del_cpu_offload()


>>> def get_depth_map(image):
...     image = feature_extractor(images=image, return_tensors="pt").pixel_values.to("cuda")
...     with torch.no_grad(), torch.autocast("cuda"):
...         depth_map = depth_estimator(image).predicted_depth

...     depth_map = torch.nn.functional.interpolate(
...         depth_map.unsqueeze(1),
...         size=(1024, 1024),
...         mode="bicubic",
...         align_corners=False,
...   