code: def _upfirdn_2d_cuda(
      x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1
  ):
      """Fast CUDA implementation of `upfirdn_2d()` using custom ops."""
  
      x = tf.convert_to_tensor(x)
      k = np.asarray(k, dtype=np.float32)
      majorDim, inH, inW, minorDim = x.shape.as_list()
      kernelH, kernelW = k.shape
      assert inW >= 1 and inH >= 1
      assert kernelW >= 1 and kernelH >= 1
      assert isinstance(upx, int) and isinstance(upy, int)
      assert isinstance(downx, int) and isinstance(downy, int)
      assert isinstance(padx0, int) and isinstance(padx1, int)
      assert isinstance(pady0, int) and isinstance(pady1, int)
  
      outW = (inW * upx + padx0 + padx1 - kernelW) // downx + 1
      outH = (inH * upy + pady0 + pady1 - kernelH) // downy + 1
      assert outW >= 1 and outH >= 1
  
      kc = tf.constant(k, dtype=x.dtype)
      gkc = tf.constant(k[::-1, ::-1], dtype=x.dtype)
      gpadx0 = kernelW - padx0 - 1
      gpady0 = kernelH - pady0 - 1
      gpadx1 = inW * upx - outW * downx + padx0 - upx + 1
      gpady1 = inH * upy - outH * downy + pady0 - upy + 1
  
      @tf.custom_gradient
      def func(x):
          y = _get_plugin().up_fir_dn2d(
              x=x,
              k=kc,
              upx=upx,
              upy=upy,
              downx=downx,
              downy=downy,
              padx0=padx0,
              padx1=padx1,
              pady0=pady0,
              pady1=pady1,
          )
          y.set_shape([majorDim, outH, outW, minorDim])
  
          @tf.custom_gradient
          def grad(dy):
              dx = _get_plugin().up_fir_dn2d(
                  x=dy,
                  k=gkc,
                  upx=downx,
                  upy=downy,
                  downx=upx,
                  downy=upy,
                  padx0=gpadx0,
                  padx1=gpadx1,
                  pady0=gpady0,
                  pady1=gpady1,
              )
              dx.set_shape([majorDim, inH, inW, minorDim])
              return dx, func
  
          return y, grad
  
      return func(x)
  
file_path: insightface/reconstruction/ostec/external/stylegan2/dnnlib/tflib/ops/upfirdn_2d.py
imports: import os
  import numpy
  import tensorflow
  from ..None import custom_ops
label_desc: Use image node_id 4 for calling a global function with example usage: _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1) and returns: func, y,  grad, dx,  func