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| <link rel="modulepreload" href="/docs/course/pr_1069/zh-TW/_app/immutable/chunks/getInferenceSnippets.24b50994.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"高級接口功能","local":"高級接口功能","sections":[{"title":"使用狀態保存數據","local":"使用狀態保存數據","sections":[],"depth":3},{"title":"通過解釋來理解預測","local":"通過解釋來理解預測","sections":[],"depth":3}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <h1 class="relative group"><a id="高級接口功能" 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="#高級接口功能"><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>高級接口功能</span></h1> <div class="flex space-x-1 absolute z-10 right-0 top-0"> <a href="https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/chapter9/section6.ipynb" target="_blank"><img alt="Open In Colab" class="!m-0" src="https://colab.research.google.com/assets/colab-badge.svg"></a> <a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/master/course/chapter9/section6.ipynb" target="_blank"><img alt="Open In Studio Lab" class="!m-0" src="https://studiolab.sagemaker.aws/studiolab.svg"></a></div> <p data-svelte-h="svelte-x51h71">現在我們可以構建和共享一個基本接口, 讓我們來探索一些更高級的特性, 如狀態和解釋。</p> <h3 class="relative group"><a id="使用狀態保存數據" 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="#使用狀態保存數據"><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>使用狀態保存數據</span></h3> <p data-svelte-h="svelte-1cc60o">Gradio 支持 <em>會話狀態</em>, 其中數據在頁面加載中的多個提交中持續存在。會話狀態對於構建演示很有用, 例如, 你希望在用戶與模型交互時保留數據的聊天機器人。請注意, 會話狀態不會在模型的不同用戶之間共享數據。</p> <p data-svelte-h="svelte-zuau5n">要將數據存儲在會話狀態中, 你需要做三件事:</p> <ol data-svelte-h="svelte-67hbs5"><li>向函數中傳遞一個 <em>額外的參數</em> , 該參數表示接口的狀態。</li> <li>在函數結束時, 將狀態的更新值作為 <em>額外的返回值</em> 返回。</li> <li>在創建<code>接口</code>時添加 ‘state’ 輸入和 ‘state’ 輸出組件。</li></ol> <p data-svelte-h="svelte-f104y5">請參閱下面的聊天機器人示例:</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-keyword">import</span> random | |
| <span class="hljs-keyword">import</span> gradio <span class="hljs-keyword">as</span> gr | |
| <span class="hljs-keyword">def</span> <span class="hljs-title function_">chat</span>(<span class="hljs-params">message, history</span>): | |
| history = history <span class="hljs-keyword">or</span> [] | |
| <span class="hljs-keyword">if</span> message.startswith(<span class="hljs-string">"How many"</span>): | |
| response = random.randint(<span class="hljs-number">1</span>, <span class="hljs-number">10</span>) | |
| <span class="hljs-keyword">elif</span> message.startswith(<span class="hljs-string">"How"</span>): | |
| response = random.choice([<span class="hljs-string">"Great"</span>, <span class="hljs-string">"Good"</span>, <span class="hljs-string">"Okay"</span>, <span class="hljs-string">"Bad"</span>]) | |
| <span class="hljs-keyword">elif</span> message.startswith(<span class="hljs-string">"Where"</span>): | |
| response = random.choice([<span class="hljs-string">"Here"</span>, <span class="hljs-string">"There"</span>, <span class="hljs-string">"Somewhere"</span>]) | |
| <span class="hljs-keyword">else</span>: | |
| response = <span class="hljs-string">"I don't know"</span> | |
| history.append((message, response)) | |
| <span class="hljs-keyword">return</span> history, history | |
| iface = gr.Interface( | |
| chat, | |
| [<span class="hljs-string">"text"</span>, <span class="hljs-string">"state"</span>], | |
| [<span class="hljs-string">"chatbot"</span>, <span class="hljs-string">"state"</span>], | |
| allow_screenshot=<span class="hljs-literal">False</span>, | |
| allow_flagging=<span class="hljs-string">"never"</span>, | |
| ) | |
| iface.launch()<!-- HTML_TAG_END --></pre></div> <iframe src="https://course-demos-Chatbot-Demo.hf.space" frameborder="0" height="350" title="Gradio app" class="container p-0 flex-grow space-iframe" allow="accelerometer; ambient-light-sensor; autoplay; battery; camera; document-domain; encrypted-media; fullscreen; geolocation; gyroscope; layout-animations; legacy-image-formats; magnetometer; microphone; midi; oversized-images; payment; picture-in-picture; publickey-credentials-get; sync-xhr; usb; vr ; wake-lock; xr-spatial-tracking" sandbox="allow-forms allow-modals allow-popups allow-popups-to-escape-sandbox allow-same-origin allow-scripts allow-downloads"></iframe> <p data-svelte-h="svelte-1qf57y9">請注意輸出組件的狀態如何在提交之間保持不變。注意: 可以給 state 參數傳入一個默認值, 作為 state 的初始值。</p> <h3 class="relative group"><a id="通過解釋來理解預測" 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="#通過解釋來理解預測"><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>通過解釋來理解預測</span></h3> <p data-svelte-h="svelte-1psqlkg">大多數機器學習模型都是黑盒子, 函數的內部邏輯對終端用戶是隱藏的。為了提高透明度, 我們通過簡單地將 Interface 類中的解釋關鍵字設置為默認值, 使向模型添加解釋變得非常容易。這允許你的用戶理解輸入的哪些部分負責輸出。看看下面這個簡單的接口, 它顯示了一個還包括解釋的圖像分類器:</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-keyword">import</span> requests | |
| <span class="hljs-keyword">import</span> tensorflow <span class="hljs-keyword">as</span> tf | |
| <span class="hljs-keyword">import</span> gradio <span class="hljs-keyword">as</span> gr | |
| inception_net = tf.keras.applications.MobileNetV2() <span class="hljs-comment"># load the model</span> | |
| <span class="hljs-comment"># Download human-readable labels for ImageNet.</span> | |
| response = requests.get(<span class="hljs-string">"https://git.io/JJkYN"</span>) | |
| labels = response.text.split(<span class="hljs-string">"\n"</span>) | |
| <span class="hljs-keyword">def</span> <span class="hljs-title function_">classify_image</span>(<span class="hljs-params">inp</span>): | |
| inp = inp.reshape((-<span class="hljs-number">1</span>, <span class="hljs-number">224</span>, <span class="hljs-number">224</span>, <span class="hljs-number">3</span>)) | |
| inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp) | |
| prediction = inception_net.predict(inp).flatten() | |
| <span class="hljs-keyword">return</span> {labels[i]: <span class="hljs-built_in">float</span>(prediction[i]) <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">1000</span>)} | |
| image = gr.Image(shape=(<span class="hljs-number">224</span>, <span class="hljs-number">224</span>)) | |
| label = gr.Label(num_top_classes=<span class="hljs-number">3</span>) | |
| title = <span class="hljs-string">"Gradio Image Classifiction + Interpretation Example"</span> | |
| gr.Interface( | |
| fn=classify_image, inputs=image, outputs=label, interpretation=<span class="hljs-string">"default"</span>, title=title | |
| ).launch()<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-3q3puo">通過提交一個輸入, 然後單擊輸出組件下的Interpret來測試解釋功能。</p> <iframe src="https://course-demos-gradio-image-interpretation.hf.space" frameborder="0" height="570" title="Gradio app" class="container p-0 flex-grow space-iframe" allow="accelerometer; ambient-light-sensor; autoplay; battery; camera; document-domain; encrypted-media; fullscreen; geolocation; gyroscope; layout-animations; legacy-image-formats; magnetometer; microphone; midi; oversized-images; payment; picture-in-picture; publickey-credentials-get; sync-xhr; usb; vr ; wake-lock; xr-spatial-tracking" sandbox="allow-forms allow-modals allow-popups allow-popups-to-escape-sandbox allow-same-origin allow-scripts allow-downloads"></iframe> <p data-svelte-h="svelte-9mllfu">除了Gradio提供的默認解釋方法之外, 你還可以為 <code>interpretation</code> 參數指定 <code>shap</code>, 並設置 <code>num_shap</code> 參數。這使用基於 Shapley 的解釋, 你可以在 <a href="https://christophm.github.io/interpretable-ml-book/shap.html" rel="nofollow">here</a> 閱讀更多信息。最後, 還可以將自己的解釋函數傳入 <code>interpretation</code> 參數。在Gradio的入門頁面 <a href="https://gradio.app/getting_started/" rel="nofollow">here</a> 中可以看到一個例子。</p> <p data-svelte-h="svelte-16becp1">這結束了我們對Gradio的<code>Interface</code>類的深入研究。正如我們所看到的, 這個類使用幾行Python代碼創建機器學習演示變得簡單。然而, 有時你會想通過改變佈局或鏈接多個預測函數來定製你的demo。如果我們能以某種方式將 <code>接口</code> 分成可定製的 “塊”, 那不是很好嗎? 幸運的是, 有! 這是最後一部分的主題。</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/course/blob/main/chapters/zh-TW/chapter9/6.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1"><</span> <span data-svelte-h="svelte-x0xyl0">></span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a> <p></p> | |
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