Skip to content
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

Jump to bottom

Fix links in TensorFlow Lite for Microcontrollers readme #29933

Merged
merged 1 commit into from Jun 26, 2019
Merged

Fix links in TensorFlow Lite for Microcontrollers readme #29933

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
10 changes: 5 additions & 5 deletions tensorflow/lite/experimental/micro/README.md
View file
Open in desktop
Expand Up @@ -14,7 +14,7 @@ detection model, takes up a total of 22KB.
* [Getting Started with Portable Reference Code](#getting-started-with-portable-reference-code)
* [Building Portable Reference Code using Make](#building-portable-reference-code-using-make)
* [Building for the "Blue Pill" STM32F103 using Make](#building-for-the-blue-pill-stm32f103-using-make)
* [Building for "Hifive1" SiFive FE310 development board using Make](#building-for-hifive1-sifive-fe310-development-board-using-make)
* [Building for "Hifive1" SiFive FE310 development board using Make](#building-for-hifive1-sifive-fe310-development-board)
* [Building for Ambiq Micro Apollo3Blue EVB using Make](#building-for-ambiq-micro-apollo3blue-evb-using-make)
* [Additional Apollo3 Instructions](#additional-apollo3-instructions)
* [Building for the Eta Compute ECM3531 EVB using Make](#Building-for-the-Eta-Compute-ECM3531-EVB-using-Make)
Expand All @@ -23,12 +23,12 @@ detection model, takes up a total of 22KB.

- [Generating Project Files](#generating-project-files)

- [Generating Arduino Libraries](#generating-arduino_libraries)
- [Generating Arduino Libraries](#generating-arduino-libraries)

- [How to Port TensorFlow Lite Micro to a New Platform](#how-to-port-tensorflow-lite-micro-to-a-new-platform)

* [Requirements](#requirements)
* [Getting Started](getting-started)
* [Getting Started](#getting-started-1)
* [Troubleshooting](#troubleshooting)
* [Optimizing for your Platform](#optimizing-for-your-platform)
* [Code Module Organization](#code-module-organization)
Expand Down Expand Up @@ -615,7 +615,7 @@ As mentioned above, the one function you will need to implement for a completely
new platform is debug logging. If your device is just a variation on an existing
platform you may be able to reuse code that's already been written. To
understand what's available, begin with the default reference implementation at
[tensorflow/lite/experimental/micro/debug_log.cc](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/micro/debug_log.cc]),
[tensorflow/lite/experimental/micro/debug_log.cc](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/micro/debug_log.cc),
which uses fprintf and stderr. If your platform has this level of support for
the C standard library in its toolchain, then you can just reuse this.
Otherwise, you'll need to do some research into how your platform and device can
Expand Down Expand Up @@ -900,7 +900,7 @@ git commit -a -m "Added DebugLog() support for <your platform>"
git push origin master
```

Then go back to https://github.com/<your account>/tensorflow, and choose "New
Then go back to `https://github.com/<your account>/tensorflow`, and choose "New
Pull Request" near the top. You should then be able to go through the standard
TensorFlow PR process to get your change added to the main repository, and
available to the rest of the community!
Expand Down