class_docstr: UpsampleOneStep module (the difference with Upsample is that it always only has 1conv + 1pixelshuffle)
     Used in lightweight SR to save parameters.
  Args:
      scale (int): Scale factor. Supported scales: 2^n and 3.
      num_feat (int): Channel number of intermediate features.
class_docstr_tok: ["UpsampleOneStep","module","(","the","difference","with","Upsample","is","that","it","always","only","has","1conv","+","1pixelshuffle",")","Used","in","lightweight","SR","to","save","parameters",".","Args",":","scale","(","int",")",":","Scale","factor",".","Supported","scales",":","2^n","and","3.","num_feat","(","int",")",":","Channel","number","of","intermediate","features","."]
code: def flops(self):
      H, W = self.input_resolution
      flops = H * W * self.num_feat * 3 * 9
      return flops
  
imports: import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 2 for calling the UpsampleOneStep obj's underlying member method code with example usage: obj.flops() and returns: flops