code: def one_scale_val(self, x):
      x_size = x.shape[2:]
      cls_out, aux_out, _ = self.ocrnet(x)
  
      cls_out = nn.functional.interpolate(
          cls_out,
          size=x_size,
          mode="bilinear",
          align_corners=self.align_corners,
      )
  
      output = [cls_out]
      return output
  
imports: import math
  import paddle
  import paddle.nn
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.utils import utils
  from paddleseg.models import layers
  from .ocrnet_nv import OCRNetNV
label_desc: Use image node_id 4 for calling the MscaleOCRNet obj's underlying member method code with example usage: obj.one_scale_val(x) and returns: output