1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
|
book_path: /mobile/_book.yaml
project_path: /mobile/_project.yaml
# TensorFlow Lite for iOS
## Building
To create a universal iOS library for TensorFlow Lite, you need to build it
using Xcode's command line tools on a MacOS machine. If you have not already,
you will need to install Xcode 8 or later and the tools using `xcode-select`:
```bash
xcode-select --install
```
If this is a new install, you will need to run XCode once to agree to the
license before continuing.
(You will also need to have [Homebrew](http://brew.sh/) installed.)
Then install
[automake](https://en.wikipedia.org/wiki/Automake)/[libtool](https://en.wikipedia.org/wiki/GNU_Libtool):
```bash
brew install automake
brew install libtool
```
If you get an error where either automake or libtool install but do not link correctly, you'll first need to:
```bash
sudo chown -R $(whoami) /usr/local/*
```
Then follow the instructions to perform the linking:
```bash
brew link automake
brew link libtool
```
Then you need to run a shell script to download the dependencies you need:
```bash
tensorflow/contrib/lite/download_dependencies.sh
```
This will fetch copies of libraries and data from the web and install them in
`tensorflow/contrib/lite/downloads`.
With all of the dependencies set up, you can now build the library for all five
supported architectures on iOS:
```bash
tensorflow/contrib/lite/build_ios_universal_lib.sh
```
Under the hood this uses a makefile in `tensorflow/contrib/lite` to build the
different versions of the library, followed by a call to `lipo` to bundle them
into a universal file containing armv7, armv7s, arm64, i386, and x86_64
architectures. The resulting library is in
`tensorflow/contrib/lite/gen/lib/libtensorflow-lite.a`.
If you get an error such as `no such file or directory: 'x86_64'` when running
`build_ios_universal_lib.sh`: open Xcode > Preferences > Locations, and ensure
a value is selected in the "Command Line Tools" dropdown.
## Using in your own application
You'll need to update various settings in your app to link against TensorFlow
Lite. You can view them in the example project at
`tensorflow/contrib/lite/examples/ios/simple/simple.xcodeproj` but here's a full
rundown:
- You'll need to add the library at
`tensorflow/contrib/lite/gen/lib/libtensorflow-lite.a` to your linking build
stage, and in Search Paths add `tensorflow/contrib/lite/gen/lib` to the
Library Search Paths setting.
- The _Header Search_ paths needs to contain:
- the root folder of tensorflow,
- `tensorflow/contrib/lite/downloads`
- `tensorflow/contrib/lite/downloads/flatbuffers/include`
- C++11 support (or later) should be enabled by setting `C++ Language Dialect`
to `GNU++11` (or `GNU++14`), and `C++ Standard Library` to `libc++`.
|
