Update guide for running qwen with AutoTP (#11065)

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binbin Deng 2024-05-20 10:53:17 +08:00 committed by GitHub
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@ -86,6 +86,8 @@ IPEX-LLM currently supports the Ubuntu 20.04 operating system and later, and sup
libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \
mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo
sudo apt install -y intel-i915-dkms intel-fw-gpu
sudo reboot
```

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@ -8,6 +8,10 @@ To run this example with IPEX-LLM on Intel GPUs, we have some recommended requir
## Example:
### 0. Prerequisites
Please visit the [Install IPEX-LLM on Linux with Intel GPU](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html), follow [Install Intel GPU Driver](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html#install-intel-gpu-driver) and [Install oneAPI](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html#install-oneapi) to install GPU driver and Intel® oneAPI Base Toolkit 2024.0.
### 1. Install
```bash
@ -15,6 +19,7 @@ conda create -n llm python=3.11
conda activate llm
# below command will install intel_extension_for_pytorch==2.1.10+xpu as default
pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
pip install transformers==4.37.0
pip install oneccl_bind_pt==2.1.100 --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
# configures OneAPI environment variables
source /opt/intel/oneapi/setvars.sh
@ -49,6 +54,14 @@ bash run_vicuna_33b_arc_2_card.sh
> **Note**: You could change `NUM_GPUS` to the number of GPUs you have on your machine. And you could also specify other low bit optimizations through `--low-bit`.
- Run Qwen1.5-14B-Chat on two Intel Arc A770
```bash
bash run_qwen_14b_arc_2_card.sh
```
> **Note**: You could change `NUM_GPUS` to the number of GPUs you have on your machine. And you could also specify other low bit optimizations through `--low-bit`.
- Run Mistral-7B-Instruct on two cards of Intel Data Center GPU Flex
```bash
@ -69,7 +82,7 @@ bash run_mistral_7b_instruct_flex_2_card.sh
[0] One day, she decided to go on a journey to find the legendary
```
**Important**: The first token latency is much larger than rest token latency, you could use [our benchmark tool](https://github.com/intel-analytics/ipex-llm/blob/main/python/llm/dev/benchmark/README.md) to obtain more details about first and rest token latency.
**Important**: To obtain more details about performance, please use [our benchmark tool](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/dev/benchmark/all-in-one). You need to specify `test_api` as `"deepspeed_optimize_model_gpu"`, and modify other configurations based on your requirement in `config.yaml`. Then just run `run-deepspeed-arc.sh` or `run-deepspeed-pvc.sh` according to your device to collect performance data.
### Known Issue

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@ -0,0 +1,38 @@
#
# Copyright 2016 The BigDL Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
## Validated BKC for Qwen1.5-14B-Chat on 2 ARC with
## Ubuntu 22.04.4, kernel 6.5.0-27-generic, level-zero 1.14.0, NEO(compute runtime) 24.09.28717.12
export MASTER_ADDR=127.0.0.1
export FI_PROVIDER=tcp
export CCL_ATL_TRANSPORT=ofi
export CCL_ZE_IPC_EXCHANGE=sockets
export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so:${LD_PRELOAD}
basekit_root=/opt/intel/oneapi
source $basekit_root/setvars.sh --force
source $basekit_root/ccl/latest/env/vars.sh --force
NUM_GPUS=2 # number of used GPU
export USE_XETLA=OFF
if grep -q "Core" /proc/cpuinfo; then
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=2
fi
export TORCH_LLM_ALLREDUCE=0 # Different from PVC
mpirun -np $NUM_GPUS --prepend-rank \
python deepspeed_autotp.py --repo-id-or-model-path 'Qwen/Qwen1.5-14B-Chat' --low-bit 'sym_int4'