class_docstr: Transformer encoder (sequence of ViTEncoderBlocks).
class_docstr_tok: ["Transformer","encoder","(","sequence","of","ViTEncoderBlocks",")","."]
code: def complexity(cx, n_layers, hidden_d, n_heads, mlp_d, seq_len):
      for _ in range(n_layers):
          cx = ViTEncoderBlock.complexity(
              cx, hidden_d, n_heads, mlp_d, seq_len
          )
      cx = layernorm_cx(cx, hidden_d)
      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 ViTEncoder obj's underlying member method code with example usage: obj.complexity(cx, n_layers, hidden_d, n_heads, mlp_d, seq_len) and returns: cx