class_docstr: Dilation2d
class_docstr_tok: ["Dilation2d"]
code: def forward(self, x):
      batch_size, c, h, w = x.shape
      x_pad = F.pad(x, pad=self.pad, mode="constant", value=-1e9)
      channel = nn.functional.unfold(
          x_pad, 2 * self.m + 1, strides=1, paddings=0
      ).reshape([batch_size, c, -1, h, w])
      result = paddle.max(channel, axis=2)
      return result
  
file_path: PaddleHub/modules/image/Image_gan/style_transfer/paint_transformer/render_utils.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import cv2
  import numpy
  from PIL import Image
  import math
label_desc: Use image node_id 2 for calling the Dilation2d obj's underlying member method code with example usage: obj.forward(x) and returns: result