mediapipe: TFLite model is slow only on iOS

Please make sure that this is a bug and also refer to the troubleshooting, FAQ documentation before raising any issues.

System information (Please provide as much relevant information as possible):

• Have I written custom code (as opposed to using a stock example script provided in MediaPipe): yes
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04, Android 11, iOS 14.4): iOS 14.6
• Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: iPhone Xs
• Browser and version (e.g. Google Chrome, Safari) if the issue happens on browser: n/a
• Programming Language and version ( e.g. C++, Python, Java): C++
• MediaPipe version: Building from master
• Bazel version (if compiling from source): 4.2.1
• Solution ( e.g. FaceMesh, Pose, Holistic ): n/a
• Android Studio, NDK, SDK versions (if issue is related to building in Android environment): n/a
• Xcode & Tulsi version (if issue is related to building for iOS): 12.5

Describe the current behavior:

I have a .tflite model that I’m trying to run within a mediapipe graph. When I run the graph on Android, inference runs quickly. When I run the model directly using Tensorflow Lite 2.7 on iOS, inference runs quickly. However, when I run the graph on iOS, inference runs very slowly (~11 seconds).

Describe the expected behavior:

Inference should be quick on iOS.

Standalone code to reproduce the issue:

Here is the contents of my graph definition:

input_stream: "IMAGE:in_stream"

node: {
  calculator: "ImageToTensorCalculator"
  input_stream: "IMAGE:in_stream"
  output_stream: "TENSORS:input_tensors"
  output_stream: "MATRIX:transform_matrix"
  options: {
    [mediapipe.ImageToTensorCalculatorOptions.ext] {
      output_tensor_width: 640
      output_tensor_height: 640
      keep_aspect_ratio: false
      output_tensor_float_range {
          min: -1.0
          max: 1.0
      }
      border_mode: BORDER_ZERO
    }
  }
}

node {
  calculator: "InferenceCalculator"
  input_stream: "TENSORS:input_tensors"
  output_stream: "TENSORS:detection_tensors"
  options: {
    [mediapipe.InferenceCalculatorOptions.ext] {
      model_path: "my-model.tflite"
      delegate { tflite {} }
    }
  }
}

If inspecting the tflite model itself would be useful, I can check with my team that it would be okay to upload that. In the meantime, I used the tflite model visualizer script to inspect the ops:

Does anything stand out here as an op that would be slow?

Other info / Complete Logs : Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached