Merge pull request #23 from Naomiusearch/flash_attention_for_rocm

Make installation steps look better

README.md

@@ -217,15 +217,15 @@ pytest -q -s tests/test_flash_attn.py
 - PyTorch 1.12.1+
 - MI200 & MI300 GPUs
 ## Method 1: Build from Source
-### i. Launch a ROCm PyTorch docker (recommended): E.g. 
+### I. Launch a ROCm PyTorch docker (recommended): E.g. 
 ```bash
 docker run -it --device /dev/dri --device /dev/kfd --network host --ipc host --privileged --cap-add SYS_PTRACE --group-add video --security-opt seccomp=unconfined rocm/pytorch:rocm5.7_ubuntu22.04_py3.10_pytorch_2.0.1
 ```
-### ii. Clone the repo with submodules
+### II. Clone the repo with submodules
 ```bash
 git clone --recursive https://github.com/ROCmSoftwarePlatform/flash-attention.git
 ```
-### iii. (optional): Build for the desired GPU architecture(s) by setting the enviroment variable (semicolon seperated). We currently only support the following options. If you do not specify, defaultly it will build for your native device architecture:
+### III. (optional): Build for the desired GPU architecture(s) by setting the enviroment variable (semicolon seperated). We currently only support the following options. If you do not specify, defaultly it will build for your native device architecture:
 To manually target for MI200 series:
 ```bash
 export GPU_ARCHS="gfx90a"
@@ -234,7 +234,7 @@ To manually target for MI300 series:
 ```bash
 export GPU_ARCHS="gfx940;gfx941;gfx942"
 ```
-### iii. Build from source
+### IV. Build from source
 ```bash
 $ cd flash-attention
 $ export PYTHON_SITE_PACKAGES=$(python -c 'import site; print(site.getsitepackages()[0])')