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6765 update GeneralizedDiceLoss #6775

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merged 3 commits into from
Jul 26, 2023
Merged

6765 update GeneralizedDiceLoss #6775

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8bb0fae
Revert "fix `GeneralizedDiceLoss` (#5468)"
wyli Jul 25, 2023
b48c53f
update docstring
wyli Jul 25, 2023
3e19399
Merge branch 'dev' into fixes-6765
wyli Jul 26, 2023
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6 changes: 4 additions & 2 deletions monai/losses/dice.py
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Original file line number Diff line number Diff line change
Expand Up @@ -268,6 +268,7 @@ def __init__(
smooth_dr: a small constant added to the denominator to avoid nan.
batch: whether to sum the intersection and union areas over the batch dimension before the dividing.
Defaults to False, intersection over union is computed from each item in the batch.
If True, the class-weighted intersection and union areas are first summed across the batches.

Raises:
TypeError: When ``other_act`` is not an ``Optional[Callable]``.
Expand Down Expand Up @@ -360,8 +361,9 @@ def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
max_values = torch.max(w, dim=1)[0].unsqueeze(dim=1)
w = w + infs * max_values

numer = 2.0 * (intersection * w) + self.smooth_nr
denom = (denominator * w) + self.smooth_dr
final_reduce_dim = 0 if self.batch else 1
numer = 2.0 * (intersection * w).sum(final_reduce_dim, keepdim=True) + self.smooth_nr
denom = (denominator * w).sum(final_reduce_dim, keepdim=True) + self.smooth_dr
f: torch.Tensor = 1.0 - (numer / denom)

if self.reduction == LossReduction.MEAN.value:
Expand Down
12 changes: 6 additions & 6 deletions tests/test_generalized_dice_loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -48,15 +48,15 @@
"input": torch.tensor([[[-1.0, 0.0, 1.0], [1.0, 0.0, -1.0]], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]]),
"target": torch.tensor([[[1.0, 0.0, 0.0]], [[1.0, 1.0, 0.0]]]),
},
0.435035,
0.469964,
],
[ # shape: (2, 2, 3), (2, 1, 3)
{"include_background": True, "to_onehot_y": True, "softmax": True, "smooth_nr": 1e-4, "smooth_dr": 1e-4},
{
"input": torch.tensor([[[-1.0, 0.0, 1.0], [1.0, 0.0, -1.0]], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]]),
"target": torch.tensor([[[1.0, 0.0, 0.0]], [[1.0, 1.0, 0.0]]]),
},
0.3837,
0.414507,
],
[ # shape: (2, 2, 3), (2, 1, 3)
{
Expand All @@ -71,7 +71,7 @@
"input": torch.tensor([[[-1.0, 0.0, 1.0], [1.0, 0.0, -1.0]], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]]),
"target": torch.tensor([[[1.0, 0.0, 0.0]], [[1.0, 1.0, 0.0]]]),
},
1.5348,
0.829015,
],
[ # shape: (2, 2, 3), (2, 1, 3)
{
Expand All @@ -86,7 +86,7 @@
"input": torch.tensor([[[-1.0, 0.0, 1.0], [1.0, 0.0, -1.0]], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]]),
"target": torch.tensor([[[1.0, 0.0, 0.0]], [[1.0, 1.0, 0.0]]]),
},
[[[0.210949], [0.295351]], [[0.599976], [0.428522]]],
[[[0.273476]], [[0.555539]]],
],
[ # shape: (2, 2, 3), (2, 1, 3)
{"include_background": False, "to_onehot_y": True, "smooth_nr": 1e-8, "smooth_dr": 1e-8},
Expand Down Expand Up @@ -114,7 +114,7 @@
"input": torch.tensor([[[0.0, 10.0, 10.0, 10.0], [10.0, 0.0, 0.0, 0.0]]]),
"target": torch.tensor([[[1, 1, 0, 0]]]),
},
0.26669,
0.250023,
],
[ # shape: (2, 1, 2, 2), (2, 1, 2, 2)
{"include_background": True, "other_act": torch.tanh, "smooth_nr": 1e-4, "smooth_dr": 1e-4},
Expand All @@ -136,7 +136,7 @@
"input": torch.tensor([[[-1.0, 0.0, 1.0], [1.0, 0.0, -1.0]], [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]]),
"target": torch.tensor([[[1.0, 0.0, 0.0]], [[1.0, 1.0, 0.0]]]),
},
-8.55485,
-0.097833,
],
]

Expand Down
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