docstr: this compares 2 influence implementations on a trained 2-layer NN model.
  the implementations we compare are `NaiveInfluenceFunction` and
  `ArnoldiInfluenceFunction`. because the model is not trained, calculations
  are not numerically stable, and so we can only project to a low dimension (2).
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code: def test_compare_implementations_random_model_and_data(
      self,
      influence_constructor_1: Callable,
      influence_constructor_2: Callable,
      delta: float,
      mode: str,
      unpack_inputs: bool,
      use_gpu: Union[bool, str],
  ):
      """
      this compares 2 influence implementations on a trained 2-layer NN model.
      the implementations we compare are `NaiveInfluenceFunction` and
      `ArnoldiInfluenceFunction`. because the model is not trained, calculations
      are not numerically stable, and so we can only project to a low dimension (2).
      """
      self._test_compare_implementations(
          "random",
          influence_constructor_1,
          influence_constructor_2,
          delta,
          mode,
          unpack_inputs,
          use_gpu,
      )
  
imports: import tempfile
  from typing import Callable, List, Tuple, Union
  import torch
  import torch.nn
  from captum.influence._core.arnoldi_influence_function import _parameter_arnoldi, _parameter_distill, ArnoldiInfluenceFunction
  from captum.influence._core.influence_function import NaiveInfluenceFunction
  from captum.influence._utils.common import _eig_helper, _flatten_params, _top_eigen, _unflatten_params_factory
  from parameterized import parameterized
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.influence._utils.common import _format_batch_into_tuple, build_test_name_func, DataInfluenceConstructor, ExplicitDataset, generate_assymetric_matrix_given_eigenvalues, generate_symmetric_matrix_given_eigenvalues, get_random_model_and_data, UnpackDataset, USE_GPU_LIST
  from torch import Tensor
  from torch.utils.data import DataLoader
label_desc: Use image node_id 6 for calling the TestArnoldiInfluence obj's underlying member method code with example usage: obj.test_compare_implementations_random_model_and_data(influence_constructor_1, influence_constructor_2, delta, mode, unpack_inputs, use_gpu) without return types