o .wi@sddlZddlmZddlmZmZddlmZdedededed ed ed eeeeffd d Z ded ed eded ef ddZ ddededed efddZ dS)N)Tensor)_rmse_sw_compute_rmse_sw_update)_uniform_filterpredstarget window_sizermse_map target_sum total_imagesreturncCsDt|||d||d\}}}|tjt|||ddd7}|||fS)aCalculate the sum of RMSE map values for the batch of examples and update intermediate states. Args: preds: Deformed image target: Ground truth image window_size: Sliding window used for RMSE calculation rmse_map: Sum of RMSE map values over all examples target_sum: target... total_images: Total number of images Return: Intermediate state of RMSE map Updated total number of already processed images N rmse_val_sumr r r)dim)rtorchsumr)rrrr r r _r_/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/functional/image/rase.py _rase_updates    rcCsltd||d\}}||}|d}d|tt|dd}t|d}t||| || fS)aCompute RASE. Args: rmse_map: Sum of RMSE map values over all examples target_sum: target... total_images: Total number of images. window_size: Sliding window used for rmse calculation Return: Relative Average Spectral Error (RASE) Nr rdr)rmeanrsqrtround)r r r rr target_meanrase_map crop_sliderrr _rase_compute0s    rcCst|trt|tr|dkrtd|jdd}tj||j|jd}tj||j|jd}tjd|jd}t ||||||\}}}t ||||S)aCompute Relative Average Spectral Error (RASE) (RelativeAverageSpectralError_). Args: preds: Deformed image target: Ground truth image window_size: Sliding window used for rmse calculation Return: Relative Average Spectral Error (RASE) Example: >>> from torch import rand >>> from torchmetrics.functional.image import relative_average_spectral_error >>> preds = rand(4, 3, 16, 16) >>> target = rand(4, 3, 16, 16) >>> relative_average_spectral_error(preds, target) tensor(5326.40...) Raises: ValueError: If ``window_size`` is not a positive integer. zs*