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Move cross_entropy calculation to a separate function.

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This commit is contained in:
Tomasz Sobczyk
2020-11-30 15:21:39 +01:00
committed by nodchip
parent 891abf5511
commit e975889132
1 changed files with 24 additions and 9 deletions
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src/learn/learn.cpp
+24 -9
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@@ -197,6 +197,29 @@ namespace Learner
return lambda; return lambda;
} }
template <typename ShallowT, typename TeacherT, typename ResultT, typename LambdaT>
static auto& cross_entropy_(
ShallowT& q_,
TeacherT& p_,
ResultT& t_,
LambdaT& lambda_
)
{
using namespace Learner::Autograd::UnivariateStatic;
constexpr double epsilon = 1e-12;
static thread_local auto teacher_entropy_ = -(p_ * log(p_ + epsilon) + (1.0 - p_) * log(1.0 - p_ + epsilon));
static thread_local auto outcome_entropy_ = -(t_ * log(t_ + epsilon) + (1.0 - t_) * log(1.0 - t_ + epsilon));
static thread_local auto teacher_loss_ = -(p_ * log(q_) + (1.0 - p_) * log(1.0 - q_));
static thread_local auto outcome_loss_ = -(t_ * log(q_) + (1.0 - t_) * log(1.0 - q_));
static thread_local auto result_ = lambda_ * teacher_loss_ + (1.0 - lambda_) * outcome_loss_;
static thread_local auto entropy_ = lambda_ * teacher_entropy_ + (1.0 - lambda_) * outcome_entropy_;
static thread_local auto loss_ = result_ - entropy_;
return loss_;
}
static ValueWithGrad<double> get_loss(Value shallow, Value teacher_signal, int result, int ply) static ValueWithGrad<double> get_loss(Value shallow, Value teacher_signal, int result, int ply)
{ {
using namespace Learner::Autograd::UnivariateStatic; using namespace Learner::Autograd::UnivariateStatic;
@@ -215,19 +238,11 @@ namespace Learner
auto loss_ = pow(q_ - p_, 2.0) * (1.0 / (2400.0 * 2.0 * 600.0)); auto loss_ = pow(q_ - p_, 2.0) * (1.0 / (2400.0 * 2.0 * 600.0));
*/ */
constexpr double epsilon = 1e-12;
static thread_local auto q_ = sigmoid(VariableParameter<double, 0>{} * ConstantParameter<double, 4>{}); static thread_local auto q_ = sigmoid(VariableParameter<double, 0>{} * ConstantParameter<double, 4>{});
static thread_local auto p_ = sigmoid(ConstantParameter<double, 1>{} * ConstantParameter<double, 4>{}); static thread_local auto p_ = sigmoid(ConstantParameter<double, 1>{} * ConstantParameter<double, 4>{});
static thread_local auto t_ = (ConstantParameter<double, 2>{} + 1.0) * 0.5; static thread_local auto t_ = (ConstantParameter<double, 2>{} + 1.0) * 0.5;
static thread_local auto lambda_ = ConstantParameter<double, 3>{}; static thread_local auto lambda_ = ConstantParameter<double, 3>{};
static thread_local auto teacher_entropy_ = -(p_ * log(p_ + epsilon) + (1.0 - p_) * log(1.0 - p_ + epsilon)); static thread_local auto loss_ = cross_entropy_(q_, p_, t_, lambda_);
static thread_local auto outcome_entropy_ = -(t_ * log(t_ + epsilon) + (1.0 - t_) * log(1.0 - t_ + epsilon));
static thread_local auto teacher_loss_ = -(p_ * log(q_) + (1.0 - p_) * log(1.0 - q_));
static thread_local auto outcome_loss_ = -(t_ * log(q_) + (1.0 - t_) * log(1.0 - q_));
static thread_local auto result_ = lambda_ * teacher_loss_ + (1.0 - lambda_) * outcome_loss_;
static thread_local auto entropy_ = lambda_ * teacher_entropy_ + (1.0 - lambda_) * outcome_entropy_;
static thread_local auto loss_ = result_ - entropy_;
auto args = std::tuple( auto args = std::tuple(
(double)shallow, (double)shallow,