code: def block(x, *, past, hparams, train=False):
      nx = x.shape[-1]
      a = attn(
          norm(x, "ln_1"),
          "attn",
          nx,
          past=past,
          hparams=hparams,
          train=train,
      )
      x = x + a
      m = mlp(
          norm(x, "ln_2"), "mlp", nx * 4, hparams=hparams, train=train
      )
      x = x + m
      return x
  
file_path: finetune/finetune/base_models/gpt2/featurizer.py
imports: import functools
  import tensorflow
  from finetune.util.shapes import shape_list, lengths_from_eos_idx
  from finetune.optimizers.recompute_grads import recompute_grad
  from finetune.nn.activations import gelu
  from finetune.base_models.gpt.featurizer import norm, dropout, get_pos_values
label_desc: Use image node_id 8 for calling a global function with example usage: block(x) and returns: x