Kernel restarting during Tensorflow Lite model Inference (Python)

I am trying to use TensorFlow Lite model to make predictions for the input data. The Neural Network was trained using Keras and then was converted to TFLite standard model as following:

keras_file = "pruned_model.h5"
converter = lite.TocoConverter.from_keras_model_file(keras_file)
tflite_model = converter.convert()

And saved it locally:

TFLITE_MODEL = "dts-model.tflite"
open(TFLITE_MODEL, "wb").write(tflite_model)

Then I loaded the model into Interpreter representation, so the inference process can run on it:

tflite_interpreter = tf.lite.Interpreter(model_path=TFLITE_MODEL)

# extracted input and output details
input_details = tflite_interpreter.get_input_details()
output_details = tflite_interpreter.get_output_details()

#created random sample data matching input shape
input_data = np.array(np.random.random_sample(input_shape), dtype=np.float32)

And when trying to run the following code, the notebook Kernel keeps crashing.

tflite_interpreter.set_tensor(input_details[0]['index'], input_data)

Kernel crash/restart screenshot

EDIT: Here's the terminal traceback of the kernel. Before executing this code when I run the interpreter, it is initialized, and after executing the above, it restarts.

INFO: Initialized TensorFlow Lite runtime.
[I 09:04:00.289 LabApp] KernelRestarter: restarting kernel (1/5), keep random ports
kernel d960c8d0-d14d-416a-bee3-3549c6a11c76 restarted

And here's the list of kernels for Jupyter:

jupyter kernelspec list
>> Available kernels:
>> python3    /home/username/anaconda3/envs/LearningML/share/jupyter/kernels/python3

I am not exactly sure why is this happening.

1) Why do the kernels generally restart and what is the reason for my kernel's restart?
2) Is there any better way I can run TFLite model inference and get outputs?

Thanks!