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style: run clang-format and configure pre-commit hooks

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AI-anonymous
2026-05-20 00:18:23 +02:00
parent 041eab7155
commit 3b15770437
28 changed files with 2226 additions and 2061 deletions
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51
tests/test_optimizer.cpp
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@@ -1,42 +1,45 @@
#include "fces/optimizer.hpp"
#include <gtest/gtest.h>
#include <torch/torch.h>
#include "fces/optimizer.hpp"
using namespace fces;
TEST(OptimizerTest, Construction) {
auto model = torch::nn::Linear(10, 5);
std::vector<torch::Tensor> params;
for (auto& p : model->parameters()) params.push_back(p);
auto model = torch::nn::Linear(10, 5);
std::vector<torch::Tensor> params;
for (auto &p : model->parameters())
params.push_back(p);
FCESOptimizer opt(params, FCESConfig{}.set_lr(1e-3f));
EXPECT_EQ(opt.step_count(), 0);
FCESOptimizer opt(params, FCESConfig{}.set_lr(1e-3f));
EXPECT_EQ(opt.step_count(), 0);
}
TEST(OptimizerTest, StepUpdatesCounter) {
auto model = torch::nn::Linear(10, 5);
std::vector<torch::Tensor> params;
for (auto& p : model->parameters()) params.push_back(p);
auto model = torch::nn::Linear(10, 5);
std::vector<torch::Tensor> params;
for (auto &p : model->parameters())
params.push_back(p);
FCESOptimizer opt(params, FCESConfig{}.set_lr(1e-3f));
FCESOptimizer opt(params, FCESConfig{}.set_lr(1e-3f));
// Simulate a training step
auto x = torch::randn({2, 10});
auto y = model->forward(x);
auto loss = y.sum();
loss.backward();
opt.step();
// Simulate a training step
auto x = torch::randn({2, 10});
auto y = model->forward(x);
auto loss = y.sum();
loss.backward();
opt.step();
EXPECT_EQ(opt.step_count(), 1);
EXPECT_EQ(opt.step_count(), 1);
}
TEST(OptimizerTest, UpdateFitness) {
auto model = torch::nn::Linear(10, 5);
std::vector<torch::Tensor> params;
for (auto& p : model->parameters()) params.push_back(p);
auto model = torch::nn::Linear(10, 5);
std::vector<torch::Tensor> params;
for (auto &p : model->parameters())
params.push_back(p);
FCESOptimizer opt(params);
opt.update_fitness(3.0f);
opt.update_fitness(2.5f);
// Should not crash
FCESOptimizer opt(params);
opt.update_fitness(3.0f);
opt.update_fitness(2.5f);
// Should not crash
}