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Merge pull request #2338 from d2l-ai/r0.17
Release 0.17.6
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chapter_installation/index.md

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@@ -21,10 +21,10 @@ For example, if you are using macOS and Python 3.x
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you would download the bash script
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whose name contains the strings "Miniconda3" and "MacOSX",
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navigate to the download location,
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and execute the installation as follows:
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and execute the installation as follows (taking Intel Macs as an example):
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```bash
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sh Miniconda3-latest-MacOSX-x86_64.sh -b
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sh Miniconda3-py39_4.12.0-MacOSX-x86_64.sh -b
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```
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a new environment as follows:
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```bash
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conda create --name d2l python=3.8 -y
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conda create --name d2l python=3.9 -y
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```
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We now need to find out what version of CUDA you have installed.
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You can check this by running `nvcc --version`
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or `cat /usr/local/cuda/version.txt`.
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Assume that you have installed CUDA 10.1,
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Assume that you have installed CUDA 10.2,
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then you can install with the following command:
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```bash
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# For Windows users
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pip install mxnet-cu101==1.7.0 -f https://dist.mxnet.io/python
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pip install mxnet-cu102==1.7.0 -f https://dist.mxnet.io/python
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# For Linux and macOS users
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pip install mxnet-cu101==1.7.0
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pip install mxnet-cu102==1.7.0
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```
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You may change the last digits according to your CUDA version, e.g., `cu100` for
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CUDA 10.0 and `cu90` for CUDA 9.0.
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You may change the last digits according to your CUDA version, e.g., `cu101` for
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CUDA 10.1 and `cu90` for CUDA 9.0.
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:end_tab:
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config.ini

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@@ -12,7 +12,7 @@ author = Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola
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copyright = 2022, All authors. Licensed under CC-BY-SA-4.0 and MIT-0.
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release = 0.17.5
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release = 0.17.6
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d2l/__init__.py

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from d2l import mxnet as d2l # Use MXNet as the backend
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from d2l import torch as d2l # Use PyTorch as the backend
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from d2l import tensorflow as d2l # Use TensorFlow as the backend
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from d2l import paddle as d2l # Use PaddlePaddle as the backend
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"""
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__version__ = "0.17.5"
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__version__ = "0.17.6"

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