code: def __init__(
      self,
      embed_dim=256,
      ffn_dim=1024,
      dropout=0.1,
      num_levels=4,
      num_heads=8,
      num_points=4,
  ):
      super().__init__()
  
      # Self attention
      self.self_attn = MSDeformAttn(
          embed_dim, num_levels, num_heads, num_points
      )
      self.dropout1 = nn.Dropout(dropout)
      self.norm1 = nn.LayerNorm(embed_dim)
  
      # FFN
      self.linear1 = nn.Linear(embed_dim, ffn_dim)
      self.activation = nn.ReLU()
      self.dropout2 = nn.Dropout(dropout)
      self.linear2 = nn.Linear(ffn_dim, embed_dim)
      self.dropout3 = nn.Dropout(dropout)
      self.norm2 = nn.LayerNorm(embed_dim)
  
imports: import copy
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import param_init
  from paddlepanseg.models.param_init import c2_xavier_fill, THLinearInitMixin
  from .common import Conv2D, PositionEmbeddingSine
  from ._ms_deform_attn import MSDeformAttn
label_desc: Use image node_id 1 to create a new MSDeformAttnTransformerEncoderLayer object from inherited base classes: nn with example: obj = MSDeformAttnTransformerEncoderLayer(embed_dim, ffn_dim, dropout, num_levels, num_heads, num_points)