upsampling_2d.py 文件源码

def backward_gpu(self, x, gy):
        xp = cuda.cupy
        gcol = conv.im2col_gpu(
            gy[0], self.kh, self.kw, self.sy, self.sx, self.ph, self.pw,
            cover_all=self.cover_all)

        gcol = gcol.transpose(0, 1, 4, 5, 2, 3)
        n, c, oy, ox, ky, kx = gcol.shape
        gcol = gcol.reshape((n, c, oy, ox, ky * kx))
        indexes = xp.asarray(self.indexes, dtype=numpy.int32)
        gx = xp.empty((n, c, oy, ox), dtype=x[0].dtype)
        xp.ElementwiseKernel(
            'int32 indexes, raw float32 gcol, int32 n, int32 c, int32 oy,'
            'int32 ox, int32 ky, int32 kx',
            'raw float32 gx',
            '''
            int ind_n = i / c / oy / ox;
            int ind_c = (i / oy / ox) % c;
            int ind_oy = (i / ox) % oy;
            int ind_ox = i % ox;
            int gcol_ky = indexes / kx;
            int gcol_kx = indexes % kx;
            float top_gx = gcol[ind_n * c * oy * ox * ky * kx + \
                                ind_c * oy * ox * ky * kx + \
                                ind_oy * ox * ky * kx + \
                                ind_ox * ky * kx + \
                                gcol_ky * kx + \
                                gcol_kx];
            gx[ind_n * c * oy * ox + \
               ind_c * oy * ox + \
               ind_oy * ox + \
               ind_ox] = top_gx;
            ''',
            'upsampling_2d_bwd')(indexes, gcol, n, c, oy, ox, ky, kx, gx)

        return gx,