diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 18e92dbf..6baa4bd2 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -17,7 +17,7 @@ All contributors must sign the CLA for their pull requests to be eligible for me You can find the CLA [here](https://code.facebook.com/cla). ## Issues -We use [GitHub issues](https://github.com/facebookresearch/flashlight/issues) to track public bugs. When filing, a bug, please make sure your description is clear and include sufficient instructions to reproduce the issue (for instance, your OS, compiler version, and selected backend). +We use [GitHub issues](https://github.com/flashlight/flashlight/issues) to track public bugs. When filing, a bug, please make sure your description is clear and include sufficient instructions to reproduce the issue (for instance, your OS, compiler version, and selected backend). ## License By contributing to flashlight, you agree that your contributions will be licensed diff --git a/README.md b/README.md index ff7d5a0b..74f9fd9d 100644 --- a/README.md +++ b/README.md @@ -6,9 +6,9 @@ | [**Installation**](#building-and-installing) | [**Documentation**](https://fl.readthedocs.io/en/latest/) -[![CircleCI](https://circleci.com/gh/facebookresearch/flashlight.svg?style=shield)](https://circleci.com/gh/facebookresearch/flashlight) +[![CircleCI](https://circleci.com/gh/flashlight/flashlight.svg?style=shield)](https://app.circleci.com/pipelines/github/flashlight/flashlight) [![Documentation Status](https://img.shields.io/readthedocs/fl.svg)](https://fl.readthedocs.io/en/latest/) -[![Docker Image Build Status](https://img.shields.io/github/workflow/status/facebookresearch/flashlight/Publish%20Docker%20images?label=docker%20image%20build)](https://hub.docker.com/r/flml/flashlight/tags) +[![Docker Image Build Status](https://img.shields.io/github/workflow/status/flashlight/flashlight/Publish%20Docker%20images?label=docker%20image%20build)](https://hub.docker.com/r/flml/flashlight/tags) [![Join the chat at https://gitter.im/flashlight-ml/community](https://img.shields.io/gitter/room/flashlight-ml/community)](https://gitter.im/flashlight-ml/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![Docker Image for CUDA backend](https://img.shields.io/docker/image-size/flml/flashlight/cuda-latest?label=docker%20%28cuda%29&logo=docker)](https://hub.docker.com/r/flml/flashlight/tags?page=1&ordering=last_updated&name=cuda-latest) @@ -26,8 +26,8 @@ tensor library. - CUDA and CPU backends for GPU and CPU training. - An emphasis on efficiency and scale. -Native support in C++ and simple extensibility makes Flashlight a powerful research framework that's *hackable to its core* and enables fast iteration on new experimental setups and algorithms without sacrificing performance. In a single repository, Flashlight provides [apps](https://github.com/facebookresearch/flashlight/tree/master/flashlight/app) for research across multiple domains: -- [Automatic speech recognition](https://github.com/facebookresearch/flashlight/tree/master/flashlight/app/asr) (the [wav2letter](https://github.com/facebookresearch/wav2letter/) project) — [Documentation](flashlight/app/asr) | [Tutorial](flashlight/app/asr/tutorial) +Native support in C++ and simple extensibility makes Flashlight a powerful research framework that's *hackable to its core* and enables fast iteration on new experimental setups and algorithms without sacrificing performance. In a single repository, Flashlight provides [apps](https://github.com/flashlight/flashlight/tree/master/flashlight/app) for research across multiple domains: +- [Automatic speech recognition](https://github.com/flashlight/flashlight/tree/master/flashlight/app/asr) (the [wav2letter](https://github.com/flashlight/wav2letter/) project) — [Documentation](flashlight/app/asr) | [Tutorial](flashlight/app/asr/tutorial) - [Image classification](flashlight/app/imgclass) - [Object detection](flashlight/app/objdet) - [Language modeling](flashlight/app/lm) @@ -188,7 +188,7 @@ To build the Flashlight CPU backend from source using dependencies installed wit ##### Build Using the `vcpkg` Toolchain File To build Flashlight from source with these dependencies, clone the repository: ```shell -git clone https://github.com/facebookresearch/flashlight.git && cd flashlight +git clone https://github.com/flashlight/flashlight.git && cd flashlight mkdir -p build && cd build ``` Then, build from source using `vcpkg`'s [CMake toolchain](https://github.com/microsoft/vcpkg/blob/master/docs/users/integration.md#cmake-toolchain-file-recommended-for-open-source-cmake-projects): @@ -209,7 +209,7 @@ Some dependencies marked below are downloaded and installed automatically if not **Once all dependencies are installed**, clone the repository: ```shell -git clone https://github.com/facebookresearch/flashlight.git && cd flashlight +git clone https://github.com/flashlight/flashlight.git && cd flashlight mkdir -p build && cd build ``` Then build all Flashlight components with: @@ -224,7 +224,7 @@ To build a smaller subset of Flashlight features/apps, see the [build options](# To install Flashlight in a custom directory, use CMake's [`CMAKE_INSTALL_PREFIX`](https://cmake.org/cmake/help/v3.10/variable/CMAKE_INSTALL_PREFIX.html) argument. Flashlight libraries can be built as shared libraries using CMake's [`BUILD_SHARED_LIBS`](https://cmake.org/cmake/help/v3.10/variable/BUILD_SHARED_LIBS.html) argument. -Flashlight uses modern CMake and `IMPORTED` targets for most dependencies. If a dependency isn't found, passing `-D_DIR` to your `cmake` command or exporting `_DIR` as an environment variable equal to the path to `Config.cmake` can help locate dependencies on your system. See [the documentation](https://cmake.org/cmake/help/v3.10/command/find_package.html) for more details. If CMake is failing to locate a package, check to see if a corresponding [issue](https://github.com/facebookresearch/flashlight/issues) has already been created before creating your own. +Flashlight uses modern CMake and `IMPORTED` targets for most dependencies. If a dependency isn't found, passing `-D_DIR` to your `cmake` command or exporting `_DIR` as an environment variable equal to the path to `Config.cmake` can help locate dependencies on your system. See [the documentation](https://cmake.org/cmake/help/v3.10/command/find_package.html) for more details. If CMake is failing to locate a package, check to see if a corresponding [issue](https://github.com/flashlight/flashlight/issues) has already been created before creating your own. #### Dependencies diff --git a/bindings/python/README.md b/bindings/python/README.md index 516e79e7..91c9672c 100644 --- a/bindings/python/README.md +++ b/bindings/python/README.md @@ -150,7 +150,7 @@ where ``ntokens`` is the number of tokens predicted for each frame (number of cl ### Beam-search decoder Currently lexicon-based and lexicon-free based beam-search decoder is supported for CTC/ASG models only (no seq2seq models support). Also only n-gram (KenLM) language model is supported for python bindings. However, one can define custom language model inside python and use it for decoding, details see below. -To have better understanding how this beam-search decoder works please see [Beam-search decoder section](https://github.com/facebookresearch/flashlight/tree/master/flashlight/app/asr#beam-search-decoders). +To have better understanding how this beam-search decoder works please see [Beam-search decoder section](https://github.com/flashlight/flashlight/tree/master/flashlight/app/asr#beam-search-decoders). To run decoder one first should define its options: ```python @@ -182,7 +182,7 @@ To run decoder one first should define its options: Then we should prepare tokens dictionary (tokens for which acoustic models returns probability for each frame), lexicon (mapping between words and its spelling with the tokens set). -Details on the tokens and lexicon files format have a look at [Data Preparation](https://github.com/facebookresearch/flashlight/tree/master/flashlight/app/asr#data-preparation). +Details on the tokens and lexicon files format have a look at [Data Preparation](https://github.com/flashlight/flashlight/tree/master/flashlight/app/asr#data-preparation). ```python from flashlight.lib.text.dictionary import Dictionary, load_words, create_word_dict