TensorFlow 2.4 Mac 優化版：性能大幅提升，可在最新的M1芯片上運行

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"通過 TensorFlow 2 在各種不同的平臺、設備和硬件上提供一流的訓練性能，使開發人員、工程師和研究人員能夠在他們喜歡的平臺上工作。TensorFlow 用戶現在可以在搭載 Intel CPU 的 Mac 或搭載 Apple 新芯片 M1 的 Mac 上使用 "},{"type":"link","attrs":{"href":"https:\/\/github.com\/apple\/tensorflow_macos","title":"","type":null},"content":[{"type":"text","text":"TensorFlow 2.4 Mac 優化版"}]},{"type":"text","text":" 和新的 ML Compute（機器學習計算）框架進行加速訓練。這些改進，加上 Apple 開發人員可以通過 "},{"type":"link","attrs":{"href":"https:\/\/www.tensorflow.org\/lite","title":"","type":null},"content":[{"type":"text","text":"TensorFlow Lite"}]},{"type":"text","text":" 在 iOS 上執行 TensorFlow，繼續展示了 TensorFlow 在 Apple 硬件上支持高性能機器學習執行的廣度和深度。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"使用 ML Compute 在 Mac 上的性能"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Mac 一直是開發人員、工程師和研究人員所喜愛的平臺。隨着 Apple 上週"},{"type":"link","attrs":{"href":"https:\/\/www.apple.com\/apple-events\/november-2020\/?useASL=true","title":"","type":null},"content":[{"type":"text","text":"宣佈"}]},{"type":"text","text":" 推出一系列採用新芯片 "},{"type":"link","attrs":{"href":"https:\/\/www.apple.com\/mac\/m1\/","title":"","type":null},"content":[{"type":"text","text":"M1"}]},{"type":"text","text":" 的 Mac 計算機，TensorFlow 2.4 Mac 優化版充分利用了 Mac 的全部能力，在性能上有了巨大的飛躍。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"ML Compute 是 Apple 推出的新框架，它支持在 Mac 上進行 TensorFlow 模型的訓練，現在你可以在搭載 M1 或 Intel CPU的 Mac 計算機上利用加速的 CPU 和 GPU 進行訓練。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"例如，M1 芯片包含了一個強大的新 8 核 CPU 和多達 8 核的 GPU，這些都是針對 Mac 計算機上的機器學習訓練任務而優化的。在下面的圖表中，你可以看到 TensorFlow 2.4 Mac 優化版在流行的搭載 M1 和 Intel CPU 的 Mac 上如何實現巨大的性能提升的。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":" "}]},{"type":"image","attrs":{"src":"https:\/\/static001.infoq.cn\/resource\/image\/02\/47\/022ae1800b9ca1bbcda0706af7168747.jpg","alt":null,"title":"","style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":"","fromPaste":false,"pastePass":false}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在搭載 M1 和 Intel CPU 的 13 英寸 MacBook Pro 上，使用 ML Compute 的常見機型的訓練效果以秒爲單位顯示，數字越小表明訓練時間越短。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"image","attrs":{"src":"https:\/\/static001.infoq.cn\/resource\/image\/87\/f9\/87020a0b62af0d12a2d520a7368c35f9.jpg","alt":null,"title":"","style":[{"key":"width","value":"75%"},{"key":"bordertype","value":"none"}],"href":"","fromPaste":false,"pastePass":false}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在搭載 Intel CPU 的 MacPro 2019 款上使用 ML Compute 對常見機型的訓練效果以秒爲單位顯示，數字越小表明訓練時間越短。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"TensorFlow Apple Mac 優化版入門"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"用戶無需對現有的 TensorFlow 腳本進行任何更改，就可以使用 ML Compute 作爲 TensorFlow 和 TensorFlow 插件的後端。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"首先，請訪問 Apple 的 "},{"type":"link","attrs":{"href":"https:\/\/github.com\/apple\/tensorflow_macos","title":"","type":null},"content":[{"type":"text","text":"GitHub 倉庫"}]},{"type":"text","text":"，瞭解如何下載並安裝 TensorFlow 2.4 Apple Mac 優化版分叉（fork）的說明。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在不久的將來，Apple 將通過分叉版本集成到 "},{"type":"link","attrs":{"href":"https:\/\/github.com\/tensorflow\/tensorflow#community-supported-builds","title":"","type":null},"content":[{"type":"text","text":"TensorFlow 主分支"}]},{"type":"text","text":" 中，使這樣的更新更容易讓用戶獲得這些性能數據。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"你可以在 "},{"type":"link","attrs":{"href":"https:\/\/machinelearning.apple.com\/updates\/ml-compute-training-on-mac","title":"","type":null},"content":[{"type":"text","text":"Apple 的機器學習網站"}]},{"type":"text","text":"上了解更多關於 ML Compute 框架的信息。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"原文鏈接："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"https:\/\/blog.tensorflow.org\/2020\/11\/accelerating-tensorflow-performance-on-mac.html"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":" "}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}