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Fix test_gelu unit test #269

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Merged
merged 1 commit into from
Jul 28, 2025
Merged

Fix test_gelu unit test #269

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15 changes: 15 additions & 0 deletions apex/fused_dense/fused_dense.py
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Original file line number Diff line number Diff line change
Expand Up @@ -128,6 +128,21 @@ def __init__(self, in_features, intermediate_features, out_features, bias=True):
self.bias1 = nn.Parameter(torch.randn(intermediate_features))
self.weight2 = nn.Parameter(torch.randn(out_features, intermediate_features))
self.bias2 = nn.Parameter(torch.randn(out_features))
self.reset_parameters()


def reset_parameters(self):
nn.init.kaiming_uniform_(self.weight1, a=math.sqrt(5))
nn.init.kaiming_uniform_(self.weight2, a=math.sqrt(5))
if self.bias1 is not None:
fan_in, _ = nn.init._calculate_fan_in_and_fan_out(self.weight1)
bound = 1 / math.sqrt(fan_in) if fan_in > 0 else 0
nn.init.uniform_(self.bias1, -bound, bound)
if self.bias2 is not None:
fan_in, _ = nn.init._calculate_fan_in_and_fan_out(self.weight2)
bound = 1 / math.sqrt(fan_in) if fan_in > 0 else 0
nn.init.uniform_(self.bias2, -bound, bound)


def forward(self, input):
return fused_dense_gelu_dense_function(input, self.weight1, self.bias1, self.weight2, self.bias2)
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7 changes: 5 additions & 2 deletions tests/L0/run_fused_dense/test_gelu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,8 @@
class FusedDenseGeluDenseTest(unittest.TestCase):

def test_fused_dense_gelu_dense(self) :
seed = 0
torch.manual_seed(seed)
batch_size = 4
in_features = 3
intermediate_features = 3
Expand All @@ -16,7 +18,7 @@ def test_fused_dense_gelu_dense(self) :
# tst_dtype = torch.float8_e5m2
tst_dtype = torch.float16

I = torch.randn(batch_size, in_features, dtype=tst_dtype, device='cuda')
I = torch.randn(batch_size, in_features, dtype=tst_dtype, device='cuda').requires_grad_(True)

denseGelu = fused_dense.FusedDenseGeluDense(in_features, intermediate_features, out_features)
denseGelu.to(dtype=tst_dtype)
Expand All @@ -28,10 +30,11 @@ def test_fused_dense_gelu_dense(self) :
W2 = denseGelu.weight2
b2 = denseGelu.bias2

y_tst = denseGelu(I.clone().detach().requires_grad_(True))

C1 = torch.matmul(I, W1.t())+b1
gelu_output = F.gelu(C1)
y_ref = torch.matmul(gelu_output, W2.t())+b2
y_tst = denseGelu(I)
torch.testing.assert_close(y_ref, y_tst, atol=1e-3, rtol=1e-3, equal_nan=True)


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