class_docstr: Make the size of feature map divisible by local group size.
class_docstr_tok: ["Make","the","size","of","feature","map","divisible","by","local","group","size","."]
code: def pad_if_needed(self, x, size):
      n, h, w, c = size
      pad_h = paddle.cast(
          paddle.ceil(h / self.lgs[0]) * self.lgs[0] - h, paddle.int32
      )
      pad_w = paddle.cast(
          paddle.ceil(w / self.lgs[1]) * self.lgs[1] - w, paddle.int32
      )
      if (
          pad_h > 0 or pad_w > 0
      ):  # center-pad the feature on H and W axes
          return F.pad(
              x,
              paddle.to_tensor(
                  [
                      pad_w // 2,
                      pad_w - pad_w // 2,
                      pad_h // 2,
                      pad_h - pad_h // 2,
                  ],
                  dtype="int32",
              ).reshape([-1]),
              data_format="NHWC",
          )
      return x
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.utils import utils, logger
  from paddleseg.models.backbones.transformer_utils import *
label_desc: Use image node_id 2 for calling the PadHelper obj's underlying member method code with example usage: obj.pad_if_needed(x, size) and returns: x, F