PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Docker能在所有主要操作系统(包括Linux,Mac OS X和Windows)上运行。 请注意,您需要更改 `Dockers设置 <https://github.com/PaddlePaddle/Paddle/issues/627>`_ 才能充分利用Mac OS X和Windows上的硬件资源。
docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:0.10.0rc1-gpu
docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:<version>-gpu
3. Use production image to release you AI application
Suppose that we have a simple application program in :code:`a.py`, we can test and run it using the production image:
```bash
docker run -it -v $PWD:/work paddle /work/a.py
```
But this works only if all dependencies of :code:`a.py` are in the production image. If this is not the case, we need to build a new Docker image from the production image and with more dependencies installs.
PaddlePaddle Book
...
...
@@ -71,11 +117,11 @@ PaddlePaddle Book is an interactive Jupyter Notebook for users and developers.
We already exposed port 8888 for this book. If you want to
dig deeper into deep learning, PaddlePaddle Book definitely is your best choice.
Once you are inside the container, simply issue the command:
We provide a packaged book image, simply issue the command:
.. code-block:: bash
jupyter notebook
docker run -p 8888:8888 paddlepaddle/book
Then, you would back and paste the address into the local browser:
...
...
@@ -85,32 +131,6 @@ Then, you would back and paste the address into the local browser:
That's all. Enjoy your journey!
Non-AVX Images
--------------
Please be aware that the CPU-only and the GPU images both use the AVX
instruction set, but old computers produced before 2008 do not support
AVX. The following command checks if your Linux computer supports
AVX:
.. code-block:: bash
if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi
If it doesn't, we will need to build non-AVX images manually from
Given the development image `paddle:dev`, the following command builds PaddlePaddle from the source tree on the development computer (host):
```bash
docker run -v$PWD:/paddle -e"WITH_GPU=OFF"-e"WITH_AVX=ON"-e"TEST=OFF" paddle:dev
docker run -v$PWD:/paddle -e"WITH_GPU=OFF"-e"WITH_AVX=ON"-e"WITH_TEST=OFF"-e"RUN_TEST=OFF" paddle:dev
```
This command mounts the source directory on the host into `/paddle` in the container, so the default entry point of `paddle:dev`, `build.sh`, could build the source code with possible local changes. When it writes to `/paddle/build` in the container, it writes to `$PWD/build` on the host indeed.
...
...
@@ -108,7 +108,11 @@ This command mounts the source directory on the host into `/paddle` in the conta
Users can specify the following Docker build arguments with either "ON" or "OFF" value:
-`WITH_GPU`: ***Required***. Generates NVIDIA CUDA GPU code and relies on CUDA libraries.
-`WITH_AVX`: ***Required***. Set to "OFF" prevents from generating AVX instructions. If you don't know what is AVX, you might want to set "ON".
-`TEST`: ***Optional, default OFF***. Build unit tests and run them after building.
-`WITH_TEST`: ***Optional, default OFF***. Build unit tests binaries. Once you've built the unit tests, you can run these test manually by the following command:
```bash
docker run -v$PWD:/paddle -e"WITH_GPU=OFF"-e"WITH_AVX=ON" paddle:dev sh -c"cd /paddle/build; make coverall"
```
-`RUN_TEST`: ***Optional, default OFF***. Run unit tests after building. You can't run unit tests without building it.