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Remove used examples asyncronously.

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This commit is contained in:
Tomasz Sobczyk
2020-11-25 23:12:02 +01:00
committed by nodchip
parent 0bee8fef64
commit 34510dd08a
1 changed files with 12 additions and 5 deletions
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17
src/nnue/evaluate_nnue_learner.cpp
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@@ -214,9 +214,10 @@ namespace Eval::NNUE {
std::vector<double> abs_discrete_eval_sum_local(thread_pool.size(), 0.0);
std::vector<double> gradient_norm_local(thread_pool.size(), 0.0);
while (examples.size() >= batch_size) {
auto batch_begin = examples.end() - batch_size;
auto batch_end = examples.end();
auto prev_batch_begin = examples.end();
while (prev_batch_begin - examples.begin() >= batch_size) {
auto batch_begin = prev_batch_begin - batch_size;
auto batch_end = prev_batch_begin;
auto size = batch_end - batch_begin;
const auto network_output = trainer->step_start(thread_pool, batch_begin, batch_end);
std::vector<LearnFloatType> gradients(size);
@@ -253,14 +254,20 @@ namespace Eval::NNUE {
trainer->backpropagate(th, gradients.data(), offset, count);
}
);
// We can asyncronously erase the examples that we used in the previous
// step. This can be done safely because we're no longer using these
// examples and erase won't invalidate iterators.
examples.erase(prev_batch_begin, examples.end());
prev_batch_begin = batch_begin;
thread_pool.wait_for_workers_finished();
trainer->step_end(thread_pool, learning_rate);
examples.resize(examples.size() - size);
collect_stats = false;
}
examples.erase(prev_batch_begin, examples.end());
if (verbose)
{