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@@ -33,7 +33,7 @@ class UNet(cv.models.UNet):
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input_channel=None):
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if num_classes > 2 and (use_bce_loss or use_dice_loss):
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raise ValueError(
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- "dice loss and bce loss is only applicable to binary classfication"
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+ "dice loss and bce loss is only applicable to binary classification"
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)
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elif num_classes == 2:
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if use_bce_loss and use_dice_loss:
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@@ -87,7 +87,7 @@ class DeepLabv3p(cv.models.DeepLabV3P):
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input_channel=None):
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if num_classes > 2 and (use_bce_loss or use_dice_loss):
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raise ValueError(
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- "dice loss and bce loss is only applicable to binary classfication"
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+ "dice loss and bce loss is only applicable to binary classification"
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)
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elif num_classes == 2:
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if use_bce_loss and use_dice_loss:
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@@ -152,7 +152,7 @@ class HRNet(cv.models.HRNet):
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input_channel=None):
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if num_classes > 2 and (use_bce_loss or use_dice_loss):
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raise ValueError(
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- "dice loss and bce loss is only applicable to binary classfication"
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+ "dice loss and bce loss is only applicable to binary classification"
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)
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elif num_classes == 2:
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if use_bce_loss and use_dice_loss:
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@@ -196,7 +196,7 @@ class FastSCNN(cv.models.FastSCNN):
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input_channel=3):
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if num_classes > 2 and (use_bce_loss or use_dice_loss):
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raise ValueError(
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- "dice loss and bce loss is only applicable to binary classfication"
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+ "dice loss and bce loss is only applicable to binary classification"
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)
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elif num_classes == 2:
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if use_bce_loss and use_dice_loss:
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