code: def mlp(x, scope, n_state, *, hparams, train=False):
      with tf.compat.v1.variable_scope(scope):
          nx = x.shape[-1]
          h = gelu(conv1d(x, "c_fc", n_state))
          h2 = conv1d(h, "c_proj", nx)
          h2 = dropout(h2, hparams.resid_p_drop, train=train)
          return h2
  
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 7 for calling a global function with example usage: mlp(x, scope, n_state) and returns: h2