lint fix

mlcommons · Dec 19, 2024 · ba3ea83 · ba3ea83
1 parent 05f7101
commit ba3ea83
Showing 1 changed file with 21 additions and 21 deletions.
diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
@@ -368,9 +368,9 @@ def __percentile_clip(
                     strictlyPositive=True,
                 )
 
-            overall_stats_dict[current_subject_id]["ssim"] = (
-                structural_similarity_index(output_infill, gt_image_infill, mask).item()
-            )
+            overall_stats_dict[current_subject_id][
+                "ssim"
+            ] = structural_similarity_index(output_infill, gt_image_infill, mask).item()
 
             # ncc metrics
             compute_ncc = parameters.get("compute_ncc", True)
@@ -415,30 +415,30 @@ def __percentile_clip(
             ).item()
 
             # same as above but with epsilon for robustness
-            overall_stats_dict[current_subject_id]["psnr_eps"] = (
-                peak_signal_noise_ratio(
-                    output_infill, gt_image_infill, epsilon=sys.float_info.epsilon
-                ).item()
-            )
+            overall_stats_dict[current_subject_id][
+                "psnr_eps"
+            ] = peak_signal_noise_ratio(
+                output_infill, gt_image_infill, epsilon=sys.float_info.epsilon
+            ).item()
 
             # only use fix data range to [0;1] if the data was normalized before
             if normalize:
                 # torchmetrics PSNR but with fixed data range of 0 to 1
-                overall_stats_dict[current_subject_id]["psnr_01"] = (
-                    peak_signal_noise_ratio(
-                        output_infill, gt_image_infill, data_range=(0, 1)
-                    ).item()
-                )
+                overall_stats_dict[current_subject_id][
+                    "psnr_01"
+                ] = peak_signal_noise_ratio(
+                    output_infill, gt_image_infill, data_range=(0, 1)
+                ).item()
 
                 # same as above but with epsilon for robustness
-                overall_stats_dict[current_subject_id]["psnr_01_eps"] = (
-                    peak_signal_noise_ratio(
-                        output_infill,
-                        gt_image_infill,
-                        data_range=(0, 1),
-                        epsilon=sys.float_info.epsilon,
-                    ).item()
-                )
+                overall_stats_dict[current_subject_id][
+                    "psnr_01_eps"
+                ] = peak_signal_noise_ratio(
+                    output_infill,
+                    gt_image_infill,
+                    data_range=(0, 1),
+                    epsilon=sys.float_info.epsilon,
+                ).item()
 
     pprint(overall_stats_dict)
     if outputfile is not None: