class_docstr: ### Stack Module
  
  This uses the stack function defined above, and does the necessary initializations.
class_docstr_tok: ["#","#","#","Stack","Module","This","uses","the","stack","function","defined","above",",","and","does","the","necessary","initializations","."]
docstr: Returns the stack
docstr_tok: ["Returns","the","stack"]
code: def get(self):
      """
      Returns the stack
      """
  
      # Keep track of the size of the stack when it was used.
      # This is used for a sanity check in `append`.
      self.last_get_n = self.n
      # Take it all through `StackFunction` so that `StackFunction.backwards`
      # is called by PyTorch during backpropagation.
      return StackFunction.apply(
          self.memory, self.memory_grad, self.last, self.n
      )
  
imports: import math
  from typing import Optional
  import torch
  from torch import nn
  from labml_helpers.module import Module
  from labml_nn.transformers.feed_forward import FeedForward
  from labml_nn.transformers.mha import PrepareForMultiHeadAttention
  from labml_nn.utils import clone_module_list
label_desc: Use image node_id 3 for calling the Stack obj's underlying member method code with example usage: obj.get() and returns: StackFunction