class_docstr: Appends the [CLS] token for BERT-like inference.
docstr: Initialize self.
docstr_tok: ["Initialize","self","."]
code: def __init__(self, d_token: int, initialization: str) -> None:
      """Initialize self."""
      super().__init__()
      self.weight = nn.Parameter(torch.Tensor(d_token))
      d_sqrt_inv = 1 / math.sqrt(d_token)
      _initialize_kaiming(self.weight, initialization, d_sqrt_inv)
  
imports: import math
  from typing import Optional
  import torch
  from einops import rearrange
  from torch import einsum, nn
  from pytorch_tabular.utils import _initialize_kaiming
  from .gated_units import GEGLU, PositionWiseFeedForward, ReGLU, SwiGLU
label_desc: Use image node_id 1 to create a new AppendCLSToken object from inherited base classes: nn with example: obj = AppendCLSToken(d_token, initialization)