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[0-size Tensor Job2 No.56] Add 0-size Tensor support for paddle.nn.functional.dice_loss[fluid_ops] #73855

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Merged
merged 1 commit into from
Jul 8, 2025
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[0-size Tensor Job2 No.56] Add 0-size Tensor support for paddle.nn.functional.dice_loss[fluid_ops] #73855

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6 changes: 0 additions & 6 deletions python/paddle/nn/functional/loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,7 @@

from __future__ import annotations

import functools
import math
import operator
from typing import TYPE_CHECKING, Literal, overload

import paddle
Expand Down Expand Up @@ -110,10 +108,6 @@ def dice_loss(
assert (
input.shape[:-1] == label.shape[:-1]
), "All dimensions should be equal except the last one."
assert (
functools.reduce(operator.mul, input.shape) != 0
and functools.reduce(operator.mul, label.shape) != 0
), "Any dimension of input and label cannot be equal to 0."

label = paddle.squeeze(label, [-1])
label = paddle.nn.functional.one_hot(label, input.shape[-1])
Expand Down
19 changes: 19 additions & 0 deletions test/legacy_test/test_nn_dice_loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,28 @@

import unittest

import numpy as np
from op_test import get_places

import paddle

num_classes = 4
eps = 1e-6


class TestDiceLossOpApi_ZeroSize(unittest.TestCase):
def test_api_with_dygraph(self):
for place in get_places():
paddle.disable_static(place)
input = paddle.randn([0, 2]).astype(paddle.float64)
input.stop_gradient = False
label = paddle.randn([0, 1]).astype(paddle.int64)
label.stop_gradient = False
out = paddle.nn.functional.dice_loss(input, label, 1e-5)
np.testing.assert_allclose(out.numpy(), paddle.nan)
out.sum().backward()
np.testing.assert_allclose(input.grad.shape, input.shape)


if __name__ == "__main__":
unittest.main()
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