9bbe253810
- CMakeLists.txt with libtorch, GoogleTest, GoogleBenchmark, OpenMP, pybind11 - Header files: config, controller, population, fitness, evolution, spectral, oscillation, telemetry, optimizer - Source implementations: controller (full micro-MLP forward pass, mutation, crossover), fitness (Welford's algorithm), oscillation (DFT), spectral (SVD rank), optimizer (sign-SGD stub) - Tests: controller, population, fitness, optimizer (Google Test) - Benchmarks: evolve throughput, optimizer step (Google Benchmark) - Examples: simple optimization, PyTorch/libtorch integration - Python extension: pybind11 bindings with setup.py - README with architecture diagram and build instructions
26 lines
719 B
C++
26 lines
719 B
C++
#include <benchmark/benchmark.h>
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#include <torch/torch.h>
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#include "fces/optimizer.hpp"
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using namespace fces;
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static void BM_OptimizerStep(benchmark::State& state) {
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auto model = torch::nn::Linear(state.range(0), state.range(0) / 2);
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std::vector<torch::Tensor> params;
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for (auto& p : model->parameters()) params.push_back(p);
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FCESOptimizer opt(params, FCESConfig{}.set_lr(1e-3f));
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auto x = torch::randn({8, state.range(0)});
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for (auto _ : state) {
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auto y = model->forward(x);
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auto loss = y.sum();
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loss.backward();
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opt.step();
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opt.zero_grad();
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benchmark::DoNotOptimize(loss);
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}
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}
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BENCHMARK(BM_OptimizerStep)->Arg(64)->Arg(256)->Arg(1024);
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