class_docstr: Transformer encoder block, following https://arxiv.org/abs/2010.11929.
class_docstr_tok: ["Transformer","encoder","block",",","following","https",":","\/\/arxiv.org\/abs\/2010.11929","."]
code: def forward(self, x):
      x_p = self.ln_1(x)
      x_p, _ = self.self_attention(x_p, x_p, x_p)
      x = x + x_p
      x_p = self.mlp_block(self.ln_2(x))
      return x + x_p
  
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 ViTEncoderBlock obj's underlying member method code with example usage: obj.forward(x) and returns: unknown