code: def forward(self, x: paddle.Tensor):
      x = self.conv1(x)  # shape = [*, width, grid, grid]
      x = x.reshape(
          [x.shape[0], x.shape[1], -1]
      )  # shape = [*, width, grid ** 2]
      x = x.transpose([0, 2, 1])  # shape = [*, grid ** 2, width]
      x = paddle.concat(
          [
              self.class_embedding
              + paddle.zeros(
                  [x.shape[0], 1, x.shape[-1]], dtype=x.dtype
              ),
              x,
          ],
          axis=1,
      )  # shape = [*, grid ** 2 + 1, width]
      x = x + paddle.cast(self.positional_embedding, x.dtype)
      x = self.ln_pre(x)
  
      x = self.transformer(x)
  
      x = self.ln_post(x[:, 0, :])
  
      if self.proj is not None:
          x = x @ self.proj
  
      return x
  
imports: from collections import OrderedDict
  from typing import Tuple
  from typing import Union
  import numpy
  import paddle
  import paddle.nn.functional
  from disco_diffusion_cnclip_vitb16.cn_clip.clip import _tokenizer
  from disco_diffusion_cnclip_vitb16.cn_clip.clip.configuration_bert import BertConfig
  from disco_diffusion_cnclip_vitb16.cn_clip.clip.modeling_bert import BertModel
  from paddle import nn
  from paddle.nn import MultiHeadAttention
label_desc: Use image node_id 2 for calling the VisualTransformer obj's underlying member method code with example usage: obj.forward(x) and returns: x