code: def _draw_kernel_feature_paths_ApproximateGP_fallback(
      model: ApproximateGP,
      _: _VariationalStrategy,
      *,
      num_inputs: int,
      **kwargs: Any,
  ) -> GeneralizedLinearPath:
      return _draw_kernel_feature_paths_fallback(
          num_inputs=num_inputs,
          mean_module=model.mean_module,
          covar_module=model.covar_module,
          **kwargs,
      )
  
imports: from __future__ import annotations
  from typing import Any, Callable, List, Optional
  from botorch.models.approximate_gp import ApproximateGPyTorchModel
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.sampling.pathwise.features import gen_kernel_features
  from botorch.sampling.pathwise.features.generators import TKernelFeatureMapGenerator
  from botorch.sampling.pathwise.paths import GeneralizedLinearPath, PathList, SamplePath
  from botorch.sampling.pathwise.utils import get_input_transform, get_output_transform, get_train_inputs, TInputTransform, TOutputTransform
  from botorch.utils.dispatcher import Dispatcher
  from botorch.utils.sampling import draw_sobol_normal_samples
  from gpytorch.kernels import Kernel
  from gpytorch.models import ApproximateGP, ExactGP, GP
  from gpytorch.variational import _VariationalStrategy
  from torch import Size, Tensor
  from torch.nn import Module
label_desc: Use image node_id 7 for calling a global function with example usage: _draw_kernel_feature_paths_ApproximateGP_fallback(model, _) and returns: _draw_kernel_feature_paths_fallback