GPU memory increased by 4GiB when running rasterizer

[CHMimilanlan]

It's a wired problem, which bothered me for a whole day.
when i running code below:

self.raster_settings = GaussianRasterizationSettings(
    image_height=self.image_size,
    image_width=self.image_size,
    tanfovx=self.tanfov,
    tanfovy=self.tanfov,
    bg=self.bg,
    scale_modifier=1.0,
    viewmatrix=w2c,
    projmatrix=full_proj,
    sh_degree=0,
    campos=cam_center,
    prefiltered=False,
    debug=False,
    antialiasing=True
)
self.rasterizer = GaussianRasterizer(raster_settings=self.raster_settings)
rendered_image, _ ,_ = self.rasterizer( 
    means3D = means3D,
    means2D = screenspace_points,
    colors_precomp = colors_precomp,
    opacities = opacities,
    scales = scales,
    rotations = rotations,
    cov3D_precomp = None)

CUDA memory increased by 4GiB, which is unbearable. That code is supposed to run several times. Each time that code is run, CUDA memory grows by 4GB until the CUDA out of memory.
I check the shape of each variable, it seems that it wasn't the problem of the size of variables, every variables are in expected shape.

means3D.shape=torch.Size([50200, 3])
screenspace_points.shape=torch.Size([50200, 3])
colors_precomp.shape=torch.Size([50200, 3])
opacities.shape=torch.Size([50200, 1])
scales.shape=torch.Size([50200, 1])
rotations.shape=torch.Size([50200, 4])

And the output size is also in expected shape, rendered_image.shape=torch.Size([3, 1024, 1024])
I have tried reinstalled diff_gaussian_rasterization and it doesn't work.

Could you tell me some potential possible reasons which cause this problem and it's corresponding solutions?
I will be grateful for your timely response !