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Cleaned Report callback PR. #17

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8041e4e
add PyReport class and expose it
gauravmanmode May 22, 2025
4765d9c
add tests
gauravmanmode Aug 12, 2025
46ad233
add notebook
gauravmanmode Aug 12, 2025
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226 changes: 226 additions & 0 deletions notebooks/report.ipynb
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Original file line number Diff line number Diff line change
@@ -0,0 +1,226 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "e6898559",
"metadata": {},
"source": [
"# How to get more info about the optimization run\n",
"\n",
"The `report` parameter is optional when initializing the optimizer.\n",
"For detailed run information, provide a Report callback object to the optimizer. \n",
"This is done by passing an instance of the Report callback class during initialization."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "f6b0aef6",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pyensmallen as pye\n",
"from pprint import pprint"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "25fc7777",
"metadata": {},
"outputs": [],
"source": [
"def square(x):\n",
" return x@x\n",
"\n",
"def objective_function(x, grad):\n",
" grad[:] = 2*x\n",
" return square(x)\n",
" "
]
},
{
"cell_type": "markdown",
"id": "a3ad6515",
"metadata": {},
"source": [
"It is optional to get a more detailed optimization report.\n",
"You can run the optimizer normally."
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "1eeb4af0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[-1.13686838e-13 1.13686838e-13]\n"
]
}
],
"source": [
"# Initial guess\n",
"initial_x = np.array([-1000, 1000.0])\n",
"\n",
"# Initialize L-BFGS optimizer\n",
"optimizer = pye.L_BFGS()\n",
"\n",
"# Optimize\n",
"result = optimizer.optimize(objective_function, initial_x)\n",
"\n",
"print(result)"
]
},
{
"cell_type": "markdown",
"id": "407d1a4c",
"metadata": {},
"source": [
"## Getting more info about the optimization\n",
"Passing this callback object allows to retrieve more info about the optimization run."
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "e9b998dc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[-1.13686838e-13 1.13686838e-13]\n",
"{'evaluate_calls': 10,\n",
" 'gradient_calls': 10,\n",
" 'iterations': 2,\n",
" 'objective_value': 2.5849394142282115e-26,\n",
" 'total_time': 3.4675e-05}\n"
]
}
],
"source": [
"\n",
"# Initialize L-BFGS optimizer\n",
"optimizer = pye.L_BFGS()\n",
"\n",
"# Initialize a dict to store optimization run info \n",
"info = dict()\n",
"\n",
"# Initialize Report callback object \n",
"report = pye.Report(info, disableOutput=True)\n",
"\n",
"# Initialize L-BFGS optimizer passing a Report object\n",
"result = optimizer.optimize(objective_function, initial_x, report=report)\n",
"print(result)\n",
"pprint(info)"
]
},
{
"cell_type": "markdown",
"id": "5ef84c09",
"metadata": {},
"source": [
"By setting `disableOutput=False`, callback prints a optimizer report to stdout which shows various info about the optimization run."
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "09f97e11",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Modified Optimization Report\n",
"--------------------------------------------------------------------------------\n",
"\n",
"Initial Coordinates:\n",
" -1.0000e+03 1.0000e+03\n",
"\n",
"Final coordinates:\n",
" -1.1369e-13 1.1369e-13\n",
"\n",
"iter loss loss change |gradient| total time \n",
"0 1.52e+06 0 2.47e+03 2.87e-05 \n",
"1 2.58e-26 1.52e+06 3.22e-13 3.44e-05 \n",
"\n",
"--------------------------------------------------------------------------------\n",
"\n",
"Version:\n",
"ensmallen: 2.22.1 (E-Bike Excitement)\n",
"armadillo: 12.6.7 (Cortisol Retox)\n",
"\n",
"Function:\n",
"Number of functions: 1\n",
"Coordinates rows: 2\n",
"Coordinates columns: 1\n",
"\n",
"Loss:\n",
"Initial 1.52e+06\n",
"Final 2.58e-26\n",
"Change 1.52e+06\n",
"\n",
"Optimizer:\n",
"Maximum iterations: 10000\n",
"Reached maximum iterations: false\n",
"Iterations: 2\n",
"Coordinates max. norm: 2.47e+03\n",
"Evaluate calls: 10\n",
"Gradient calls: 10\n",
"Time (in seconds): 3.44e-05\n"
]
}
],
"source": [
"# Initialize L-BFGS optimizer\n",
"optimizer = pye.L_BFGS()\n",
"\n",
"# Initialize a dict to store optimization run info \n",
"info = dict()\n",
"\n",
"# Initialize Report callback object \n",
"report = pye.Report(info, disableOutput=False)\n",
"\n",
"# Initialize L-BFGS optimizer passing a Report object\n",
"result = optimizer.optimize(objective_function, initial_x, report=report)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2da4dbe3",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "optimagic",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.18"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
21 changes: 19 additions & 2 deletions pyensmallen/module.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,12 @@
#include "newton_type.hpp"
#include "constrained.hpp"
#include "first_order.hpp"

#include "report.hpp"
namespace py = pybind11;

PYBIND11_MODULE(_pyensmallen, m)
{

// L-BFGS (Newton-type) optimizer
py::class_<PyL_BFGS>(m, "L_BFGS")
.def(py::init<>())
Expand Down Expand Up @@ -40,7 +41,11 @@ PYBIND11_MODULE(_pyensmallen, m)
&PyL_BFGS::setMaxLineSearchTrials)
.def_property("minStep", &PyL_BFGS::getMinStep, &PyL_BFGS::setMinStep)
.def_property("maxStep", &PyL_BFGS::getMaxStep, &PyL_BFGS::setMaxStep)
.def("optimize", &PyL_BFGS::Optimize);
.def("optimize", &PyL_BFGS::Optimize,
py::arg("f"),
py::arg("initial_point"),
py::arg("report") = nullptr);


// FrankWolfe - constrained optimization
py::class_<PyFrankWolfe>(m, "FrankWolfe")
Expand Down Expand Up @@ -245,4 +250,16 @@ PYBIND11_MODULE(_pyensmallen, m)
&PyAdamType<ens::NadamUpdate>::getResetPolicy,
&PyAdamType<ens::NadamUpdate>::setResetPolicy)
.def("optimize", &PyAdamType<ens::NadamUpdate>::Optimize);

py::class_<ens::PyReport>(m, "Report")
.def(py::init<
py::dict,
bool,
double,
size_t>(),
py::arg("resultIn"),
py::arg("disableOutput") = false,
py::arg("iterationsPercentageIn") = 0.1,
py::arg("outputMatrixSizeIn") = 4
);
}
29 changes: 16 additions & 13 deletions pyensmallen/newton_type.hpp
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
#pragma once

#include "utils.hpp"
#include "report.hpp"

// Wrapper for L-BFGS optimizer
class PyL_BFGS
Expand Down Expand Up @@ -79,19 +80,21 @@ class PyL_BFGS
void setMaxStep(double maxStep) { optimizer.MaxStep() = maxStep; }

py::array_t<double> Optimize(DifferentiableFunction f,
py::array_t<double> initial_point)
{
py::buffer_info buf_info = initial_point.request();
arma::vec arma_initial_point(static_cast<double *>(buf_info.ptr),
buf_info.shape[0], false, true);

DifferentiableFunctionWrapper fw(f);
arma::vec result = arma_initial_point;

optimizer.Optimize(fw, result);

return py::array_t<double>(result.n_elem, result.memptr());
}
py::array_t<double> initial_point, ens::PyReport* report = nullptr)
{
py::buffer_info buf_info = initial_point.request();
arma::vec arma_initial_point(static_cast<double *>(buf_info.ptr),
buf_info.shape[0], false, true);

DifferentiableFunctionWrapper fw(f);
arma::vec result = arma_initial_point;
if (report)
optimizer.Optimize(fw, result, *report);
else
optimizer.Optimize(fw, result);
return py::array_t<double>(result.n_elem, result.memptr());

}

private:
ens::L_BFGS optimizer;
Expand Down
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