- 理解 Machine Learning，特別是深度學習
- 熟悉機器學習庫（TensorFlow、Keras、PyTorch、Apache MXNet）
- Python 程式設計經驗
觀眾
- 開發人員
- 數據科學家
Horovod 是一個開源軟體框架，旨在使用 TensorFlow、Keras、PyTorch 和 Apache MXNet 處理快速高效的分散式深度學習模型。它可以擴展單個 GPU 訓練腳本，以便在多個 GPU 或主機上運行，只需進行最少的代碼更改。
這種由講師指導的即時培訓（在線或現場）面向希望使用 Horovod 運行分散式深度學習訓練並將其擴展為在多個 GPU 之間並行運行的開發人員或數據科學家。
在本次培訓結束時，參與者將能夠：
- 設置必要的開發環境以開始運行深度學習訓練。
- 安裝並配置 Horovod 以使用 TensorFlow、Keras、PyTorch 和 Apache MXNet 訓練模型。
- 使用 Horovod 擴展深度學習訓練以在多個 GPU 上運行。
課程形式
- 互動講座和討論。
- 大量的練習和練習。
- 在即時實驗室環境中動手實施。
課程自定義選項
- 本課程側重於 Horovod，但可能需要其他軟體工具和框架，如 TensorFlow、Keras、PyTorch 和 Apache MXNet。如果您有具體要求或偏好，請告訴我們。
- 要申請本課程的定製培訓，請聯繫我們進行安排。
介紹
- Horovod 功能和概念概述
- 了解支援的框架
安裝和設定 Horovod
- 準備託管環境
- 為 TensorFlow、Keras、PyTorch 和 Apache MXNet 構建 Horovod
- 正在執行 Horovod
運行分散式訓練
- 使用 TensorFlow 修改和運行訓練範例
- 使用 Keras 修改和運行訓練範例
- 使用 Py 修改和運行訓練範例Torch
- 使用 Apache MXNet 修改和運行訓練範例
優化分散式訓練過程
- 在多個GPU 上運行併發操作
- 優化超參數
- 啟用性能自動調整
故障排除
總結和結論
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