Add Qwen2-audio example (#11835)
* add draft for qwen2-audio * update example for `Qwen2-Audio` * update * update * add warmup
This commit is contained in:
Ch1y0q
GitHub
parent
b11b28e9a9
commit
730d9ec811
3 changed files with 203 additions and 0 deletions
|
|
@ -276,6 +276,7 @@ Over 50 models have been optimized/verified on `ipex-llm`, including *LLaMA/LLaM
|
|||
| Qwen1.5 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen1.5) | [link](python/llm/example/GPU/HuggingFace/LLM/qwen1.5) |
|
||||
| Qwen2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen2) | [link](python/llm/example/GPU/HuggingFace/LLM/qwen2) |
|
||||
| Qwen-VL | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen-vl) | [link](python/llm/example/GPU/HuggingFace/Multimodal/qwen-vl) |
|
||||
| Qwen2-Audio | | [link](python/llm/example/GPU/HuggingFace/Multimodal/qwen2-audio) |
|
||||
| Aquila | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila) | [link](python/llm/example/GPU/HuggingFace/LLM/aquila) |
|
||||
| Aquila2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila2) | [link](python/llm/example/GPU/HuggingFace/LLM/aquila2) |
|
||||
| MOSS | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/moss) | |
|
||||
|
|
|
|||
|
|
@ -0,0 +1,127 @@
|
|||
# Qwen2-Audio
|
||||
In this directory, you will find examples on how you could apply IPEX-LLM INT4 optimizations on Qwen2-Audio models on [Intel GPUs](../../../README.md). For illustration purposes, we utilize [Qwen/Qwen2-Audio-7B-Instruct](https://huggingface.co/Qwen/Qwen2-Audio-7B-Instruct) as reference model.
|
||||
|
||||
## 0. Requirements
|
||||
To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../../../README.md#requirements) for more information.
|
||||
|
||||
|
||||
## Example: Predict Tokens using `generate()` API
|
||||
In the example [generate.py](./generate.py), we show a basic use case for a Qwen2-Audio model to conduct transcription using `processor` API, then use the recoginzed text as the input for Qwen2-Audio model to perform an English-Chinese translation using `generate()` API, with IPEX-LLM INT4 optimizations on Intel GPUs.
|
||||
### 1. Install
|
||||
|
||||
> [!NOTE]
|
||||
> Qwen2-Audio requires minimal `transformers` version of 4.35.0, which is not yet released. Currently, you can install the latest version of `transformers` from GitHub. When such a version is released, you can install it using `pip install transformers==4.35.0`.
|
||||
|
||||
#### 1.1 Installation on Linux
|
||||
We suggest using conda to manage environment:
|
||||
```bash
|
||||
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 librosa
|
||||
pip install git+https://github.com/huggingface/transformers
|
||||
```
|
||||
|
||||
#### 1.2 Installation on Windows
|
||||
We suggest using conda to manage environment:
|
||||
```bash
|
||||
conda create -n llm python=3.11 libuv
|
||||
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 librosa
|
||||
pip install git+https://github.com/huggingface/transformers
|
||||
```
|
||||
|
||||
### 2. Configures OneAPI environment variables for Linux
|
||||
|
||||
> [!NOTE]
|
||||
> Skip this step if you are running on Windows.
|
||||
|
||||
This is a required step on Linux for APT or offline installed oneAPI. Skip this step for PIP-installed oneAPI.
|
||||
|
||||
```bash
|
||||
source /opt/intel/oneapi/setvars.sh
|
||||
```
|
||||
|
||||
### 3. Runtime Configurations
|
||||
For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
|
||||
#### 3.1 Configurations for Linux
|
||||
<details>
|
||||
|
||||
<summary>For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series</summary>
|
||||
|
||||
```bash
|
||||
export USE_XETLA=OFF
|
||||
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
|
||||
export SYCL_CACHE_PERSISTENT=1
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
|
||||
<summary>For Intel Data Center GPU Max Series</summary>
|
||||
|
||||
```bash
|
||||
export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
|
||||
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
|
||||
export SYCL_CACHE_PERSISTENT=1
|
||||
export ENABLE_SDP_FUSION=1
|
||||
```
|
||||
> Note: Please note that `libtcmalloc.so` can be installed by `conda install -c conda-forge -y gperftools=2.10`.
|
||||
</details>
|
||||
|
||||
<details>
|
||||
|
||||
<summary>For Intel iGPU</summary>
|
||||
|
||||
```bash
|
||||
export SYCL_CACHE_PERSISTENT=1
|
||||
export BIGDL_LLM_XMX_DISABLED=1
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
#### 3.2 Configurations for Windows
|
||||
<details>
|
||||
|
||||
<summary>For Intel iGPU</summary>
|
||||
|
||||
```cmd
|
||||
set SYCL_CACHE_PERSISTENT=1
|
||||
set BIGDL_LLM_XMX_DISABLED=1
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
|
||||
<summary>For Intel Arc™ A-Series Graphics</summary>
|
||||
|
||||
```cmd
|
||||
set SYCL_CACHE_PERSISTENT=1
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
> [!NOTE]
|
||||
> For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile.
|
||||
### 4. Running examples
|
||||
|
||||
```
|
||||
python ./generate.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH
|
||||
```
|
||||
|
||||
Arguments info:
|
||||
- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Qwen2-Audio model (e.g. `Qwen/Qwen2-Audio-7B-Instruct`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'Qwen/Qwen2-Audio-7B-Instruct'`.
|
||||
|
||||
#### Sample Output
|
||||
In `generate.py`, [an audio clip](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/translate_to_chinese.wav) is used as the input, which asks the model to translate an English sentence into Chinese. The response from the model is expected to be similar to:
|
||||
```bash
|
||||
['每个人都希望被赏识，所以如果你欣赏某人，不要保密。']
|
||||
```
|
||||
|
|
@ -0,0 +1,75 @@
|
|||
#
|
||||
# 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.
|
||||
#
|
||||
|
||||
import argparse
|
||||
from io import BytesIO
|
||||
from urllib.request import urlopen
|
||||
import librosa
|
||||
import torch
|
||||
from transformers import Qwen2AudioForConditionalGeneration, AutoProcessor
|
||||
from ipex_llm import optimize_model
|
||||
|
||||
def main(args):
|
||||
model_path = args.repo_id_or_model_path
|
||||
max_length = args.max_length
|
||||
audio_url = args.audio_url
|
||||
|
||||
processor = AutoProcessor.from_pretrained(model_path)
|
||||
model = Qwen2AudioForConditionalGeneration.from_pretrained(model_path)
|
||||
model = optimize_model(model, low_bit='sym_int4', optimize_llm=True)
|
||||
model = model.half().to('xpu')
|
||||
|
||||
conversation = [
|
||||
{"role": "user", "content": [
|
||||
{"type": "audio", "audio_url": audio_url},
|
||||
]},
|
||||
]
|
||||
text = processor.apply_chat_template(conversation, add_generation_prompt=True, tokenize=False)
|
||||
audios = []
|
||||
for message in conversation:
|
||||
if isinstance(message["content"], list):
|
||||
for ele in message["content"]:
|
||||
if ele["type"] == "audio":
|
||||
audios.append(librosa.load(
|
||||
BytesIO(urlopen(ele['audio_url']).read()),
|
||||
sr=processor.feature_extractor.sampling_rate)[0]
|
||||
)
|
||||
|
||||
inputs = processor(text=text, audios=audios, return_tensors="pt", padding=True)
|
||||
inputs = inputs.to('xpu')
|
||||
|
||||
with torch.inference_mode():
|
||||
generate_ids = model.generate(**inputs, max_length=max_length) # warmup
|
||||
import time
|
||||
st = time.time()
|
||||
generate_ids = model.generate(**inputs, max_length=max_length)
|
||||
generate_ids = generate_ids[:, inputs.input_ids.size(1):]
|
||||
et = time.time()
|
||||
print(f'Inference time: {et-st} s')
|
||||
|
||||
response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)
|
||||
print(response)
|
||||
|
||||
if __name__=="__main__":
|
||||
parser = argparse.ArgumentParser(description="Qwen2-Audio")
|
||||
parser.add_argument('--repo-id-or-model-path', type=str, default="Qwen/Qwen2-Audio-7B-Instruct",
|
||||
help='The huggingface repo id for the Qwen2-Audio model checkpoint')
|
||||
parser.add_argument('--max-length', type=int, default=256,
|
||||
help='The max length of input text')
|
||||
parser.add_argument('--audio-url', type=str, default="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/translate_to_chinese.wav",
|
||||
help='The URL to the input audio file')
|
||||
args = parser.parse_args()
|
||||
main(args)
|
||||
Loading…
Reference in a new issue