class_docstr: MSCAN Block.
  
  Args:
      dim (int): Number of feature channels.
      atten_kernel_sizes (list[int], optional): The height or width of each strip convolution kernel in attention module.
          Default: [7, 11, 21].
      mlp_ratio (float, optional): Ratio of mlp hidden dim to embedding dim. Default: 4.0.
      drop (float, optional): Dropout rate. Default: 0.0
      attn_drop (float, optional): Attention dropout rate. Default: 0.0.
      drop_path (float, optional): Stochastic depth rate. Default: 0.0.
      act_layer (nn.Layer, optional): Activation layer. Default: nn.GELU.
class_docstr_tok: ["MSCAN","Block",".","Args",":","dim","(","int",")",":","Number","of","feature","channels",".","atten_kernel_sizes","(","list","[","int","]",",","optional",")",":","The","height","or","width","of","each","strip","convolution","kernel","in","attention","module",".","Default",":","[","7",",","11",",","21","]",".","mlp_ratio","(","float",",","optional",")",":","Ratio","of","mlp","hidden","dim","to","embedding","dim",".","Default",":","4.0.","drop","(","float",",","optional",")",":","Dropout","rate",".","Default",":","0.0","attn_drop","(","float",",","optional",")",":","Attention","dropout","rate",".","Default",":","0.0.","drop_path","(","float",",","optional",")",":","Stochastic","depth","rate",".","Default",":","0.0.","act_layer","(","nn.Layer",",","optional",")",":","Activation","layer",".","Default",":","nn.GELU","."]
code: def forward(self, x, H, W):
      B, N, C = x.shape
      x = x.transpose([0, 2, 1]).reshape([B, C, H, W])
      x = x + self.drop_path(
          self.layer_scale_1 * self.attn(self.norm1(x))
      )
      x = x + self.drop_path(
          self.layer_scale_2 * self.mlp(self.norm2(x))
      )
      x = x.reshape([B, C, N]).transpose([0, 2, 1])
      return x
  
imports: import math
  import numpy
  import paddle
  import paddle.nn
  from paddle.nn import Conv2D
  from paddle.nn.initializer import Assign, Normal
  from paddleseg.cvlibs import manager
  from paddleseg.models.backbones.transformer_utils import DropPath, ones_, to_2tuple, zeros_
  from paddleseg.models.layers import SyncBatchNorm
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x, H, W) and returns: x