class_docstr: This class implements attention pooling layer, as
  described in `Clip <https://arxiv.org/pdf/2103.00020.pdf>`_, and should be
  used for CNN-style models, including MobileViTs
class_docstr_tok: ["This","class","implements","attention","pooling","layer",",","as","described","in","`","Clip","<","https",":","\/\/arxiv.org\/pdf\/2103.00020.pdf",">","`","_",",","and","should","be","used","for","CNN-style","models",",","including","MobileViTs"]
code: def reset_parameters(self):
      std = self.projection_dim**-0.5
      nn.init.normal_(
          self.multi_head_attn.qkv_proj.weight, mean=0.0, std=std
      )
      nn.init.normal_(
          self.multi_head_attn.out_proj.weight, mean=0.0, std=std
      )
  
file_path: ml-cvnets/cvnets/image_projection_layers/attention_pool_2d.py
imports: import argparse
  import torch
  from torch import Tensor, nn
  from torch.nn import functional
  from cvnets.image_projection_layers import IMAGE_PROJECTION_HEAD_REGISTRY, BaseImageProjectionHead
  from cvnets.layers import MultiHeadAttention, PositionalEmbedding
  from utils import logger
label_desc: Use image node_id 3 for calling the AttentionPool2dHead obj's underlying member method code with example usage: obj.reset_parameters() without return types