本篇文章译自英文文档 Compile PaddlePaddle Models tvm 0.14.dev0 documentation
作者是 ZiyuanMa (Ziyuan Ma) · GitHub
更多 TVM 中文文档可访问 →Apache TVM 是一个端到端的深度学习编译框架，适用于 CPU、GPU 和各种机器学习加速芯片。 | Apache TVM 中文站
本文介绍如何用 Relay 部署 PaddlePaddle 模型，首先安装 PaddlePaddle（版本>=2.1.3），可通过 pip 快速安装：
pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
或参考官方网站：
https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html
import tarfile
import paddle
import numpy as np
import tvm
from tvm import relay
from tvm.contrib.download import download_testdata
输出结果：
/usr/local/lib/python3.7/dist-packages/paddle/vision/transforms/functional_pil.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.'nearest': Image.NEAREST,
/usr/local/lib/python3.7/dist-packages/paddle/vision/transforms/functional_pil.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.'bilinear': Image.BILINEAR,
/usr/local/lib/python3.7/dist-packages/paddle/vision/transforms/functional_pil.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.'bicubic': Image.BICUBIC,
/usr/local/lib/python3.7/dist-packages/paddle/vision/transforms/functional_pil.py:39: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.'box': Image.BOX,
/usr/local/lib/python3.7/dist-packages/paddle/vision/transforms/functional_pil.py:40: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.'lanczos': Image.LANCZOS,
/usr/local/lib/python3.7/dist-packages/paddle/vision/transforms/functional_pil.py:41: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.'hamming': Image.HAMMING
加载预训练的 ResNet50 模型
加载 PaddlePaddle 提供的 ResNet50 预训练模型：
url = "https://bj.bcebos.com/x2paddle/models/paddle_resnet50.tar"
model_path = download_testdata(url, "paddle_resnet50.tar", module="model")with tarfile.open(model_path) as tar:names = tar.getnames()for name in names:tar.extract(name, "./")model = paddle.jit.load("./paddle_resnet50/model")
输出结果：
/usr/local/lib/python3.7/dist-packages/paddle/fluid/backward.py:1666: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop workingreturn list(x) if isinstance(x, collections.Sequence) else [x]
加载测试图像
还是用猫的图像：
from PIL import Image
import paddle.vision.transforms as Ttransforms = T.Compose([T.Resize((256, 256)),T.CenterCrop(224),T.ToTensor(),T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),]
)img_url = "https://github.com/dmlc/mxnet.js/blob/main/data/cat.png?raw=true"
img_path = download_testdata(img_url, "cat.png", module="data")
img = Image.open(img_path).resize((224, 224))img = transforms(img)
img = np.expand_dims(img, axis=0)
使用 Relay 编译模型
target = "llvm"
shape_dict = {"inputs": img.shape}
mod, params = relay.frontend.from_paddle(model, shape_dict)with tvm.transform.PassContext(opt_level=3):executor = relay.build_module.create_executor("graph", mod, tvm.cpu(0), target, params).evaluate()
输出结果：
/workspace/python/tvm/driver/build_module.py:268: UserWarning: target_host parameter is going to be deprecated. Please pass in tvm.target.Target(target, host=target_host) instead."target_host parameter is going to be deprecated. "
在 TVM 上执行
dtype = "float32"
tvm_output = executor(tvm.nd.array(img.astype(dtype))).numpy()
查找分类集名称
在 1000 个类的分类集中，查找分数最高的第一个：
synset_url = "".join(["https://gist.githubusercontent.com/zhreshold/","4d0b62f3d01426887599d4f7ede23ee5/raw/","596b27d23537e5a1b5751d2b0481ef172f58b539/","imagenet1000_clsid_to_human.txt",]
)
synset_name = "imagenet1000_clsid_to_human.txt"
synset_path = download_testdata(synset_url, synset_name, module="data")
with open(synset_path) as f:synset = f.readlines()top1 = np.argmax(tvm_output[0])
print(f"TVM prediction top-1 id: {top1}, class name: {synset[top1]}")
输出结果：
TVM prediction top-1 id: 282, class name: 282: 'tiger cat',
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