTypeIdEE) , expected: (N11onnxruntime17PrimitiveDataTypeIlEE)
  
  </code></pre>