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[ROCm] Cleanup Dockerfile and remove outdated patch (#6482)

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Hongxia Yang
2024-07-17 01:47:02 -04:00
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parent 1d094fd7c0
commit 10383887e0
3 changed files with 14 additions and 77 deletions
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docs/source/getting_started/amd-installation.rst
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@@ -3,7 +3,7 @@
Installation with ROCm
======================
vLLM supports AMD GPUs with ROCm 5.7 and 6.0.
vLLM supports AMD GPUs with ROCm 6.1.
Requirements
------------
@@ -11,7 +11,7 @@ Requirements
* OS: Linux
* Python: 3.8 -- 3.11
* GPU: MI200s (gfx90a), MI300 (gfx942), Radeon RX 7900 series (gfx1100)
* ROCm 6.0 and ROCm 5.7
* ROCm 6.1
Installation options:
@@ -27,10 +27,10 @@ You can build and install vLLM from source.
First, build a docker image from `Dockerfile.rocm <https://github.com/vllm-project/vllm/blob/main/Dockerfile.rocm>`_ and launch a docker container from the image.
`Dockerfile.rocm <https://github.com/vllm-project/vllm/blob/main/Dockerfile.rocm>`_ uses ROCm 6.0 by default, but also supports ROCm 5.7.
`Dockerfile.rocm <https://github.com/vllm-project/vllm/blob/main/Dockerfile.rocm>`_ uses ROCm 6.1 by default, but also supports ROCm 5.7 and 6.0 in older vLLM branches.
It provides flexibility to customize the build of docker image using the following arguments:
* `BASE_IMAGE`: specifies the base image used when running ``docker build``, specifically the PyTorch on ROCm base image. We have tested ROCm 5.7 and ROCm 6.0. The default is `rocm/pytorch:rocm6.0_ubuntu20.04_py3.9_pytorch_2.1.1`
* `BASE_IMAGE`: specifies the base image used when running ``docker build``, specifically the PyTorch on ROCm base image.
* `BUILD_FA`: specifies whether to build CK flash-attention. The default is 1. For `Radeon RX 7900 series (gfx1100) <https://rocm.docs.amd.com/projects/radeon/en/latest/index.html>`_, this should be set to 0 before flash-attention supports this target.
* `FX_GFX_ARCHS`: specifies the GFX architecture that is used to build CK flash-attention, for example, `gfx90a;gfx942` for MI200 and MI300. The default is `gfx90a;gfx942`
* `FA_BRANCH`: specifies the branch used to build the CK flash-attention in `ROCm's flash-attention repo <https://github.com/ROCmSoftwarePlatform/flash-attention>`_. The default is `ae7928c`
@@ -39,24 +39,17 @@ It provides flexibility to customize the build of docker image using the followi
Their values can be passed in when running ``docker build`` with ``--build-arg`` options.
To build vllm on ROCm 6.0 for MI200 and MI300 series, you can use the default:
To build vllm on ROCm 6.1 for MI200 and MI300 series, you can use the default:
.. code-block:: console
$ docker build -f Dockerfile.rocm -t vllm-rocm .
$ DOCKER_BUILDKIT=1 docker build -f Dockerfile.rocm -t vllm-rocm .
To build vllm on ROCm 6.0 for Radeon RX7900 series (gfx1100), you should specify ``BUILD_FA`` as below:
To build vllm on ROCm 6.1 for Radeon RX7900 series (gfx1100), you should specify ``BUILD_FA`` as below:
.. code-block:: console
$ docker build --build-arg BUILD_FA="0" -f Dockerfile.rocm -t vllm-rocm .
To build docker image for vllm on ROCm 5.7, you can specify ``BASE_IMAGE`` as below:
.. code-block:: console
$ docker build --build-arg BASE_IMAGE="rocm/pytorch:rocm5.7_ubuntu22.04_py3.10_pytorch_2.0.1" \
-f Dockerfile.rocm -t vllm-rocm .
$ DOCKER_BUILDKIT=1 docker build --build-arg BUILD_FA="0" -f Dockerfile.rocm -t vllm-rocm .
To run the above docker image ``vllm-rocm``, use the below command:
@@ -85,25 +78,12 @@ Option 2: Build from source
0. Install prerequisites (skip if you are already in an environment/docker with the following installed):
- `ROCm <https://rocm.docs.amd.com/en/latest/deploy/linux/index.html>`_
- `Pytorch <https://pytorch.org/>`_
- `PyTorch <https://pytorch.org/>`_
- `hipBLAS <https://rocm.docs.amd.com/projects/hipBLAS/en/latest/install.html>`_
For installing PyTorch, you can start from a fresh docker image, e.g, `rocm/pytorch:rocm6.1.2_ubuntu20.04_py3.9_pytorch_staging`, `rocm/pytorch:rocm6.0_ubuntu20.04_py3.9_pytorch_2.1.1`, `rocm/pytorch-nightly`.
For installing PyTorch, you can start from a fresh docker image, e.g, `rocm/pytorch:rocm6.1.2_ubuntu20.04_py3.9_pytorch_staging`, `rocm/pytorch-nightly`.
Alternatively, you can install pytorch using pytorch wheels. You can check Pytorch installation guild in Pytorch `Getting Started <https://pytorch.org/get-started/locally/>`_
For rocm6.0:
.. code-block:: console
$ pip3 install torch --index-url https://download.pytorch.org/whl/rocm6.0
For rocm5.7:
.. code-block:: console
$ pip install torch --index-url https://download.pytorch.org/whl/rocm5.7
Alternatively, you can install PyTorch using PyTorch wheels. You can check PyTorch installation guild in PyTorch `Getting Started <https://pytorch.org/get-started/locally/>`_
1. Install `Triton flash attention for ROCm <https://github.com/ROCm/triton>`_
@@ -115,8 +95,6 @@ Install ROCm's Triton flash attention (the default triton-mlir branch) following
Install ROCm's flash attention (v2.0.4) following the instructions from `ROCm/flash-attention <https://github.com/ROCm/flash-attention/tree/flash_attention_for_rocm#amd-gpurocm-support>`_
.. note::
- If you are using rocm5.7 with pytorch 2.1.0 onwards, you don't need to apply the `hipify_python.patch`. You can build the ROCm flash attention directly.
- If you fail to install `ROCm/flash-attention`, try cloning from the commit `6fd2f8e572805681cd67ef8596c7e2ce521ed3c6`.
- ROCm's Flash-attention-2 (v2.0.4) does not support sliding windows attention.
- You might need to downgrade the "ninja" version to 1.10 it is not used when compiling flash-attention-2 (e.g. `pip install ninja==1.10.2.4`)
@@ -131,7 +109,6 @@ Install ROCm's flash attention (v2.0.4) following the instructions from `ROCm/fl
.. tip::
- You may need to turn on the ``--enforce-eager`` flag if you experience process hang when running the `benchmark_thoughput.py` script to test your installation.
- Triton flash attention is used by default. For benchmarking purposes, it is recommended to run a warm up step before collecting perf numbers.
- To use CK flash-attention, please use this flag ``export VLLM_USE_TRITON_FLASH_ATTN=0`` to turn off triton flash attention.
- The ROCm version of pytorch, ideally, should match the ROCm driver version.
- To use CK flash-attention or PyTorch naive attention, please use this flag ``export VLLM_USE_TRITON_FLASH_ATTN=0`` to turn off triton flash attention.
- The ROCm version of PyTorch, ideally, should match the ROCm driver version.