feat: implement FCES optimizer python bindings, add telemetry & comparative Ackley benchmark
This commit is contained in:
AI-anonymous
125
python/compare_fces_adam.py
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125
python/compare_fces_adam.py
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import os
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import sys
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from typing import List, Tuple
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# Ensure python folder is in path
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python_dir = os.path.dirname(os.path.abspath(__file__))
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sys.path.insert(0, python_dir)
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import torch # noqa: E402
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import fces_native # noqa: E402
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from send_telemetry import push_to_mariadb, push_to_surrealdb # noqa: E402
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def ackley(w: torch.Tensor) -> torch.Tensor:
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x, y = w[0], w[1]
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part1 = -20.0 * torch.exp(-0.2 * torch.sqrt(0.5 * (x**2 + y**2)))
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part2 = -torch.exp(
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0.5 * (torch.cos(2 * 3.1415926535 * x) + torch.cos(2 * 3.1415926535 * y))
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)
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return part1 + part2 + 2.718281828459 + 20.0
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def run_adamw(steps: int = 200) -> Tuple[List[float], torch.Tensor]:
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torch.manual_seed(42)
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# Start at x=3.0, y=3.0 (trapped in a local minimum)
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w = torch.tensor([3.0, 3.0])
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w.requires_grad_(True)
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optimizer = torch.optim.AdamW([w], lr=0.1)
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losses = []
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for step in range(steps):
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optimizer.zero_grad()
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loss = ackley(w)
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loss.backward()
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optimizer.step()
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losses.append(float(loss.item()))
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return losses, w.detach().clone()
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def run_fces(steps: int = 200) -> Tuple[List[float], torch.Tensor]:
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torch.manual_seed(42)
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# Start at x=3.0, y=3.0
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w = torch.tensor([3.0, 3.0])
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w.requires_grad_(True)
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cfg = fces_native.FCESConfig()
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cfg.lr = 0.1
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cfg.population_size = 64
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cfg.total_steps = steps
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optimizer = fces_native.FCESOptimizer([w], cfg)
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losses = []
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for step in range(steps):
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optimizer.zero_grad()
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loss = ackley(w)
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loss.backward()
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optimizer.step()
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optimizer.update_fitness(float(loss.item()))
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losses.append(float(loss.item()))
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return losses, w.detach().clone()
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def main() -> None:
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print("=" * 80)
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print(
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" FCES VS ADAMW CONVERGENCE BENCHMARK (NON-CONVEX ACKLEY FUNCTION) "
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)
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print("=" * 80)
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steps = 200
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print("[INFO] Running AdamW baseline...")
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adam_losses, adam_final_w = run_adamw(steps)
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print("[INFO] Running FCES optimizer...")
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fces_losses, fces_final_w = run_fces(steps)
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print("\n" + "-" * 40 + " BENCHMARK RESULT SUMMARY " + "-" * 40)
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print(f"{'Step':<10}{'AdamW Loss':<20}{'FCES Loss':<20}{'FCES Improvement':<20}")
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print("-" * 106)
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telemetry_entries = []
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for idx in range(0, steps, 20):
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improvement = adam_losses[idx] - fces_losses[idx]
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pct = (improvement / adam_losses[idx]) * 100 if adam_losses[idx] > 0 else 0
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print(f"{idx:<10}{adam_losses[idx]:<20.6f}{fces_losses[idx]:<20.6f}{pct:.2f}%")
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telemetry_entries.append(
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(
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"INFO",
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"benchmark_step",
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f"Step {idx} | AdamW Loss: {adam_losses[idx]:.4f} | FCES Loss: {fces_losses[idx]:.4f}",
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)
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)
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print("-" * 106)
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print(f"Final AdamW Loss: {adam_losses[-1]:.6f} (Final w: {adam_final_w.numpy()})")
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print(f"Final FCES Loss: {fces_losses[-1]:.6f} (Final w: {fces_final_w.numpy()})")
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# Calculate ratio improvement
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improvement_factor = adam_losses[-1] - fces_losses[-1]
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print(f"FCES Absolute Improvement: {improvement_factor:.6f} lower loss!")
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print("=" * 80)
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# Send telemetry
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push_to_surrealdb(telemetry_entries)
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push_to_mariadb(telemetry_entries)
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# Save results to a summary file
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summary_path = os.path.join(os.path.dirname(python_dir), "benchmark_summary.txt")
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with open(summary_path, "w") as f:
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f.write("FCES vs AdamW Optimization Benchmark (Ackley Function)\n")
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f.write(
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f"Final AdamW Loss: {adam_losses[-1]:.6f} (w: {adam_final_w.numpy()})\n"
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)
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f.write(
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f"Final FCES Loss: {fces_losses[-1]:.6f} (w: {fces_final_w.numpy()})\n"
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)
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f.write(f"Absolute Improvement: {improvement_factor:.6f}\n")
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print(f"[INFO] Benchmark summary saved to {summary_path}")
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if __name__ == "__main__":
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main()
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@@ -34,7 +34,7 @@ PYBIND11_MODULE(fces_native, m) {
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py::class_<fces::FCESOptimizer>(m, "FCESOptimizer")
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.def(py::init<std::vector<torch::Tensor>, fces::FCESConfig>(),
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py::arg("params"), py::arg("config") = fces::FCESConfig{})
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.def("step", &fces::FCESOptimizer::step)
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.def("step", [](fces::FCESOptimizer &self) { return self.step(); })
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.def("update_fitness", &fces::FCESOptimizer::update_fitness)
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.def("backup_to_ram", &fces::FCESOptimizer::backup_to_ram)
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.def("restore_from_ram", &fces::FCESOptimizer::restore_from_ram)
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199
python/send_telemetry.py
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199
python/send_telemetry.py
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import os
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import urllib.request
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import json
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import subprocess
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from typing import List, Tuple
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LOG_FILE = "telemetry.log"
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OFFSET_FILE = "telemetry.offset"
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DB_URL = "http://localhost:8000/sql"
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NAMESPACE = "omega"
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DATABASE = "fces"
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def push_to_surrealdb(entries: List[Tuple[str, str, str]]) -> bool:
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if not entries:
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return True
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# Construct SurrealQL queries
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queries = []
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for entry in entries:
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level, event, detail = entry
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# Escape quotes for safety in SurrealQL
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level_esc = level.replace("'", "\\'")
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event_esc = event.replace("'", "\\'")
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detail_esc = detail.replace("'", "\\'")
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query = f"CREATE telemetry CONTENT {{ level: '{level_esc}', event: '{event_esc}', detail: '{detail_esc}', timestamp: time::now() }};"
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queries.append(query)
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prefix = f"DEFINE NAMESPACE {NAMESPACE};\nUSE NS {NAMESPACE};\nDEFINE DATABASE {DATABASE};\nUSE DB {DATABASE};\n"
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sql_script = prefix + "\n".join(queries)
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import base64
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auth_str = base64.b64encode(b"root:root").decode("utf-8")
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headers = {"Accept": "application/json", "Authorization": f"Basic {auth_str}"}
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req = urllib.request.Request(
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DB_URL, data=sql_script.encode("utf-8"), headers=headers, method="POST"
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)
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try:
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with urllib.request.urlopen(req, timeout=5) as response:
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res_data = json.loads(response.read().decode("utf-8"))
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# Filter query results: ignore "AlreadyExists" status ERR
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db_errors = []
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if isinstance(res_data, list):
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for r in res_data:
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if r.get("status") == "ERR":
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kind = r.get("kind")
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if kind != "AlreadyExists":
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db_errors.append(r)
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else:
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db_errors.append(res_data)
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if not db_errors:
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print(f"Successfully pushed {len(entries)} entries to SurrealDB.")
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return True
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else:
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print(f"SurrealDB query warning/error: {db_errors}")
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return False
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except Exception as e:
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print(f"Failed to connect/push to SurrealDB: {e}")
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return False
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def push_to_mariadb(entries: List[Tuple[str, str, str]]) -> bool:
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if not entries:
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return True
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# Connection details
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host = os.getenv("SQL_HOST", "zky.de")
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port_str = os.getenv("SQL_PORT", "3306")
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try:
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port = int(port_str)
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except ValueError:
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port = 3306
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user = os.getenv("SQL_USER", "c1_kaggle")
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password = os.getenv("SQL_PASS", "!Dommke2026")
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db = os.getenv("SQL_DB", "c1_kaggle")
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try:
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import mysql.connector
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conn = mysql.connector.connect(
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host=host,
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port=port,
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user=user,
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password=password,
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database=db,
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connect_timeout=5,
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)
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cursor = conn.cursor()
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# Create table if not exists
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS telemetry (
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id INT AUTO_INCREMENT PRIMARY KEY,
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level VARCHAR(50),
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event VARCHAR(255),
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detail TEXT,
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timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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# Insert entries
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sql = "INSERT INTO telemetry (level, event, detail) VALUES (%s, %s, %s)"
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cursor.executemany(sql, entries)
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conn.commit()
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cursor.close()
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conn.close()
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print(f"Successfully pushed {len(entries)} entries to MariaDB.")
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return True
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except Exception as e:
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print(f"Failed to connect/push to MariaDB: {e}")
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return False
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def push_to_git() -> None:
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try:
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# Check if there are changes in telemetry.log
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status = subprocess.run(
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["git", "status", "--porcelain", LOG_FILE], capture_output=True, text=True
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)
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if status.stdout.strip():
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print("Committing and pushing telemetry.log to git.zky.de...")
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subprocess.run(["git", "add", LOG_FILE], check=True)
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subprocess.run(
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["git", "commit", "-m", "chore: update telemetry log [skip ci]"],
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check=True,
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)
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subprocess.run(["git", "push", "origin", "main"], check=True)
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print("Successfully pushed telemetry.log to git.zky.de.")
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else:
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print("No changes in telemetry.log to push to git.")
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except Exception as e:
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print(f"Git push failed: {e}")
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def main() -> None:
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if not os.path.exists(LOG_FILE):
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print(f"Log file {LOG_FILE} does not exist.")
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return
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# Read offset
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offset = 0
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if os.path.exists(OFFSET_FILE):
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try:
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with open(OFFSET_FILE, "r") as f:
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offset = int(f.read().strip())
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except Exception:
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offset = 0
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# Read new lines from log file
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new_entries: List[Tuple[str, str, str]] = []
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file_size = os.path.getsize(LOG_FILE)
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if file_size > offset:
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with open(LOG_FILE, "r", encoding="utf-8") as f:
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f.seek(offset)
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new_lines = f.readlines()
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for line in new_lines:
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line = line.strip()
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if not line:
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continue
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# Parse line format: [LEVEL] event | detail
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# or just [LEVEL] event
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try:
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if "] " in line:
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level_part, rest = line.split("] ", 1)
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level = level_part.replace("[", "").strip()
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if " | " in rest:
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event, detail = rest.split(" | ", 1)
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else:
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event = rest
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detail = ""
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new_entries.append((level, event, detail))
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except Exception as pe:
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print(f"Failed to parse line: {line} ({pe})")
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# Push to SurrealDB
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db_success = push_to_surrealdb(new_entries)
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# Push to MariaDB
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maria_success = push_to_mariadb(new_entries)
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if db_success or maria_success:
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# Update offset if either DB push succeeded
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with open(OFFSET_FILE, "w") as f:
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f.write(str(file_size))
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# Always try to push to Git if there are any updates
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push_to_git()
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if __name__ == "__main__":
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main()
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@@ -1,6 +1,10 @@
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import os
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from setuptools import setup
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from torch.utils.cpp_extension import BuildExtension, CppExtension
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# Get absolute path to project directory
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proj_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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setup(
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name="fces_native",
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version="0.1.0",
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@@ -10,17 +14,17 @@ setup(
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name="fces_native",
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sources=[
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"fces_native.cpp",
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"../src/config.cpp",
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"../src/controller.cpp",
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"../src/population.cpp",
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"../src/fitness.cpp",
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"../src/evolution.cpp",
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"../src/spectral.cpp",
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"../src/oscillation.cpp",
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"../src/optimizer.cpp",
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"../src/telemetry.cpp",
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os.path.join(proj_dir, "src", "config.cpp"),
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os.path.join(proj_dir, "src", "controller.cpp"),
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os.path.join(proj_dir, "src", "population.cpp"),
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os.path.join(proj_dir, "src", "fitness.cpp"),
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os.path.join(proj_dir, "src", "evolution.cpp"),
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os.path.join(proj_dir, "src", "spectral.cpp"),
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os.path.join(proj_dir, "src", "oscillation.cpp"),
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os.path.join(proj_dir, "src", "optimizer.cpp"),
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os.path.join(proj_dir, "src", "telemetry.cpp"),
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],
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include_dirs=["../include"],
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include_dirs=[os.path.join(proj_dir, "include")],
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),
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],
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cmdclass={"build_ext": BuildExtension},
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