fix: TorchFix Errors

segmentation_models_pytorch/base/heads.py

@@ -10,7 +10,7 @@ def __init__(
             in_channels, out_channels, kernel_size=kernel_size, padding=kernel_size // 2
         )
         upsampling = (
-            nn.UpsamplingBilinear2d(scale_factor=upsampling)
+            nn.Upsample(mode="bilinear", scale_factor=upsampling)
             if upsampling > 1
             else nn.Identity()
         )

segmentation_models_pytorch/decoders/deeplabv3/decoder.py

@@ -105,7 +105,7 @@ def __init__(
         )
 
         scale_factor = 4 if output_stride == 16 and encoder_depth > 3 else 2
-        self.up = nn.UpsamplingBilinear2d(scale_factor=scale_factor)
+        self.up = nn.Upsample(mode="bilinear", scale_factor=scale_factor)
 
         highres_in_channels = encoder_channels[2]
         highres_out_channels = 48  # proposed by authors of paper

segmentation_models_pytorch/losses/_functional.py

@@ -226,7 +226,7 @@ def wing_loss(
     idx_smaller = diff_abs < width
     idx_bigger = diff_abs >= width
 
-    loss[idx_smaller] = width * torch.log(1 + diff_abs[idx_smaller] / curvature)
+    loss[idx_smaller] = width * torch.log1p(diff_abs[idx_smaller] / curvature)
 
     C = width - width * math.log(1 + width / curvature)
     loss[idx_bigger] = loss[idx_bigger] - C