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Merged
soumith merged 5 commits into from
Jun 8, 2018
Merged

Stop BCELoss from returning negative results #8147

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4fb0dfe
Stop BCELoss from returning negative results
Jun 5, 2018
22df924
check explicitly for 0 before taking log
Jun 5, 2018
229472b
add tests
Jun 7, 2018
654ac99
fix lint
Jun 7, 2018
b5c1fd8
address comments
Jun 7, 2018
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20 changes: 15 additions & 5 deletions aten/src/THCUNN/BCECriterion.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,15 @@ inline __host__ __device__ float eps() { return 1e-12f; }
template <>
inline __host__ __device__ double eps() { return 1e-12; }

template <typename T>
inline __host__ __device__ T safe_log(T a) {
if (a == 0.)
{
return THCNumerics<T>::log(eps<T>());
}
return THCNumerics<T>::log(a);
}

template <typename Dtype, typename Acctype>
struct bce_functor
{
Expand All @@ -31,7 +40,8 @@ struct bce_functor
Dtype input = thrust::get<0>(x);
Dtype t = thrust::get<1>(x);
assert(input >= 0. && input <= 1.);
return - (t * THCNumerics<Acctype>::log(input + eps<Acctype>()) + (Acctype(1)- t) * THCNumerics<Acctype>::log(Acctype(1) - input + eps<Acctype>()));
return - (t * safe_log<Acctype>(ScalarConvert<Dtype, Acctype>::to(input))
+ (Acctype(1) - t) * safe_log<Acctype>(Acctype(1) - input));
}
};

Expand All @@ -46,8 +56,8 @@ struct bce_updateOutput_no_reduce_functor
{
assert(*input >= 0. && *input <= 1.);
*output = ScalarConvert<Acctype, Dtype>::to(
-(*target * THCNumerics<Acctype>::log(*input + eps<Acctype>()) +
(Acctype(1) - *target) * THCNumerics<Acctype>::log(Acctype(1) - *input + eps<Acctype>())));
-(*target * safe_log<Acctype>(ScalarConvert<Dtype, Acctype>::to(*input)) +
(Acctype(1) - *target) * safe_log<Acctype>(Acctype(1) - *input)));
}
};

Expand All @@ -62,8 +72,8 @@ struct bce_functor_weights
Dtype t = thrust::get<1>(x);
Dtype w = thrust::get<2>(x);
assert(input >= 0. && input <= 1.);
return - w * (t * THCNumerics<Acctype>::log(input + eps<Acctype>()) +
(Acctype(1) - t) * THCNumerics<Acctype>::log(Acctype(1) - input + eps<Acctype>()));
return - w * (t * safe_log<Acctype>(ScalarConvert<Dtype, Acctype>::to(input)) +
(Acctype(1) - t) * safe_log<Acctype>(Acctype(1) - input));
}
};

Expand Down
13 changes: 10 additions & 3 deletions aten/src/THNN/generic/BCECriterion.c
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,13 @@

#define EPS 1e-12

static inline real safe_log(real a) {
if (a == 0.) {
return log(EPS);
}
return log(a);

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}

void THNN_(BCECriterion_updateOutput)(
THNNState *state,
THTensor *input,
Expand All @@ -24,7 +31,7 @@ void THNN_(BCECriterion_updateOutput)(
THAssertMsg(x >= 0. && x <= 1.,
"input value should be between 0~1, but got %f",
(double) x);
*output_data = -(log(x + EPS) * y + log(1. - x + EPS) * (1. - y));
*output_data = -(safe_log(x) * y + safe_log(1. - x) * (1. - y));
);
if (weights) {
THTensor_(cmul)(output, output, weights);
Expand All @@ -43,7 +50,7 @@ void THNN_(BCECriterion_updateOutput)(
THAssertMsg(x >= 0. && x <= 1.,
"input value should be between 0~1, but got %f",
(double) x);
sum -= (log(x + EPS) * y + log(1. - x + EPS) * (1. - y)) * w;
sum -= (safe_log(x) * y + safe_log(1. - x) * (1. - y)) * w;
);
} else {
TH_TENSOR_APPLY2(real, input, real, target,
Expand All @@ -52,7 +59,7 @@ void THNN_(BCECriterion_updateOutput)(
THAssertMsg(x >= 0. && x <= 1.,
"input value should be between 0~1, but got %f",
(double) x);
sum -= log(x + EPS) * y + log(1. - x + EPS) * (1. - y);
sum -= safe_log(x) * y + safe_log(1. - x) * (1. - y);
);
}

Expand Down
9 changes: 9 additions & 0 deletions test/test_nn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4116,6 +4116,15 @@ def func(root):
gradcheck(func, [v])
gradgradcheck(func, [v])

def test_bce_loss_always_nonnegative(self):
target = torch.ones(5)
input = torch.ones(5)
self.assertEqual((nn.BCELoss()(input, target) < 0).sum(), 0)

target = torch.zeros(5)
input = torch.zeros(5)
self.assertEqual((nn.BCELoss()(input, target) < 0).sum(), 0)

def test_bce_with_logits_raises_if_target_and_input_are_different_size(self):
target = torch.rand(5)
input = torch.rand(5, 1)
Expand Down