class_docstr: ## Auto regressive model
class_docstr_tok: ["#","#","Auto","regressive","model"]
docstr: Retrieve saved $f(c_t)$
docstr_tok: ["Retrieve","saved","$","f","(","c_t",")","$"]
code: def ff_input(self) -> torch.Tensor:
      """
      Retrieve saved $f(c_t)$
      """
      return self.encoder.layers[-1].ff_input
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/knn/train_model.py
imports: import torch
  from labml import experiment
  from labml.configs import option
  from labml.utils.pytorch import get_modules
  from labml_helpers.module import Module
  from labml_nn.experiments.nlp_autoregression import NLPAutoRegressionConfigs
  from labml_nn.transformers import Encoder, Generator, TransformerConfigs
  from labml_nn.transformers.utils import subsequent_mask
label_desc: Use image node_id 2 for calling the AutoregressiveModel obj's underlying member method code with example usage: obj.ff_input() and returns: self