class_docstr: An attention module used in PETR. `End-to-End Multi-Person
  Pose Estimation with Transformers`.
  
  Args:
      embed_dims (int): The embedding dimension of Attention.
          Default: 256.
      num_heads (int): Parallel attention heads. Default: 8.
      num_levels (int): The number of feature map used in
          Attention. Default: 4.
      num_points (int): The number of sampling points for
          each query in each head. Default: 17.
      im2col_step (int): The step used in image_to_column.
          Default: 64.
      dropout (float): A Dropout layer on `inp_residual`.
          Default: 0.1.
      init_cfg (obj:`mmcv.ConfigDict`): The Config for initialization.
          Default: None.
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docstr: Default initialization for Parameters of Module.
docstr_tok: ["Default","initialization","for","Parameters","of","Module","."]
code: def init_weights(self):
      """Default initialization for Parameters of Module."""
      constant_(self.sampling_offsets.weight)
      constant_(self.sampling_offsets.bias)
      constant_(self.attention_weights.weight)
      constant_(self.attention_weights.bias)
      xavier_uniform_(self.value_proj.weight)
      constant_(self.value_proj.bias)
      xavier_uniform_(self.output_proj.weight)
      constant_(self.output_proj.bias)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register
  from ..layers import MultiHeadAttention, _convert_attention_mask
  from .utils import _get_clones
  from ..initializer import linear_init_, normal_, constant_, xavier_uniform_
label_desc: Use image node_id 2 for calling the MultiScaleDeformablePoseAttention obj's underlying member method code with example usage: obj.init_weights() without return types