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https://github.com/edumucelli/build-tensorflow

Build Tensorflow from source using a Dockerfile
https://github.com/edumucelli/build-tensorflow

cuda cudnn docker tensorflow

Last synced: about 2 months ago
JSON representation

Build Tensorflow from source using a Dockerfile

Host: GitHub
URL: https://github.com/edumucelli/build-tensorflow
Owner: edumucelli
Created: 2019-10-21T20:36:40.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2019-11-06T22:56:11.000Z (over 5 years ago)
Last Synced: 2024-11-06T02:12:07.721Z (3 months ago)
Topics: cuda, cudnn, docker, tensorflow
Language: Dockerfile
Size: 15.6 KB
Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

# Build Tensorflow from source

(You may want to see the already built [releases](https://github.com/edumucelli/build-tensorflow/releases) before building yourself)

This project aims to build the Tensorflow from the source using a Dockerfile.
The idea is to simplify the build so that one can choose the the Cuda/CuDNN
version which better fits ones environment.

As Tensorflow pre-built binaries require specific Cuda/CuDnn versions
up to the patch version, e.g., [#15656](https://github.com/tensorflow/tensorflow/issues/15656) you will
struggle if you have Cuda 9.1/2, as pre-built binaries won't work as they
require cuda 9.0.

The default configuration of the Dockerfile will build:

* Python 3.5
* Tensorflow 1.7
* Cuda 9.1.85
* CuDNN 7.1.3

As it downloads the packages straight from Nvidia you can build the one
you prefer with Cuda, the package comes straight from [here](https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64).
The following versions are then available, just replace the `CUDA_VERSION`
variable by one of the following:

* 8.0.44
* 8.0.61
* 9.0.176
* 9.1.85
* 9.2.88
* 9.2.148
* 10.0.130
* 10.1.105
* 10.1.168
* 10.1.243

Likewise, CuDNN version can be one of the following. Just replace the `CUDNN_PKG_VERSION`
variable to the one you prefer. The packages come directly from [here](https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64).

* 7.0.1.13-1+cuda8.0
* 7.0.2.38-1+cuda8.0
* 7.0.3.11-1+cuda8.0
* 7.0.3.11-1+cuda9.0
* 7.0.4.31-1+cuda8.0
* 7.0.4.31-1+cuda9.0
* 7.0.5.15-1+cuda8.0
* 7.0.5.15-1+cuda9.0
* 7.0.5.15-1+cuda9.1
* 7.1.1.5-1+cuda8.0
* 7.1.1.5-1+cuda9.0
* 7.1.1.5-1+cuda9.1
* 7.1.2.21-1+cuda8.0
* 7.1.2.21-1+cuda9.0
* 7.1.2.21-1+cuda9.1
* 7.1.3.16-1+cuda8.0
* 7.1.3.16-1+cuda9.0
* 7.1.3.16-1+cuda9.1
* 7.1.4.18-1+cuda8.0
* 7.1.4.18-1+cuda9.0
* 7.1.4.18-1+cuda9.2
* 7.2.1.38-1+cuda8.0
* 7.2.1.38-1+cuda9.0
* 7.2.1.38-1+cuda9.2
* 7.3.0.29-1+cuda9.0
* 7.3.0.29-1+cuda10.0
* 7.3.1.20-1+cuda9.0
* 7.3.1.20-1+cuda9.2
* 7.3.1.20-1+cuda10.0
* 7.4.1.5-1+cuda9.0
* 7.4.1.5-1+cuda9.2
* 7.4.1.5-1+cuda10.0
* 7.4.2.24-1+cuda9.0
* 7.4.2.24-1+cuda9.2
* 7.4.2.24-1+cuda10.0
* 7.5.0.56-1+cuda9.0
* 7.5.0.56-1+cuda9.2
* 7.5.0.56-1+cuda10.0
* 7.5.0.56-1+cuda10.1
* 7.5.1.10-1+cuda9.0
* 7.5.1.10-1+cuda9.2
* 7.5.1.10-1+cuda10.0
* 7.5.1.10-1+cuda10.1
* 7.6.0.64-1+cuda9.0
* 7.6.0.64-1+cuda9.2
* 7.6.0.64-1+cuda10.0
* 7.6.0.64-1+cuda10.1
* 7.6.1.34-1+cuda9.0
* 7.6.1.34-1+cuda9.2
* 7.6.1.34-1+cuda10.0
* 7.6.1.34-1+cuda10.1
* 7.6.2.24-1+cuda9.0
* 7.6.2.24-1+cuda9.2
* 7.6.2.24-1+cuda10.0
* 7.6.2.24-1+cuda10.1
* 7.6.3.30-1+cuda9.0
* 7.6.3.30-1+cuda9.2
* 7.6.3.30-1+cuda10.0
* 7.6.3.30-1+cuda10.1
* 7.6.4.38-1+cuda9.0
* 7.6.4.38-1+cuda9.2
* 7.6.4.38-1+cuda10.0
* 7.6.4.38-1+cuda10.1

One thing to note is that some of the packages will respect the Cuda version
you are looking for, e.g.,

```
apt-get install ...
cuda-command-line-tools-9-1 \
cuda-cublas-dev-9-1 \
cuda-cudart-dev-9-1 \
cuda-cufft-dev-9-1 \
cuda-curand-dev-9-1 \
cuda-cusolver-dev-9-1 \
cuda-cusparse-dev-9-1 \
```

have the `9-1` in the package names, if you are building a Cuda `10.1` then
you should replace the `9-1` everywhere by `10-1`.

## Building

Just run `(sudo) docker build -t build-tensorflow .` in the same directory
as the one where the Dockerfile is stored. The tensorflow well will be
stored on the `/tmp/pip` directory of the container.

## Getting the wheel out of the container

There are [several ways](https://stackoverflow.com/questions/22049212/copying-files-from-docker-container-to-host) to copy
data from container to the host machine. Here is a suggestion:

`sudo docker cp CONTAINER_ID:/tmp/pip/tensorflow-1.7.1-cp35-cp35m-linux_x86_64.whl .`

To get the `CONTAINER_ID` just run `docker ps -alq` or `docker ps` then see the `CONTAINER_ID`
respective to the `build-tensorflow` image, or the one you -t `image tag` you gave in the
building command.