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Installation | ||
============ | ||
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CacheFlow is a Python library that includes some C++ and CUDA code. | ||
CacheFlow can run on systems that meet the following requirements: | ||
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* OS: Linux | ||
* Python: 3.8 or higher | ||
* CUDA: 11.0 -- 11.8 | ||
* GPU: compute capability 7.0 or higher (e.g., V100, T4, RTX20xx, A100, etc.) | ||
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.. note:: | ||
As of now, CacheFlow does not support CUDA 12. | ||
If you are using Hopper or Lovelace GPUs, please use CUDA 11.8. | ||
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.. tip:: | ||
If you have trouble installing CacheFlow, we recommend using the NVIDIA PyTorch Docker image. | ||
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.. code-block:: console | ||
$ docker run --gpus all -it --rm --shm-size=8g nvcr.io/nvidia/pytorch:22.12-py3 | ||
Install with pip | ||
---------------- | ||
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You can install CacheFlow using pip: | ||
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.. code-block:: console | ||
$ # (Optional) Create a new conda environment. | ||
$ conda create -n myenv python=3.8 -y | ||
$ conda activate myenv | ||
$ # Install CacheFlow. | ||
$ pip install cacheflow | ||
.. _build_from_source: | ||
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Build from source | ||
----------------- | ||
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You can also build and install CacheFlow from source. | ||
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.. code-block:: console | ||
$ git clone https://github.com/WoosukKwon/cacheflow.git | ||
$ cd cacheflow | ||
$ pip install -r requirements.txt | ||
$ pip install -e . # This may take several minutes. | ||
$ pip install -e . # This may take 5-10 minutes. |