code: def test_forward_layer_eval_on_mixed_args_kwargs_module(self) -> None:
      x = torch.randn(10, 5)
      y = torch.randn(10, 5)
  
      model = MixedKwargsAndArgsModule()
  
      self.forward_eval_layer_with_inputs_helper(model, {"x": x})
      self.forward_eval_layer_with_inputs_helper(
          model, {"x": x, "y": y}
      )
  
file_path: captum/tests/attr/test_input_layer_wrapper.py
imports: import functools
  import inspect
  from typing import Callable, Dict, Tuple
  import torch
  from captum._utils.gradient import _forward_layer_eval
  from captum.attr import DeepLift, DeepLiftShap, FeatureAblation, GradientShap, InputXGradient, IntegratedGradients, LayerDeepLift, LayerDeepLiftShap, LayerFeatureAblation, LayerGradientShap, LayerGradientXActivation, LayerIntegratedGradients
  from captum.attr._utils.input_layer_wrapper import ModelInputWrapper
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel, BasicModel_MultiLayer_TrueMultiInput, MixedKwargsAndArgsModule
label_desc: Use image node_id 1 for calling the TestInputLayerWrapper obj's underlying member method code with example usage: obj.test_forward_layer_eval_on_mixed_args_kwargs_module() without return types