[README] Re-org the installation/usage structure.
Reduce the depth of TOC and re-organize it so that we first include
instructions for installation, then for usage.
@@ -37,10 +37,9 @@ developers to expose new optimization problems for AI.
**Table of Contents**
- [Features](#features)
-- [Getting Started](#getting-started)
- [Installation](#installation)
- [Building from Source](#building-from-source)
- - [Trying it out](#trying-it-out)
+- [Usage](#usage)
- [Leaderboards](#leaderboards)
- [LLVM Instruction Count](#llvm-instruction-count)
- [Contributing](#contributing)
@@ -81,15 +80,7 @@ features:
For a glimpse of what's to come, check out [our
roadmap](https://github.com/facebookresearch/CompilerGym/projects/1).
-# Getting Started
-
-Starting with CompilerGym is simple. If you not already familiar with the gym
-interface, refer to the
-[getting started guide](http://facebookresearch.github.io/CompilerGym/getting_started.html)
-for an overview of the key concepts.
-
-
-## Installation
+# Installation
Install the latest CompilerGym release using:
@@ -98,12 +89,12 @@ Install the latest CompilerGym release using:
The binary works on macOS and Linux (on Ubuntu 18.04, Fedora 28, Debian 10 or
newer equivalents).
-### Building from Source
+## Building from Source
If you prefer, you may build from source. This requires a modern C++ toolchain
and bazel.
-#### macOS <!-- omit in toc -->
+### macOS <!-- omit in toc -->
On macOS the required dependencies can be installed using
[homebrew](https://docs.brew.sh/Installation):
@@ -117,7 +108,7 @@ export PKG_CONFIG_PATH="/usr/local/opt/zlib/lib/pkgconfig"
Now proceed to [All platforms](#all-platforms) below.
-#### Linux <!-- omit in toc -->
+### Linux <!-- omit in toc -->
On debian-based linux systems, install the required toolchain using:
@@ -130,7 +121,7 @@ export CC=clang
export CXX=clang++
```
-#### All platforms <!-- omit in toc -->
+### All platforms <!-- omit in toc -->
We recommend using
[conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/)
@@ -173,8 +164,12 @@ environment using:
conda deactivate
conda env remove -n compiler_gym
+# Usage
-## Trying it out
+Starting with CompilerGym is simple. If you not already familiar with the gym
+interface, refer to the [getting started
+guide](http://facebookresearch.github.io/CompilerGym/getting_started.html) for
+an overview of the key concepts.
In Python, import `compiler_gym` to use the environments:
