code: def convert_to_interface(arr, interface):
      """Dispatch arrays for different interfaces"""
      import jax.numpy as jnp
      import tensorflow as tf
      import torch
  
      if interface == "autograd":
          return arr
  
      if interface == "jax":
          return jnp.array(arr)
  
      if interface == "tf":
          return tf.constant(arr)
  
      if interface == "torch":
          return torch.tensor(arr)
  
imports: import pytest
  import numpy
  import pennylane
  import pennylane.numpy
  from pennylane.shadows import ClassicalShadow, median_of_means, pauli_expval
label_desc: Use image node_id 5 for calling a global function with example usage: convert_to_interface(arr, interface) and returns: arr, jnp, tf, torch