predict_md.sh (Middlebury 2014 dataset) GPU running out of memory

[andrea-unity]

I'm able to run inference on a Kitti 2015 dataset.
Do you know how can I run prediction on Middlebury 2014 with a single GPU with 24GB?
It always run out of memory, Should I downsize the input?

I'm using MiddEval3-data-H -> 1000 x 1500 size

Exception has occurred: RuntimeError
CUDA out of memory. Tried to allocate 5.49 GiB (GPU 0; 23.68 GiB total capacity; 16.71 GiB already allocated; 3.46 GiB free; 18.42 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
File "/home/andreaa/dev/stereo_depth/LEAStereo/retrain/skip_model_3d.py", line 47, in forward
s1 = F.interpolate(s1, [feature_size_d, feature_size_h, feature_size_w], mode='trilinear', align_corners=True)
File "/home/andreaa/dev/stereo_depth/LEAStereo/retrain/skip_model_3d.py", line 155, in forward
out10= self.cells[10](out9[0], out9[1])
File "/home/andreaa/dev/stereo_depth/LEAStereo/retrain/LEAStereo.py", line 41, in forward
cost = self.matching(cost)
File "/home/andreaa/dev/stereo_depth/LEAStereo/utils/multadds_count.py", line 21, in comp_multadds
_ = model(input_data, input_data)
File "/home/andreaa/dev/stereo_depth/LEAStereo/predict.py", line 48, in
mult_adds = comp_multadds(model, input_size=(3,opt.crop_height, opt.crop_width)) #(3,192, 192))

[AiYoWeiYL]

I have the same problem. Have you solved it？