about customizing your PyTorch image. For more information about PyTorch, including tutorials, documentation, and examples, see: ‣ PyTorch website ‣ PyTorch project This document provides information Guide. ‣ For non-DGX users, see NVIDIA ® GPU Cloud ™ (NGC) container registry installation documentation based on your platform. ‣ Ensure that you have access and can log in to the NGC container registry NVIDIA_VISIBLE_DEVICES environment variable). For more information, refer to the nvidia-docker documentation. Note: Starting in Docker 19.03, complete the steps below. The method implemented in your system

安装完成后我们可以通过运行以下命令打开Jupyter笔记本（在Window系统的命令行窗口中运行以下命令前， 需先将当前路径定位到刚下载的本书代码解压后的目录）： jupyter notebook 9 https://developer.nvidia.com/cuda‐downloads 10 目录 现在可以在Web浏览器中打开http://localhost:8888（通常会自动打开）。由此，我们可以运行这本书中每个 16160MiB | 55% Default | (continues on next page) 79 https://discuss.d2l.ai/t/1839 80 https://developer.nvidia.com/cuda‐downloads 5.6. GPU 211 (continued from previous page) | | | N/A | +-------- 这一点。 3. 设计一个实验，在CPU和GPU这两种设备上使用并行计算和通信。 4. 使用诸如NVIDIA的Nsight145之类的调试器来验证代码是否有效。 145 https://developer.nvidia.com/nsight‐compute‐2019_5 12.3. 自动并行 515 5. 设计并实验具有更加复杂的数据依赖关系的计算任务，以查看是否可以在提高性能的同时获得正确的

tensorflow.org/lite/examples TensorFlow Lite Examples 搭建 TensorFlow Lite 运行环境 (Android) https://developer.android.com/studio Step 1：下载 TensorFlow examples 项目 $ git clone https://github.com/tensorflow/examples

flower from its picture. We have access to a flowers dataset (oxford_flowers102). As an application developer, with no experience with ML, we would like a model trained on the flowers dataset to integrate into

torch.float torch.FloatTensor 64-bit integer (signed) torch.long torch.LongTensor see official documentation for more information on data types. ● Using different data types for model and data will cause shape x.dtype x.dtype ref: https://github.com/wkentaro/pytorch-for-numpy-users see official documentation for more information on data types. Tensors – PyTorch v.s. NumPy ● Many functions have the same gradients of prediction loss. 3. Call optimizer.step() to adjust model parameters. See official documentation for more optimization algorithms. Training & Testing Neural Networks – in Pytorch Define Neural

__version__)' python -c 'import torch; print(torch.cuda.is_available())' Useful Links Miniconda Documentation PyTorch: Getting Started Install TensorFlow

https://oncomputingwell.princeton.edu/2018/05/jupyter-on-the-cluster/ • Best reference is PyTorch Documentation • https://pytorch.org/ and https://github.com/pytorch/pytorch • Good Blogs: (with examples and

显卡，例如部分计算机显卡生 产商为 AMD 或 Intel，则无法安装 CUDA 程序，因此可以跳过这一步，直接进入 PyTorch CPU 版本的安装。 首先打开 CUDA 程序的下载官网：https://developer.nvidia.com/cuda-10.1-download- archive，这里选择使用 CUDA 10.1 版本(读者可根据需求自行选择最新版)，依次选择 Windows 平台，x86_64