Skip to content

Updated TF Windows build document #2220

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
copybara-service merged 17 commits into from
Apr 28, 2023
Merged

Updated TF Windows build document #2220

Changes from 16 commits
Commits
Show all changes
17 commits
Select commit Hold shift + click to select a range
fbcc36c
TF Windows documentation
mraunak Apr 13, 2023
4d7ad17
TF Windows doc update
mraunak Apr 13, 2023
d59833b
TF Windows Document Update
mraunak Apr 14, 2023
92d067a
GPU_doc_fix
mraunak Apr 17, 2023
9263014
Python Configure Update
mraunak Apr 17, 2023
7486c4d
Updated Python Configure section, GPU support
mraunak Apr 17, 2023
1f8a2c7
Updated GPU Support info
mraunak Apr 17, 2023
9558943
Updated TF Windows Doc
mraunak Apr 20, 2023
8a8345b
revised docs
mraunak Apr 24, 2023
9e3f5be
Revised TF Windows docs as per the comments
mraunak Apr 24, 2023
8d9770d
Update source_windows.md
mraunak Apr 24, 2023
7038fa4
Update site/en/install/source_windows.md
mraunak Apr 25, 2023
d179d70
Update site/en/install/source_windows.md
mraunak Apr 25, 2023
7dd83d7
resolved the comment
mraunak Apr 25, 2023
1958473
Merge branch 'mraunak/tf_win_docs' of https://github.com/Intel-tensor…
mraunak Apr 25, 2023
62dcc32
resolved comments
mraunak Apr 25, 2023
7be6338
Reverted a change
mraunak Apr 25, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
101 changes: 66 additions & 35 deletions site/en/install/source_windows.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@ environment.
### Install Python and the TensorFlow package dependencies

Install a
[Python 3.8+ 64-bit release for Windows](https://www.python.org/downloads/windows/){:.external}.
[Python 3.9+ 64-bit release for Windows](https://www.python.org/downloads/windows/){:.external}.
Select *pip* as an optional feature and add it to your `%PATH%` environmental
variable.

Expand Down Expand Up @@ -69,6 +69,8 @@ Note: TensorFlow is tested against the *Visual Studio 2019*.
See the Windows [GPU support](./gpu.md) guide to install the drivers and
additional software required to run TensorFlow on a GPU.

Note: GPU support on native-Windows is only available for 2.10 or earlier versions, starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2 or use tensorflow-cpu with TensorFlow-DirectML-Plugin

### Download the TensorFlow source code

Use [Git](https://git-scm.com/){:.external} to clone the
Expand All @@ -91,6 +93,28 @@ git checkout <em>branch_name</em> # r1.9, r1.10, etc.
Key Point: If you're having build problems on the latest development branch, try
a release branch that is known to work.

## Optional: Environmental Variable Set Up
Run following commands before running build command to avoid issue with package creation:
(If the below commands were set up while installing the packages, please ignore them). Run `set` check if all the paths were set correctly, run `echo %Environmental Variable%` e.g. `echo %BAZEL_VC%` to check path set up for a specific Environmental Variable

Python path set up issue [tensorflow:issue#59943](https://github.com/tensorflow/tensorflow/issues/59943),[tensorflow:issue#9436](https://github.com/tensorflow/tensorflow/issues/9436),[tensorflow:issue#60083](https://github.com/tensorflow/tensorflow/issues/60083)

<pre class="devsite-terminal tfo-terminal-windows devsite-click-to-copy">
set PATH=path/to/python # [e.g. (C:/Python310)]
set PATH=path/to/python/Scripts # [e.g. (C:/Python310/Scripts)]
set PYTHON_BIN_PATH=path/to/python_virtualenv/Scripts/python.exe
set PYTHON_LIB_PATH=path/to/python virtualenv/lib/site-packages
set PYTHON_DIRECTORY=path/to/python_virtualenv/Scripts
</pre>

Bazel/MSVC path set up issue [tensorflow:issue#54578](https://github.com/tensorflow/tensorflow/issues/54578)

<pre class="devsite-terminal tfo-terminal-windows devsite-click-to-copy">
set BAZEL_SH=C:/msys64/usr/bin/bash.exe
set BAZEL_VS=C:/Program Files(x86)/Microsoft Visual Studio/2019/BuildTools
set BAZEL_VC=C:/Program Files(x86)/Microsoft Visual Studio/2019/BuildTools/VC
</pre>


## Optional: Configure the build

Expand All @@ -114,49 +138,41 @@ differ):
<h4 class="showalways">View sample configuration session</h4>
<pre class="devsite-terminal tfo-terminal-windows">
python ./configure.py
Starting local Bazel server and connecting to it...
................
You have bazel 0.15.0 installed.
Please specify the location of python. [Default is C:\python36\python.exe]:

You have bazel 5.3.0 installed.
Please specify the location of python. [Default is C:\Python310\python.exe]:
Found possible Python library paths:
C:\python36\lib\site-packages
Please input the desired Python library path to use. Default is [C:\python36\lib\site-packages]

Do you wish to build TensorFlow with CUDA support? [y/N]: <b>Y</b>
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 9.0]:

Please specify the location where CUDA 9.0 toolkit is installed. Refer to README.md for more details. [Default is C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v9.0]:
C:\Python310\lib\site-packages
Please input the desired Python library path to use. Default is [C:\Python310\lib\site-packages]

Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]: <b>7.0</b>
Do you wish to build TensorFlow with ROCm support? [y/N]:
No ROCm support will be enabled for TensorFlow.

Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v9.0]: <b>C:\tools\cuda</b>

Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 3.5,7.0]: <b>3.7</b>
WARNING: Cannot build with CUDA support on Windows.
Starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is /arch:AVX]:


Would you like to override eigen strong inline for some C++ compilation to reduce the compilation time? [Y/n]:
Eigen strong inline overridden.

Configuration finished
</pre>
</section>

### Configuration options
Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]:
Not configuring the WORKSPACE for Android builds.

For [GPU support](./gpu.md), specify the versions of CUDA and cuDNN. If your
system has multiple versions of CUDA or cuDNN installed, explicitly set the
version instead of relying on the default. `./configure.py` creates symbolic
links to your system's CUDA libraries—so if you update your CUDA library paths,
this configuration step must be run again before building.
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
--config=mkl # Build with MKL support.
--config=mkl_aarch64 # Build with oneDNN and Compute Library for the Arm Architecture (ACL).
--config=monolithic # Config for mostly static monolithic build.
--config=numa # Build with NUMA support.
--config=dynamic_kernels # (Experimental) Build kernels into separate shared objects.
--config=v1 # Build with TensorFlow 1 API instead of TF 2 API.
Preconfigured Bazel build configs to DISABLE default on features:
--config=nogcp # Disable GCP support.
--config=nonccl # Disable NVIDIA NCCL support.

Warning: TF-TRT Windows support is provided experimentally. No guarantee is made
regarding functionality or engineering support. Use at your own risk.
</pre>
</section>

## Build and install the pip package

Expand Down Expand Up @@ -184,12 +200,21 @@ bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package

#### GPU support

Note: GPU support on native-Windows is only available for 2.10 or earlier versions, starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2 or use tensorflow-cpu with TensorFlow-DirectML-Plugin

To make the TensorFlow package builder with GPU support:

<pre class="devsite-terminal tfo-terminal-windows devsite-click-to-copy">
bazel build --config=opt --config=cuda --define=no_tensorflow_py_deps=true //tensorflow/tools/pip_package:build_pip_package
</pre>

Commands to clean the bazel cache to resolve errors due to invalid or outdated cached data, bazel clean with --expunge flag removes files permanently

<pre class="devsite-terminal tfo-terminal-windows devsite-click-to-copy">
bazel clean
bazel clean --expunge
</pre>

#### Bazel build options

Use this option when building to avoid issue with package creation:
Expand Down Expand Up @@ -223,13 +248,16 @@ Although it is possible to build both CUDA and non-CUDA configs under the
same source tree, we recommend running `bazel clean` when switching between
these two configurations in the same source tree.


### Install the package

The filename of the generated `.whl` file depends on the TensorFlow version and
your platform. Use `pip3 install` to install the package, for example:

<pre class="devsite-terminal tfo-terminal-windows prettyprint lang-bsh">
pip3 install C:/tmp/tensorflow_pkg/tensorflow-<var>version</var>-cp36-cp36m-win_amd64.whl
pip3 install C:/tmp/tensorflow_pkg/tensorflow-<var>version</var>-<var>tags</var>.whl

e.g. pip3 install C:/tmp/tensorflow_pkg/tensorflow-2.12.0-cp310-cp310-win_amd64.whl
</pre>

Success: TensorFlow is now installed.
Expand All @@ -256,12 +284,12 @@ considered a Unix absolute path since it starts with a slash.)

Add the Bazel and Python installation directories to your `$PATH` environmental
variable. If Bazel is installed to `C:\tools\bazel.exe`, and Python to
`C:\Python36\python.exe`, set your `PATH` with:
`C:\Python\python.exe`, set your `PATH` with:

<pre class="prettyprint lang-bsh">
# Use Unix-style with ':' as separator
<code class="devsite-terminal">export PATH="/c/tools:$PATH"</code>
<code class="devsite-terminal">export PATH="/c/Python36:$PATH"</code>
<code class="devsite-terminal">export PATH="/c/path/to/Python:$PATH"</code>
</pre>

For GPU support, add the CUDA and cuDNN bin directories to your `$PATH`:
Expand All @@ -272,6 +300,8 @@ For GPU support, add the CUDA and cuDNN bin directories to your `$PATH`:
<code class="devsite-terminal">export PATH="/c/tools/cuda/bin:$PATH"</code>
</pre>

Note: Starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2 or use tensorflow-cpu with TensorFlow-DirectML-Plugin

<a name="tested_build_configurations"></a>
## Tested build configurations

Expand Down Expand Up @@ -311,6 +341,7 @@ For GPU support, add the CUDA and cuDNN bin directories to your `$PATH`:
</table>

### GPU
Note: GPU support on native-Windows is only available for 2.10 or earlier versions, starting in TF 2.11, CUDA build is not supported for Windows. For using TensorFlow GPU on Windows, you will need to build/install TensorFlow in WSL2 or use tensorflow-cpu with TensorFlow-DirectML-Plugin

<table>
<tr><th>Version</th><th>Python version</th><th>Compiler</th><th>Build tools</th><th>cuDNN</th><th>CUDA</th></tr>
Expand Down