code: def compute_accuracy_drop(
      tensor_1: Any, tensor_2: Any, y: Any
  ) -> float:
      assert y is not None, (
          "No label found in the dataloader provided. "
          "To use accuracy metric, you must set also the labels"
      )
      tensor_1, tensor_2, y = map(
          convert_to_numpy, (tensor_1, tensor_2, y)
      )
      accuracy_1 = np.mean(tensor_1.argmax(axis=-1) == y)
      accuracy_2 = np.mean(tensor_2.argmax(axis=-1) == y)
      return accuracy_1 - accuracy_2
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/measures/utils.py
imports: import time
  from typing import Tuple, List, Union, Any
  import numpy
  from loguru import logger
  from nebullvm.config import ONNX_PROVIDERS
  from nebullvm.core.models import Device, DeviceType
  from nebullvm.operations.inference_learners.base import BaseInferenceLearner
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch, Module
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.onnx import convert_to_numpy, get_input_names, get_output_names
label_desc: Use image node_id 6 for calling a global function with example usage: compute_accuracy_drop(tensor_1, tensor_2, y) and returns: unknown