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Make all grad related functions in learn static. Pass calc_grad as a parameter.

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This commit is contained in:
Tomasz Sobczyk
2020-10-24 23:29:32 +02:00
committed by nodchip
parent e4868cb59e
commit cde6ec2bf2
4 changed files with 23 additions and 30 deletions
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7
src/nnue/evaluate_nnue_learner.cpp
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@@ -18,8 +18,6 @@
#include "misc.h"
#include "thread_win32_osx.h"
#include "learn/learn.h"
// Learning rate scale
double global_learning_rate;
@@ -183,7 +181,7 @@ namespace Eval::NNUE {
}
// update the evaluation function parameters
void update_parameters(uint64_t epoch, bool verbose) {
void update_parameters(uint64_t epoch, bool verbose, Learner::CalcGradFunc calc_grad) {
assert(batch_size > 0);
const auto learning_rate = static_cast<LearnFloatType>(
@@ -210,7 +208,8 @@ namespace Eval::NNUE {
batch[b].sign * network_output[b] * kPonanzaConstant));
const auto discrete = batch[b].sign * batch[b].discrete_nn_eval;
const auto& psv = batch[b].psv;
const double gradient = batch[b].sign * Learner::calc_grad(shallow, psv);
const double gradient =
batch[b].sign * calc_grad(shallow, (Value)psv.score, psv.game_result, psv.gamePly);
gradients[b] = static_cast<LearnFloatType>(gradient * batch[b].weight);