class_docstr: Transformer MLP block, fc, gelu, fc.
class_docstr_tok: ["Transformer","MLP","block",",","fc",",","gelu",",","fc","."]
code: def complexity(cx, w_in, mlp_d, seq_len):
      cx = linear_cx(cx, w_in, mlp_d, bias=True, num_locations=seq_len)
      cx = linear_cx(cx, mlp_d, w_in, bias=True, num_locations=seq_len)
      return cx
  
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 3 for calling the MLPBlock obj's underlying member method code with example usage: obj.complexity(cx, w_in, mlp_d, seq_len) and returns: cx