zhangyiss/mlx
1
0
Fork 0
mirror of https://github.com/ml-explore/mlx.git synced 2025-10-18 15:28:16 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Add Binary Cross Entropy loss (#122)

Browse Source 
* update BCE added tests for it ...

* added binary cross entropy loss to docs

* resolving conflicts for merge
This commit is contained in:
__mo_san__
2023-12-11 16:55:18 +01:00
committed by GitHub
parent b0cd092b7f
commit f4ddd7dc44
3 changed files with 102 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
python/tests/test_nn.py
View File

@@ -100,6 +100,25 @@ class TestNN(mlx_tests.MLXTestCase):
expected_sum = mx.sum(expected_none)
self.assertTrue(mx.allclose(losses_sum, expected_sum))
def test_binary_cross_entropy(self):
inputs = mx.array([[0.5, 0.5], [0.5, 0.5]])
targets = mx.array([[0.0, 1.0], [1.0, 0.0]])
# Test with reduction 'none'
losses_none = nn.losses.binary_cross_entropy(inputs, targets, reduction="none")
expected_none = mx.array([[0.693147, 0.693147], [0.693147, 0.693147]])
self.assertTrue(mx.array_equal(losses_none, expected_none))
# Test with reduction 'mean'
losses_mean = nn.losses.binary_cross_entropy(inputs, targets, reduction="mean")
expected_mean = mx.mean(expected_none)
self.assertEqual(losses_mean, expected_mean)
# Test with reduction 'sum'
losses_sum = nn.losses.binary_cross_entropy(inputs, targets, reduction="sum")
expected_sum = mx.sum(expected_none)
self.assertEqual(losses_sum, expected_sum)
def test_gelu(self):
inputs = [1.15286231, -0.81037411, 0.35816911, 0.77484438, 0.66276414]