code: def get_layer(model, layer_name):
      """
      Return the targeted layer (nn.Module Object) given a hierarchical layer name,
      separated by /.
      Args:
          model (model): model to get layers from.
          layer_name (str): name of the layer.
      Returns:
          prev_module (nn.Module): the layer from the model with `layer_name` name.
      """
      layer_ls = layer_name.split("/")
      prev_module = model
      for layer in layer_ls:
          prev_module = prev_module._modules[layer]
  
      return prev_module
  
imports: import itertools
  import numpy
  import matplotlib.pyplot
  import torch
  from sklearn.metrics import confusion_matrix
  import slowfast.utils.logging
  from slowfast.datasets.utils import pack_pathway_output, tensor_normalize
label_desc: Use image node_id 7 for calling a global function with example usage: get_layer(model, layer_name) and returns: prev_module