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<title>Datasets Module — easyjailbreak 0.1.0 documentation</title>
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<li class="toctree-l1 current"><a class="current reference internal" href="#">Datasets Module</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="#instance-class">Instance class</a></li>
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<section id="datasets-module">
<h1>Datasets Module<a class="headerlink" href="#datasets-module" title="Permalink to this heading"></a></h1>
<p>Before users start jailbreak processes, users need to prepare and load harmful queries that models should not respond to. EasyJailbreak contains an Instance class to store these queries and other information that may be useful for the jailbreak processes, e.g. the responses from the target model. Meanwhile EasyJailbreak uses a JailbreakDataset class to gather these instances up and support batch operations.</p>
<section id="instance">
<h2>instance<a class="headerlink" href="#instance" title="Permalink to this heading"></a></h2>
<section id="instance-class">
<h3>Instance class<a class="headerlink" href="#instance-class" title="Permalink to this heading"></a></h3>
</section>
</section>
<section id="jailbreak-datasets">
<h2>jailbreak_datasets<a class="headerlink" href="#jailbreak-datasets" title="Permalink to this heading"></a></h2>
<section id="jailbreak-dataset-module">
<h3>Jailbreak_Dataset Module<a class="headerlink" href="#jailbreak-dataset-module" title="Permalink to this heading"></a></h3>
<p>This module provides the JailbreakDataset class, which is designed to manage and manipulate datasets for the Easy Jailbreak application. It is capable of handling datasets structured with PromptNode instances, offering functionalities such as shuffling, accessing, and processing data points in an organized way for machine learning tasks related to Easy Jailbreak.</p>
</section>
<dl class="py class">
<dt class="sig sig-object py">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">easyjailbreak.datasets.jailbreak_datasets.</span></span><span class="sig-name descname"><span class="pre">JailbreakDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">Instance</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">local_file_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'json'</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>JailbreakDataset class is designed for handling datasets specifically structured for the Easy Jailbreak application.
It allows for the representation, manipulation, and access of data points in the form of Instance instances.
This class provides essential functionalities such as shuffling, accessing, and formatting data for use in machine learning models.</p>
<dl class="py method">
<dt class="sig sig-object py">
<span class="sig-name descname"><span class="pre">add</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">Instance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Instance</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Adds a new Instance to the dataset.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>instance</strong> (<em>Instance</em>) – The Instance to be added to the dataset.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<span class="sig-name descname"><span class="pre">group_by</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Groups instances in the dataset based on a specified key function.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>key</strong> (<em>function</em>) – A function that takes an Instance and returns a hashable object for grouping.</p>
</dd>
<dt class="field-even">Return list[list[Instance]]<span class="colon">:</span></dt>
<dd class="field-even"><p>A list of lists, where each sublist contains Instances grouped by the specified key.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<span class="sig-name descname"><span class="pre">group_by_parents</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span></dt>
<dd><p>Groups instances in the dataset based on their parent nodes.</p>
<dl class="field-list simple">
<dt class="field-odd">Return list[list[Instance]]<span class="colon">:</span></dt>
<dd class="field-odd"><p>A list of lists, where each sublist contains Instances grouped by their parent nodes.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load_csv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'data.csv'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">headers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Loads a CSV file into the dataset.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>path</strong> (<em>str</em>) – The path of the CSV file to be loaded.</p></li>
<li><p><strong>headers</strong> (<em>list</em><em>[</em><em>str</em><em>]</em>) – A list of column names to be used as headers. Defaults to None.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load_jsonl</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'data.jsonl'</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Loads a JSONL file into the dataset.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>path</strong> (<em>str</em>) – The path of the JSONL file to be loaded.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">merge</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_list</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Merges multiple JailbreakDataset instances into a single dataset.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>dataset_list</strong> (<em>list</em><em>[</em><em>JailbreakDataset</em><em>]</em>) – A list of JailbreakDataset instances to be merged.</p>
</dd>
<dt class="field-even">Return JailbreakDataset<span class="colon">:</span></dt>
<dd class="field-even"><p>A new JailbreakDataset instance containing merged data from the provided datasets.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<span class="sig-name descname"><span class="pre">save_to_csv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'data.csv'</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Saves the dataset to a CSV file.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>path</strong> (<em>str</em>) – The path of the file where the dataset will be saved. Defaults to ‘data.csv’.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<span class="sig-name descname"><span class="pre">save_to_jsonl</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'data.jsonl'</span></span></em><span class="sig-paren">)</span></dt>
<dd><p>Saves the dataset to a JSONL file using jsonlines library.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>path</strong> (<em>str</em>) – The path of the file where the dataset will be saved. Defaults to ‘data.jsonl’.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py">
<span class="sig-name descname"><span class="pre">shuffle</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span></dt>
<dd><p>Shuffles the dataset in place.</p>
<p>This method randomizes the order of the dataset’s elements and updates the <cite>shuffled</cite> attribute to True.</p>
</dd></dl>
</dd></dl>
</section>
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