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| <link rel="modulepreload" href="/docs/datasets/pr_8113/en/_app/immutable/chunks/CodeBlock.77fa95e2.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"Use with NumPy","local":"use-with-numpy","sections":[{"title":"Dataset format","local":"dataset-format","sections":[{"title":"N-dimensional arrays","local":"n-dimensional-arrays","sections":[],"depth":3},{"title":"Other feature types","local":"other-feature-types","sections":[],"depth":3}],"depth":2},{"title":"Data loading","local":"data-loading","sections":[{"title":"Using with_format('numpy')","local":"using-withformatnumpy","sections":[],"depth":3}],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <div class="items-center shrink-0 min-w-[100px] max-sm:min-w-[50px] justify-end ml-auto flex" style="float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"><div class="inline-flex rounded-md max-sm:rounded-sm"><button class="inline-flex items-center gap-1 h-7 max-sm:h-7 px-2 max-sm:px-1.5 text-sm font-medium text-gray-800 border border-r-0 rounded-l-md max-sm:rounded-l-sm border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-live="polite"><span class="inline-flex items-center justify-center rounded-md p-0.5 max-sm:p-0 hover:text-gray-800 dark:hover:text-gray-200"><svg class="sm:size-3.5 size-3" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg></span> <span>Copy page</span></button> <button class="inline-flex items-center justify-center w-6 max-sm:w-5 h-7 max-sm:h-7 disabled:pointer-events-none text-sm text-gray-500 hover:text-gray-700 dark:hover:text-white rounded-r-md max-sm:rounded-r-sm border border-l transition border-gray-200 bg-white hover:shadow-inner dark:border-gray-850 dark:bg-gray-950 dark:text-gray-200 dark:hover:bg-gray-800" aria-haspopup="menu" aria-expanded="false" aria-label="Open copy menu"><svg class="transition-transform text-gray-400 overflow-visible sm:size-3.5 size-3 rotate-0" width="1em" height="1em" viewBox="0 0 12 7" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M1 1L6 6L11 1" stroke="currentColor"></path></svg></button></div> </div> <h1 class="relative group"><a id="use-with-numpy" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#use-with-numpy"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Use with NumPy</span></h1> <p data-svelte-h="svelte-movp6t">This document is a quick introduction to using <code>datasets</code> with NumPy, with a particular focus on how to get | |
| <code>numpy.ndarray</code> objects out of our datasets, and how to use them to train models based on NumPy such as <code>scikit-learn</code> models.</p> <h2 class="relative group"><a id="dataset-format" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#dataset-format"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Dataset format</span></h2> <p data-svelte-h="svelte-jsr2ey">By default, datasets return regular Python objects: integers, floats, strings, lists, etc..</p> <p data-svelte-h="svelte-tgh4v8">To get NumPy arrays instead, you can set the format of the dataset to <code>numpy</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset | |
| <span class="hljs-meta">>>> </span>data = [[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]] | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"data"</span>: data}) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] | |
| {<span class="hljs-string">'data'</span>: array([<span class="hljs-number">1</span>, <span class="hljs-number">2</span>])} | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">2</span>] | |
| {<span class="hljs-string">'data'</span>: array([ | |
| [<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], | |
| [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]])}<!-- HTML_TAG_END --></pre></div> <blockquote class="tip" data-svelte-h="svelte-rvocsc"><p>A <a href="/docs/datasets/pr_8113/en/package_reference/main_classes#datasets.Dataset">Dataset</a> object is a wrapper of an Arrow table, which allows fast reads from arrays in the dataset to NumPy arrays.</p></blockquote> <p data-svelte-h="svelte-19vwxv0">Note that the exact same procedure applies to <code>DatasetDict</code> objects, so that | |
| when setting the format of a <code>DatasetDict</code> to <code>numpy</code>, all the <code>Dataset</code>s there | |
| will be formatted as <code>numpy</code>:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> DatasetDict | |
| <span class="hljs-meta">>>> </span>data = {<span class="hljs-string">"train"</span>: {<span class="hljs-string">"data"</span>: [[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]]}, <span class="hljs-string">"test"</span>: {<span class="hljs-string">"data"</span>: [[<span class="hljs-number">5</span>, <span class="hljs-number">6</span>], [<span class="hljs-number">7</span>, <span class="hljs-number">8</span>]]}} | |
| <span class="hljs-meta">>>> </span>dds = DatasetDict.from_dict(data) | |
| <span class="hljs-meta">>>> </span>dds = dds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>dds[<span class="hljs-string">"train"</span>][:<span class="hljs-number">2</span>] | |
| {<span class="hljs-string">'data'</span>: array([ | |
| [<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], | |
| [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]])}<!-- HTML_TAG_END --></pre></div> <h3 class="relative group"><a id="n-dimensional-arrays" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#n-dimensional-arrays"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>N-dimensional arrays</span></h3> <p data-svelte-h="svelte-n2lxj9">If your dataset consists of N-dimensional arrays, you will see that by default they are considered as the same array if the shape is fixed:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset | |
| <span class="hljs-meta">>>> </span>data = [[[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>],[<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]], [[<span class="hljs-number">5</span>, <span class="hljs-number">6</span>],[<span class="hljs-number">7</span>, <span class="hljs-number">8</span>]]] <span class="hljs-comment"># fixed shape</span> | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"data"</span>: data}) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] | |
| {<span class="hljs-string">'data'</span>: array([[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], | |
| [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]])}<!-- HTML_TAG_END --></pre></div> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset | |
| <span class="hljs-meta">>>> </span>data = [[[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>],[<span class="hljs-number">3</span>]], [[<span class="hljs-number">4</span>, <span class="hljs-number">5</span>, <span class="hljs-number">6</span>],[<span class="hljs-number">7</span>, <span class="hljs-number">8</span>]]] <span class="hljs-comment"># varying shape</span> | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"data"</span>: data}) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] | |
| {<span class="hljs-string">'data'</span>: array([array([<span class="hljs-number">1</span>, <span class="hljs-number">2</span>]), array([<span class="hljs-number">3</span>])], dtype=<span class="hljs-built_in">object</span>)}<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1gw41y9">However this logic often requires slow shape comparisons and data copies. | |
| To avoid this, you must explicitly use the <code>Array</code> feature type and specify the shape of your tensors:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset, Features, Array2D | |
| <span class="hljs-meta">>>> </span>data = [[[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>],[<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]],[[<span class="hljs-number">5</span>, <span class="hljs-number">6</span>],[<span class="hljs-number">7</span>, <span class="hljs-number">8</span>]]] | |
| <span class="hljs-meta">>>> </span>features = Features({<span class="hljs-string">"data"</span>: Array2D(shape=(<span class="hljs-number">2</span>, <span class="hljs-number">2</span>), dtype=<span class="hljs-string">'int32'</span>)}) | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"data"</span>: data}, features=features) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] | |
| {<span class="hljs-string">'data'</span>: array([[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], | |
| [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]])} | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">2</span>] | |
| {<span class="hljs-string">'data'</span>: array([[[<span class="hljs-number">1</span>, <span class="hljs-number">2</span>], | |
| [<span class="hljs-number">3</span>, <span class="hljs-number">4</span>]], | |
| [[<span class="hljs-number">5</span>, <span class="hljs-number">6</span>], | |
| [<span class="hljs-number">7</span>, <span class="hljs-number">8</span>]]])}<!-- HTML_TAG_END --></pre></div> <h3 class="relative group"><a id="other-feature-types" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#other-feature-types"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Other feature types</span></h3> <p data-svelte-h="svelte-i603sw"><a href="/docs/datasets/pr_8113/en/package_reference/main_classes#datasets.ClassLabel">ClassLabel</a> data is properly converted to arrays:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset, Features, ClassLabel | |
| <span class="hljs-meta">>>> </span>labels = [<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">1</span>] | |
| <span class="hljs-meta">>>> </span>features = Features({<span class="hljs-string">"label"</span>: ClassLabel(names=[<span class="hljs-string">"negative"</span>, <span class="hljs-string">"positive"</span>])}) | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"label"</span>: labels}, features=features) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">3</span>] | |
| {<span class="hljs-string">'label'</span>: array([<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">1</span>])}<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1i7nqnr">String and binary objects are unchanged, since NumPy only supports numbers.</p> <p data-svelte-h="svelte-1r1cbno">The <a href="/docs/datasets/pr_8113/en/package_reference/main_classes#datasets.Image">Image</a> and <a href="/docs/datasets/pr_8113/en/package_reference/main_classes#datasets.Audio">Audio</a> feature types are also supported.</p> <blockquote class="tip" data-svelte-h="svelte-bebjte"><p>To use the <a href="/docs/datasets/pr_8113/en/package_reference/main_classes#datasets.Image">Image</a> feature type, you’ll need to install the <code>vision</code> extra as | |
| <code>pip install datasets[vision]</code>.</p></blockquote> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset, Features, Image | |
| <span class="hljs-meta">>>> </span>images = [<span class="hljs-string">"path/to/image.png"</span>] * <span class="hljs-number">10</span> | |
| <span class="hljs-meta">>>> </span>features = Features({<span class="hljs-string">"image"</span>: Image()}) | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"image"</span>: images}, features=features) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>][<span class="hljs-string">"image"</span>].shape | |
| (<span class="hljs-number">512</span>, <span class="hljs-number">512</span>, <span class="hljs-number">3</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>] | |
| {<span class="hljs-string">'image'</span>: array([[[ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>], | |
| [ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>], | |
| ..., | |
| [ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>], | |
| [ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>]]], dtype=uint8)} | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">2</span>][<span class="hljs-string">"image"</span>].shape | |
| (<span class="hljs-number">2</span>, <span class="hljs-number">512</span>, <span class="hljs-number">512</span>, <span class="hljs-number">3</span>) | |
| <span class="hljs-meta">>>> </span>ds[:<span class="hljs-number">2</span>] | |
| {<span class="hljs-string">'image'</span>: array([[[[ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>], | |
| [ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>], | |
| ..., | |
| [ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>], | |
| [ <span class="hljs-number">255</span>, <span class="hljs-number">255</span>, <span class="hljs-number">255</span>]]]], dtype=uint8)}<!-- HTML_TAG_END --></pre></div> <blockquote class="tip" data-svelte-h="svelte-1tooptg"><p>To use the <a href="/docs/datasets/pr_8113/en/package_reference/main_classes#datasets.Audio">Audio</a> feature type, you’ll need to install the <code>audio</code> extra as | |
| <code>pip install datasets[audio]</code>.</p></blockquote> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset, Features, Audio | |
| <span class="hljs-meta">>>> </span>audio = [<span class="hljs-string">"path/to/audio.wav"</span>] * <span class="hljs-number">10</span> | |
| <span class="hljs-meta">>>> </span>features = Features({<span class="hljs-string">"audio"</span>: Audio()}) | |
| <span class="hljs-meta">>>> </span>ds = Dataset.from_dict({<span class="hljs-string">"audio"</span>: audio}, features=features) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>][<span class="hljs-string">"audio"</span>][<span class="hljs-string">"array"</span>] | |
| array([-<span class="hljs-number">0.059021</span> , -<span class="hljs-number">0.03894043</span>, -<span class="hljs-number">0.00735474</span>, ..., <span class="hljs-number">0.0133667</span> , | |
| <span class="hljs-number">0.01809692</span>, <span class="hljs-number">0.00268555</span>], dtype=float32) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-number">0</span>][<span class="hljs-string">"audio"</span>][<span class="hljs-string">"sampling_rate"</span>] | |
| array(<span class="hljs-number">44100</span>, weak_type=<span class="hljs-literal">True</span>)<!-- HTML_TAG_END --></pre></div> <h2 class="relative group"><a id="data-loading" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#data-loading"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Data loading</span></h2> <p data-svelte-h="svelte-14evha6">NumPy doesn’t have any built-in data loading capabilities, so you’ll either need to materialize the NumPy arrays like <code>X, y</code> to use in <code>scikit-learn</code> or use a library such as <a href="https://pytorch.org/" rel="nofollow">PyTorch</a> to load your data using a <code>DataLoader</code>.</p> <h3 class="relative group"><a id="using-withformatnumpy" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#using-withformatnumpy"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Using with_format('numpy')</span></h3> <p data-svelte-h="svelte-kj9r2i">The easiest way to get NumPy arrays out of a dataset is to use the <code>with_format('numpy')</code> method. Lets assume | |
| that we want to train a neural network on the <a href="http://yann.lecun.com/exdb/mnist/" rel="nofollow">MNIST dataset</a> available | |
| at the HuggingFace Hub at <a href="https://huggingface.co/datasets/mnist" rel="nofollow">https://huggingface.co/datasets/mnist</a>.</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset | |
| <span class="hljs-meta">>>> </span>ds = load_dataset(<span class="hljs-string">"ylecun/mnist"</span>) | |
| <span class="hljs-meta">>>> </span>ds = ds.with_format(<span class="hljs-string">"numpy"</span>) | |
| <span class="hljs-meta">>>> </span>ds[<span class="hljs-string">"train"</span>][<span class="hljs-number">0</span>] | |
| {<span class="hljs-string">'image'</span>: array([[ <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, ...], | |
| [ <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, ...], | |
| ..., | |
| [ <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, ...], | |
| [ <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, ...]], dtype=uint8), | |
| <span class="hljs-string">'label'</span>: array(<span class="hljs-number">5</span>)}<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-117alrv">Once the format is set we can feed the dataset to the model based on NumPy in batches using the <code>Dataset.iter()</code> | |
| method:</p> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-meta">>>> </span><span class="hljs-keyword">for</span> epoch <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(epochs): | |
| <span class="hljs-meta">... </span> <span class="hljs-keyword">for</span> batch <span class="hljs-keyword">in</span> ds[<span class="hljs-string">"train"</span>].<span class="hljs-built_in">iter</span>(batch_size=<span class="hljs-number">32</span>): | |
| <span class="hljs-meta">... </span> x, y = batch[<span class="hljs-string">"image"</span>], batch[<span class="hljs-string">"label"</span>] | |
| <span class="hljs-meta">... </span> ...<!-- HTML_TAG_END --></pre></div> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/datasets/blob/main/docs/source/use_with_numpy.mdx" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg> <span data-svelte-h="svelte-zjs2n5"><span class="underline">Update</span> on GitHub</span></a> <p></p> | |
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