[fbsync] feat: Raise ValueError for alpha > 1 in sigmoid_focal_loss (#8882)

Reviewed By: scotts

Differential Revision: D77997070

fbshipit-source-id: be9289a4b3fab0447d17ae18ceeddd617cc9ab75

Co-authored-by: Nicolas Hug <[email protected]>
Co-authored-by: Nicolas Hug <[email protected]>

Author: NicolasHug

torchvision/ops/focal_loss.py

@@ -20,7 +20,7 @@ def sigmoid_focal_loss(
         targets (Tensor): A float tensor with the same shape as inputs. Stores the binary
                 classification label for each element in inputs
                 (0 for the negative class and 1 for the positive class).
-        alpha (float): Weighting factor in range (0,1) to balance
+        alpha (float): Weighting factor in range [0, 1] to balance
                 positive vs negative examples or -1 for ignore. Default: ``0.25``.
         gamma (float): Exponent of the modulating factor (1 - p_t) to
                 balance easy vs hard examples. Default: ``2``.
@@ -33,6 +33,9 @@ def sigmoid_focal_loss(
     """
     # Original implementation from https://github.com/facebookresearch/fvcore/blob/master/fvcore/nn/focal_loss.py
 
+    if not (0 <= alpha <= 1) or alpha != -1:
+        raise ValueError(f"Invalid alpha value: {alpha}. alpha must be in the range [0,1] or -1 for ignore.")
+
     if not torch.jit.is_scripting() and not torch.jit.is_tracing():
         _log_api_usage_once(sigmoid_focal_loss)
     p = torch.sigmoid(inputs)