From model-runner I get the error ProtobufLoader.cpp line: 33 message: There is no tensor registered with name input_data. My graph (ONNX) looks like this:
graph(%input_data : Float(1, 2)
      %1 : Float(8, 2)
      %2 : Float(8)
      %3 : Float(8, 8)
      %4 : Float(8)
      %5 : Float(8, 8)
      %6 : Float(8)
      %7 : Float(1, 8)
      %8 : Float(1)) {
  %9 : Float(1, 8) = onnx::Gemm[alpha=1, beta=1, transB=1](%input_data, %1, %2), scope: FeedForwardNN/Linear
  %10 : Float(1, 8) = onnx::Relu(%9), scope: FeedForwardNN/ReLU
  %11 : Float(1, 8) = onnx::Gemm[alpha=1, beta=1, transB=1](%10, %3, %4), scope: FeedForwardNN/ReLU
  %12 : Float(1, 8) = onnx::Relu(%11), scope: FeedForwardNN/ReLU
  %13 : Float(1, 8) = onnx::Gemm[alpha=1, beta=1, transB=1](%12, %5, %6), scope: FeedForwardNN/ReLU
  %14 : Float(1, 8) = onnx::Relu(%13), scope: FeedForwardNN/ReLU
  %15 : Float(1, 1) = onnx::Gemm[alpha=1, beta=1, transB=1](%14, %7, %8), scope: FeedForwardNN/ReLU
  %output : Float(1, 1) = onnx::Sigmoid(%15), scope: FeedForwardNN/Sigmoid
  return (%output);
}

The command line looks like this:
/bin $ ./model-runner -model=./ffnn.onnx -network-name="ffnn" -cpu -emit-bundle=./ -verbose
I have confirmed that the graph (ONNX) is constructed correctly by importing it in Python, then using the caffe2 backend to run inference.
I have also tried creating the init_net.pb and predict_net.pb, but I get the same error when specifying *.pb instead of *.onnx
I am guessing this has something to do with not specifying the input for model-runner (the way we do, for instance, with image-classifier). But then again, there is no way to specify input for model-runner.
Any ideas would be appreciated.
Thanks!