class_docstr: Transformer encoder (sequence of ViTEncoderBlocks).
class_docstr_tok: ["Transformer","encoder","(","sequence","of","ViTEncoderBlocks",")","."]
code: def forward(self, x):
      for block in self.children():
          x = block(x)
      return 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 ViTEncoder obj's underlying member method code with example usage: obj.forward(x) and returns: x