class_docstr: A model wrapper to run model forward/backward steps and storing some intermediate feature/gradient information.
docstr: Args:
      layer_id: a layer name string or a callable. If it is a callable such as `lambda m: m.fc`,
          this method will return the module `self.model.fc`.
  
  Returns:
      a submodule from self.model.
code: def get_layer(
      self, layer_id: str | Callable[[nn.Module], nn.Module]
  ) -> nn.Module:
      """
  
      Args:
          layer_id: a layer name string or a callable. If it is a callable such as `lambda m: m.fc`,
              this method will return the module `self.model.fc`.
  
      Returns:
          a submodule from self.model.
      """
      if callable(layer_id):
          return layer_id(self.model)
      if isinstance(layer_id, str):
          for name, mod in self.model.named_modules():
              if name == layer_id:
                  return cast(nn.Module, mod)
      raise NotImplementedError(f"Could not find {layer_id}.")
  
imports: from __future__ import annotations
  import warnings
  from collections.abc import Callable, Sequence
  from typing import cast
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from monai.config import NdarrayTensor
  from monai.transforms import ScaleIntensity
  from monai.utils import ensure_tuple, pytorch_after
  from monai.visualize.visualizer import default_upsampler
label_desc: Use image node_id 4 for calling the ModelWithHooks obj's underlying member method code with example usage: obj.get_layer(layer_id) and returns: layer_id, cast