I tried to convert my Pytorch models to TensorFlow Lite with ONNX. But my inference time from TensorFlow Lite is twice as slow as Tensorflow and Pytorch. I run TensorFlow Lite model in google colab and this is my first time using TensorFlow Lite.
Here is my code to convert from Tensorflow to TensorFlow Lite:
converter = tf.lite.TFLiteConverter.from_saved_model("model/")
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.target_spec.supported_types = [tf.float16]
model_lite = converter.convert()

with open('model.tflite', 'wb') as f:
    f.write(model_lite)

I  used time module from Python to measure the latency of frameworks. I don’t know why my Lite version is slower than the others. Any suggestions will help me a lot.