You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
250 lines
15 KiB
250 lines
15 KiB
<!doctype html>
|
|
<html lang="en">
|
|
<head>
|
|
<meta charset="utf-8">
|
|
<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
|
|
<meta name="generator" content="pdoc 0.7.0" />
|
|
<title>miplearn.solvers.tests API documentation</title>
|
|
<meta name="description" content="" />
|
|
<link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
|
|
<link href='https://cdnjs.cloudflare.com/ajax/libs/10up-sanitize.css/8.0.0/sanitize.min.css' rel='stylesheet'>
|
|
<link href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/github.min.css" rel="stylesheet">
|
|
<style>.flex{display:flex !important}body{line-height:1.5em}#content{padding:20px}#sidebar{padding:30px;overflow:hidden}.http-server-breadcrumbs{font-size:130%;margin:0 0 15px 0}#footer{font-size:.75em;padding:5px 30px;border-top:1px solid #ddd;text-align:right}#footer p{margin:0 0 0 1em;display:inline-block}#footer p:last-child{margin-right:30px}h1,h2,h3,h4,h5{font-weight:300}h1{font-size:2.5em;line-height:1.1em}h2{font-size:1.75em;margin:1em 0 .50em 0}h3{font-size:1.4em;margin:25px 0 10px 0}h4{margin:0;font-size:105%}a{color:#058;text-decoration:none;transition:color .3s ease-in-out}a:hover{color:#e82}.title code{font-weight:bold}h2[id^="header-"]{margin-top:2em}.ident{color:#900}pre code{background:#f8f8f8;font-size:.8em;line-height:1.4em}code{background:#f2f2f1;padding:1px 4px;overflow-wrap:break-word}h1 code{background:transparent}pre{background:#f8f8f8;border:0;border-top:1px solid #ccc;border-bottom:1px solid #ccc;margin:1em 0;padding:1ex}#http-server-module-list{display:flex;flex-flow:column}#http-server-module-list div{display:flex}#http-server-module-list dt{min-width:10%}#http-server-module-list p{margin-top:0}.toc ul,#index{list-style-type:none;margin:0;padding:0}#index code{background:transparent}#index h3{border-bottom:1px solid #ddd}#index ul{padding:0}#index h4{font-weight:bold}#index h4 + ul{margin-bottom:.6em}@media (min-width:200ex){#index .two-column{column-count:2}}@media (min-width:300ex){#index .two-column{column-count:3}}dl{margin-bottom:2em}dl dl:last-child{margin-bottom:4em}dd{margin:0 0 1em 3em}#header-classes + dl > dd{margin-bottom:3em}dd dd{margin-left:2em}dd p{margin:10px 0}.name{background:#eee;font-weight:bold;font-size:.85em;padding:5px 10px;display:inline-block;min-width:40%}.name:hover{background:#e0e0e0}.name > span:first-child{white-space:nowrap}.name.class > span:nth-child(2){margin-left:.4em}.inherited{color:#999;border-left:5px solid #eee;padding-left:1em}.inheritance em{font-style:normal;font-weight:bold}.desc h2{font-weight:400;font-size:1.25em}.desc h3{font-size:1em}.desc dt code{background:inherit}.source summary,.git-link-div{color:#666;text-align:right;font-weight:400;font-size:.8em;text-transform:uppercase}.source summary > *{white-space:nowrap;cursor:pointer}.git-link{color:inherit;margin-left:1em}.source pre{max-height:500px;overflow:auto;margin:0}.source pre code{font-size:12px;overflow:visible}.hlist{list-style:none}.hlist li{display:inline}.hlist li:after{content:',\2002'}.hlist li:last-child:after{content:none}.hlist .hlist{display:inline;padding-left:1em}img{max-width:100%}.admonition{padding:.1em .5em;margin-bottom:1em}.admonition-title{font-weight:bold}.admonition.note,.admonition.info,.admonition.important{background:#aef}.admonition.todo,.admonition.versionadded,.admonition.tip,.admonition.hint{background:#dfd}.admonition.warning,.admonition.versionchanged,.admonition.deprecated{background:#fd4}.admonition.error,.admonition.danger,.admonition.caution{background:lightpink}</style>
|
|
<style media="screen and (min-width: 700px)">@media screen and (min-width:700px){#sidebar{width:30%}#content{width:70%;max-width:100ch;padding:3em 4em;border-left:1px solid #ddd}pre code{font-size:1em}.item .name{font-size:1em}main{display:flex;flex-direction:row-reverse;justify-content:flex-end}.toc ul ul,#index ul{padding-left:1.5em}.toc > ul > li{margin-top:.5em}}</style>
|
|
<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
|
|
</head>
|
|
<body>
|
|
<main>
|
|
<article id="content">
|
|
<header>
|
|
<h1 class="title">Module <code>miplearn.solvers.tests</code></h1>
|
|
</header>
|
|
<section id="section-intro">
|
|
<details class="source">
|
|
<summary>
|
|
<span>Expand source code</span>
|
|
</summary>
|
|
<pre><code class="python"># MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
|
|
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
|
|
# Released under the modified BSD license. See COPYING.md for more details.
|
|
|
|
from inspect import isclass
|
|
from typing import List, Callable, Any
|
|
|
|
from pyomo import environ as pe
|
|
|
|
from miplearn.instance import Instance
|
|
from miplearn.problems.knapsack import KnapsackInstance, GurobiKnapsackInstance
|
|
from miplearn.solvers.gurobi import GurobiSolver
|
|
from miplearn.solvers.internal import InternalSolver
|
|
from miplearn.solvers.pyomo.base import BasePyomoSolver
|
|
from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
|
|
from miplearn.solvers.pyomo.xpress import XpressPyomoSolver
|
|
|
|
|
|
class InfeasiblePyomoInstance(Instance):
|
|
def to_model(self) -> pe.ConcreteModel:
|
|
model = pe.ConcreteModel()
|
|
model.x = pe.Var([0], domain=pe.Binary)
|
|
model.OBJ = pe.Objective(expr=model.x[0], sense=pe.maximize)
|
|
model.eq = pe.Constraint(expr=model.x[0] >= 2)
|
|
return model
|
|
|
|
|
|
class InfeasibleGurobiInstance(Instance):
|
|
def to_model(self) -> Any:
|
|
import gurobipy as gp
|
|
from gurobipy import GRB
|
|
|
|
model = gp.Model()
|
|
x = model.addVars(1, vtype=GRB.BINARY, name="x")
|
|
model.addConstr(x[0] >= 2)
|
|
model.setObjective(x[0])
|
|
return model
|
|
|
|
|
|
def _is_subclass_or_instance(obj, parent_class):
|
|
return isinstance(obj, parent_class) or (
|
|
isclass(obj) and issubclass(obj, parent_class)
|
|
)
|
|
|
|
|
|
def _get_knapsack_instance(solver):
|
|
if _is_subclass_or_instance(solver, BasePyomoSolver):
|
|
return KnapsackInstance(
|
|
weights=[23.0, 26.0, 20.0, 18.0],
|
|
prices=[505.0, 352.0, 458.0, 220.0],
|
|
capacity=67.0,
|
|
)
|
|
if _is_subclass_or_instance(solver, GurobiSolver):
|
|
return GurobiKnapsackInstance(
|
|
weights=[23.0, 26.0, 20.0, 18.0],
|
|
prices=[505.0, 352.0, 458.0, 220.0],
|
|
capacity=67.0,
|
|
)
|
|
assert False
|
|
|
|
|
|
def _get_infeasible_instance(solver):
|
|
if _is_subclass_or_instance(solver, BasePyomoSolver):
|
|
return InfeasiblePyomoInstance()
|
|
if _is_subclass_or_instance(solver, GurobiSolver):
|
|
return InfeasibleGurobiInstance()
|
|
|
|
|
|
def _get_internal_solvers() -> List[Callable[[], InternalSolver]]:
|
|
return [GurobiPyomoSolver, GurobiSolver, XpressPyomoSolver]</code></pre>
|
|
</details>
|
|
</section>
|
|
<section>
|
|
<h2 class="section-title" id="header-submodules">Sub-modules</h2>
|
|
<dl>
|
|
<dt><code class="name"><a title="miplearn.solvers.tests.test_internal_solver" href="test_internal_solver.html">miplearn.solvers.tests.test_internal_solver</a></code></dt>
|
|
<dd>
|
|
<section class="desc"></section>
|
|
</dd>
|
|
<dt><code class="name"><a title="miplearn.solvers.tests.test_lazy_cb" href="test_lazy_cb.html">miplearn.solvers.tests.test_lazy_cb</a></code></dt>
|
|
<dd>
|
|
<section class="desc"></section>
|
|
</dd>
|
|
<dt><code class="name"><a title="miplearn.solvers.tests.test_learning_solver" href="test_learning_solver.html">miplearn.solvers.tests.test_learning_solver</a></code></dt>
|
|
<dd>
|
|
<section class="desc"></section>
|
|
</dd>
|
|
</dl>
|
|
</section>
|
|
<section>
|
|
</section>
|
|
<section>
|
|
</section>
|
|
<section>
|
|
<h2 class="section-title" id="header-classes">Classes</h2>
|
|
<dl>
|
|
<dt id="miplearn.solvers.tests.InfeasibleGurobiInstance"><code class="flex name class">
|
|
<span>class <span class="ident">InfeasibleGurobiInstance</span></span>
|
|
</code></dt>
|
|
<dd>
|
|
<section class="desc"><p>Abstract class holding all the data necessary to generate a concrete model of the
|
|
problem.</p>
|
|
<p>In the knapsack problem, for example, this class could hold the number of items,
|
|
their weights and costs, as well as the size of the knapsack. Objects
|
|
implementing this class are able to convert themselves into a concrete
|
|
optimization model, which can be optimized by a solver, or into arrays of
|
|
features, which can be provided as inputs to machine learning models.</p></section>
|
|
<details class="source">
|
|
<summary>
|
|
<span>Expand source code</span>
|
|
</summary>
|
|
<pre><code class="python">class InfeasibleGurobiInstance(Instance):
|
|
def to_model(self) -> Any:
|
|
import gurobipy as gp
|
|
from gurobipy import GRB
|
|
|
|
model = gp.Model()
|
|
x = model.addVars(1, vtype=GRB.BINARY, name="x")
|
|
model.addConstr(x[0] >= 2)
|
|
model.setObjective(x[0])
|
|
return model</code></pre>
|
|
</details>
|
|
<h3>Ancestors</h3>
|
|
<ul class="hlist">
|
|
<li><a title="miplearn.instance.Instance" href="../../instance.html#miplearn.instance.Instance">Instance</a></li>
|
|
<li>abc.ABC</li>
|
|
</ul>
|
|
<h3>Inherited members</h3>
|
|
<ul class="hlist">
|
|
<li><code><b><a title="miplearn.instance.Instance" href="../../instance.html#miplearn.instance.Instance">Instance</a></b></code>:
|
|
<ul class="hlist">
|
|
<li><code><a title="miplearn.instance.Instance.build_lazy_constraint" href="../../instance.html#miplearn.instance.Instance.build_lazy_constraint">build_lazy_constraint</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.find_violated_lazy_constraints" href="../../instance.html#miplearn.instance.Instance.find_violated_lazy_constraints">find_violated_lazy_constraints</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.get_instance_features" href="../../instance.html#miplearn.instance.Instance.get_instance_features">get_instance_features</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.get_variable_category" href="../../instance.html#miplearn.instance.Instance.get_variable_category">get_variable_category</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.get_variable_features" href="../../instance.html#miplearn.instance.Instance.get_variable_features">get_variable_features</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.to_model" href="../../instance.html#miplearn.instance.Instance.to_model">to_model</a></code></li>
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
</dd>
|
|
<dt id="miplearn.solvers.tests.InfeasiblePyomoInstance"><code class="flex name class">
|
|
<span>class <span class="ident">InfeasiblePyomoInstance</span></span>
|
|
</code></dt>
|
|
<dd>
|
|
<section class="desc"><p>Abstract class holding all the data necessary to generate a concrete model of the
|
|
problem.</p>
|
|
<p>In the knapsack problem, for example, this class could hold the number of items,
|
|
their weights and costs, as well as the size of the knapsack. Objects
|
|
implementing this class are able to convert themselves into a concrete
|
|
optimization model, which can be optimized by a solver, or into arrays of
|
|
features, which can be provided as inputs to machine learning models.</p></section>
|
|
<details class="source">
|
|
<summary>
|
|
<span>Expand source code</span>
|
|
</summary>
|
|
<pre><code class="python">class InfeasiblePyomoInstance(Instance):
|
|
def to_model(self) -> pe.ConcreteModel:
|
|
model = pe.ConcreteModel()
|
|
model.x = pe.Var([0], domain=pe.Binary)
|
|
model.OBJ = pe.Objective(expr=model.x[0], sense=pe.maximize)
|
|
model.eq = pe.Constraint(expr=model.x[0] >= 2)
|
|
return model</code></pre>
|
|
</details>
|
|
<h3>Ancestors</h3>
|
|
<ul class="hlist">
|
|
<li><a title="miplearn.instance.Instance" href="../../instance.html#miplearn.instance.Instance">Instance</a></li>
|
|
<li>abc.ABC</li>
|
|
</ul>
|
|
<h3>Inherited members</h3>
|
|
<ul class="hlist">
|
|
<li><code><b><a title="miplearn.instance.Instance" href="../../instance.html#miplearn.instance.Instance">Instance</a></b></code>:
|
|
<ul class="hlist">
|
|
<li><code><a title="miplearn.instance.Instance.build_lazy_constraint" href="../../instance.html#miplearn.instance.Instance.build_lazy_constraint">build_lazy_constraint</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.find_violated_lazy_constraints" href="../../instance.html#miplearn.instance.Instance.find_violated_lazy_constraints">find_violated_lazy_constraints</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.get_instance_features" href="../../instance.html#miplearn.instance.Instance.get_instance_features">get_instance_features</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.get_variable_category" href="../../instance.html#miplearn.instance.Instance.get_variable_category">get_variable_category</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.get_variable_features" href="../../instance.html#miplearn.instance.Instance.get_variable_features">get_variable_features</a></code></li>
|
|
<li><code><a title="miplearn.instance.Instance.to_model" href="../../instance.html#miplearn.instance.Instance.to_model">to_model</a></code></li>
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
</dd>
|
|
</dl>
|
|
</section>
|
|
</article>
|
|
<nav id="sidebar">
|
|
<h1>Index</h1>
|
|
<div class="toc">
|
|
<ul></ul>
|
|
</div>
|
|
<ul id="index">
|
|
<li><h3>Super-module</h3>
|
|
<ul>
|
|
<li><code><a title="miplearn.solvers" href="../index.html">miplearn.solvers</a></code></li>
|
|
</ul>
|
|
</li>
|
|
<li><h3><a href="#header-submodules">Sub-modules</a></h3>
|
|
<ul>
|
|
<li><code><a title="miplearn.solvers.tests.test_internal_solver" href="test_internal_solver.html">miplearn.solvers.tests.test_internal_solver</a></code></li>
|
|
<li><code><a title="miplearn.solvers.tests.test_lazy_cb" href="test_lazy_cb.html">miplearn.solvers.tests.test_lazy_cb</a></code></li>
|
|
<li><code><a title="miplearn.solvers.tests.test_learning_solver" href="test_learning_solver.html">miplearn.solvers.tests.test_learning_solver</a></code></li>
|
|
</ul>
|
|
</li>
|
|
<li><h3><a href="#header-classes">Classes</a></h3>
|
|
<ul>
|
|
<li>
|
|
<h4><code><a title="miplearn.solvers.tests.InfeasibleGurobiInstance" href="#miplearn.solvers.tests.InfeasibleGurobiInstance">InfeasibleGurobiInstance</a></code></h4>
|
|
</li>
|
|
<li>
|
|
<h4><code><a title="miplearn.solvers.tests.InfeasiblePyomoInstance" href="#miplearn.solvers.tests.InfeasiblePyomoInstance">InfeasiblePyomoInstance</a></code></h4>
|
|
</li>
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
</nav>
|
|
</main>
|
|
<footer id="footer">
|
|
<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
|
|
</footer>
|
|
<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
|
|
<script>hljs.initHighlightingOnLoad()</script>
|
|
</body>
|
|
</html> |