class_docstr: Transformer MLP block, fc, gelu, fc.
class_docstr_tok: ["Transformer","MLP","block",",","fc",",","gelu",",","fc","."]
code: def forward(self, x):
      return self.linear_2(self.af(self.linear_1(x)))
  
imports: import math
  import numpy
  import torch
  from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, layernorm, layernorm_cx, linear, linear_cx, MultiheadAttention, norm2d, norm2d_cx, patchify2d, patchify2d_cx
  from torch.nn import init, Module, Parameter
label_desc: Use image node_id 2 for calling the MLPBlock obj's underlying member method code with example usage: obj.forward(x) and returns: self