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v2.1.0

PaddlePaddle/Paddle

版本发布时间: 2021-05-19 14:44:29

PaddlePaddle/Paddle最新发布版本:v3.0.0-beta0(2024-06-27 18:00:34)

重要更新

飞桨框架2.1.0 版本有如下重要更新：

飞桨的官方模型库和套件的最新更新请参见：Paddle projects notes along with PaddlePaddle2.1。

不兼容升级

# will import nothing from the deeply nested namespaces
from paddle.nn.layer.loss import *
from paddle.nn.layer.conv import *
2.0 2.1 
>>> import paddle
>>> x = paddle.to_tensor(5., stop_gradient=False)
>>> y = paddle.pow(x, 4.0)
>>> y.backward()
>>> type(x.grad)
< class ‘numpy.ndarray’ >



>>> import paddle
>>> x = paddle.to_tensor(5., stop_gradient=False)
>>> y = paddle.pow(x, 4.0)
>>> y.backward()
>>> type(x.grad)
< class ‘paddle.Tensor’ >
2.0 2.1 
>>> import os
>>> import paddle
>>> from paddle.vision.models import resnet18

>>> model = resnet18()
>>> x = paddle.rand([1, 3, 224, 224])
>>> _, static_layer = paddle.jit.TracedLayer.trace(model, inputs=[x])
>>> save_path = './save_infer_model'
>>> static_layer.save_inference_model(dirname=save_path)

>>> print(os.path.isdir(save_path))
>>> print(len(os.listdir(save_path)))
True
103



>>> import os
>>> import paddle
>>> from paddle.vision.models import resnet18

>>> model = resnet18()
>>> x = paddle.rand([1, 3, 224, 224])
>>> _, static_layer = paddle.jit.TracedLayer.trace(model, inputs=[x])
>>> save_path = 'save_infer_model'
>>> static_layer.save_inference_model(path=save_path)

>>> print(os.path.isdir(save_path))
>>> print([name for name in os.listdir('./') if name.startswith(save_path)])
False
['save_infer_model.pdmodel', 'save_infer_model.pdiparams']
2.0 2.1 
>>> import numpy as np
>>> import paddle
>>> from paddle.io import DataLoader, Dataset
>>> 
>>> class RandomDataset(Dataset):
>>>     def __getitem__(self, idx):
>>>         return np.random.random((2, 3)).astype('float32')
>>> 
>>>     def __len__(self):
>>>         return 10
>>> 
>>> dataset = RandomDataset()
>>> loader = DataLoader(dataset, batch_size=1)
>>> data = next(loader())
>>> print(data)
[Tensor(shape=[1, 2, 3], dtype=float32, place=CUDAPinnedPlace, stop_gradient=True,
       [[[0.73782003, 0.62605530, 0.32727283],
         [0.37154925, 0.63570684, 0.53859973]]])]



>>> import numpy as np
>>> import paddle
>>> from paddle.io import DataLoader, Dataset
>>> 
>>> class RandomDataset(Dataset):
>>>     def __getitem__(self, idx):
>>>         return np.random.random((2, 3)).astype('float32')
>>> 
>>>     def __len__(self):
>>>         return 10
>>> 
>>> dataset = RandomDataset()
>>> loader = DataLoader(dataset, batch_size=1)
>>> data = next(loader())
>>> print(data)
Tensor(shape=[1, 2, 3], dtype=float32, place=CUDAPinnedPlace, stop_gradient=True,
       [[[0.73782003, 0.62605530, 0.32727283],
         [0.37154925, 0.63570684, 0.53859973]]])

训练框架

功能优化（含分布式）

基础API

2.0 2.1 
>>> from paddle.vision.models import resnet18
>>> model = resnet18()
>>> 
>>> print(len(model.sublayers(include_sublayers=True)))
>>> print(len(model.sublayers(include_sublayers=False)))
67
0



>>> from paddle.vision.models import resnet18
>>> model = resnet18()
>>> 
>>> print(len(model.sublayers(include_self=True)))
>>> print(len(model.sublayers(include_self=False)))
68
67

高层API

动态图转静态图

修复了动态图转静态图的bug：

混合精度训练

BF16训练

分布式训练优化

动态图混合并行

动态图分布式支持混合并行功能，支持数据并行，模型并行以及流水线并行三种并行方式的任意组合。同时支持混合并行基础上添加AMP混合精度策略，ReCompute策略。

自定义OP

模型保存与载入

性能优化（含分布式）

推理部署

模型量化

Paddle Inference

功能升级

性能优化

易用性优化

BugFix

环境适配

编译安装

新硬件训练支持

Thanks to our Contributors

This release contains contributions from:

123malin, Adam Osewski, alncat, arlesniak, AshburnLee, Aurelius84, Bai Yifan, Baibaifan, Bin Lu, cc, ceci3, chajchaj, chalsliu, channings, Chen Long, Chen Weihang, chen zhiyu, Chengmo, chentianyu03, cnn, CtfGo, cucuzg, danleifeng, denglin-github, Double_V, fangshuixun007, Feiyu Chan, fluffyrita, FlyingQianMM, FNRE, furnace, GaoWei8, GeminiCarrie, gongweibao, Gradie, GT-Zhang, Guanghua Yu, Guo Sheng, guofei, hong, houj04, huangjun12, huangxu96, Huihuang Zheng, hutuxian, iducn, Jacek Czaja, Jack Zhou, jakpiase, JamesLim, Jiabin Yang, jiangcheng, Jiaqi Liu, Jiawei Wang, joanna.wozna.intel, joejiong, JZ-LIANG, Kaipeng Deng, Kqnonrime, kuizhiqing, Lei.C, Leo Chen, lidanqing, LielinJiang, lijianshe02, lilong12, limingshu, littletomatodonkey, liu zhengxi, LiuChiachi, liuyuhui, liym27, LoveAn, LutaoChu, minghaoBD, mls1999725, niuliling123, Ouyang Chao, pangyoki, parap1uie-s, Pei Yang, procr, Qi Li, qingqing01, QingshuChen, Ren Wei (任卫), ronnywang, ruri, seemingwang, Shang Zhizhou, shanliang1992, ShenLiang, Shibo Tao, Steffy-zxf, syyxsxx, taixiurong, tangwei12, Tao Luo, Thomas Young, Thunderbrook, tianshuo78520a, TTerror, wangchaochaohu, wangguanzhong, wanghuancoder, wangna11BD, WangXi, wangxinxin08, wawltor, Wei Shengyu, weihaoji, WeiXin, wenbin, Wenyu, whs, Wilber, winter-wang, Wojciech Uss, wuhuanzhou, wuyefeilin, XGZhang, XiangGao, XiaoguangHu, xiaoting, xiegegege, xiemoyuan, xingfeng01, Yang Zhang, yaoxuefeng, yiak, yingshengBD, yinhaofeng, Yiqun Liu, ykkk2333, yongqiangma, Yuang Liu, yukavio, YUNSHEN XIE, Y_Xuan, Zhang Jun, Zhang Ting, zhang wenhui, Zhang Zheng, zhangchunle, Zhen Wang, zhiboniu, Zhong Hui, Zhou Wei, zhulei, zhupengyang, zlsh80826, 卖鱼的哲学, 石晓伟

PaddlePaddle 2.1.0 Release Note

Highlights

The PaddlePaddle Framework V2.1.0 has the following important updates:

For the latest updates to the official model libraries and suites of PaddlePaddle, please see: Paddle projects notes along with PaddlePaddle2.1.

Backwards Incompatible Changes

# will import nothing from the deeply nested namespaces
from paddle.nn.layer.loss import *
from paddle.nn.layer.conv import *
2.0 2.1 
>>> import paddle
>>> x = paddle.to_tensor(5., stop_gradient=False)
>>> y = paddle.pow(x, 4.0)
>>> y.backward()
>>> type(x.grad)
< class ‘numpy.ndarray’ >



>>> import paddle
>>> x = paddle.to_tensor(5., stop_gradient=False)
>>> y = paddle.pow(x, 4.0)
>>> y.backward()
>>> type(x.grad)
< class ‘paddle.Tensor’ >
2.0 2.1 
>>> import os
>>> import paddle
>>> from paddle.vision.models import resnet18

>>> model = resnet18()
>>> x = paddle.rand([1, 3, 224, 224])
>>> _, static_layer = paddle.jit.TracedLayer.trace(model, inputs=[x])
>>> save_path = './save_infer_model'
>>> static_layer.save_inference_model(dirname=save_path)

>>> print(os.path.isdir(save_path))
>>> print(len(os.listdir(save_path)))
True
103



>>> import os
>>> import paddle
>>> from paddle.vision.models import resnet18

>>> model = resnet18()
>>> x = paddle.rand([1, 3, 224, 224])
>>> _, static_layer = paddle.jit.TracedLayer.trace(model, inputs=[x])
>>> save_path = 'save_infer_model'
>>> static_layer.save_inference_model(path=save_path)

>>> print(os.path.isdir(save_path))
>>> print([name for name in os.listdir('./') if name.startswith(save_path)])
False
['save_infer_model.pdmodel', 'save_infer_model.pdiparams']
2.0 2.1 
>>> import numpy as np
>>> import paddle
>>> from paddle.io import DataLoader, Dataset
>>> 
>>> class RandomDataset(Dataset):
>>>     def __getitem__(self, idx):
>>>         return np.random.random((2, 3)).astype('float32')
>>> 
>>>     def __len__(self):
>>>         return 10
>>> 
>>> dataset = RandomDataset()
>>> loader = DataLoader(dataset, batch_size=1)
>>> data = next(loader())
>>> print(data)
[Tensor(shape=[1, 2, 3], dtype=float32, place=CUDAPinnedPlace, stop_gradient=True,
       [[[0.73782003, 0.62605530, 0.32727283],
         [0.37154925, 0.63570684, 0.53859973]]])]



>>> import numpy as np
>>> import paddle
>>> from paddle.io import DataLoader, Dataset
>>> 
>>> class RandomDataset(Dataset):
>>>     def __getitem__(self, idx):
>>>         return np.random.random((2, 3)).astype('float32')
>>> 
>>>     def __len__(self):
>>>         return 10
>>> 
>>> dataset = RandomDataset()
>>> loader = DataLoader(dataset, batch_size=1)
>>> data = next(loader())
>>> print(data)
Tensor(shape=[1, 2, 3], dtype=float32, place=CUDAPinnedPlace, stop_gradient=True,
       [[[0.73782003, 0.62605530, 0.32727283],
         [0.37154925, 0.63570684, 0.53859973]]])

Training Framework

Functional optimization (including distributed)

Basic API

2.0 2.1 
>>> from paddle.vision.models import resnet18
>>> model = resnet18()
>>> 
>>> print(len(model.sublayers(include_sublayers=True)))
>>> print(len(model.sublayers(include_sublayers=False)))
67
0



>>> from paddle.vision.models import resnet18
>>> model = resnet18()
>>> 
>>> print(len(model.sublayers(include_self=True)))
>>> print(len(model.sublayers(include_self=False)))
68
67

High-level API

Dynamic Graphs to Static Graphs

Fix the bug of dynamic graphs converted to static graphs.

Mixed Precision Training

BF16 Training

Distributed Training Optimization

Hybrid Parallelism with dynamic Graph

Support hybrid parallelism in the distributed dynamic graph mode, powered by data parallelism, model parallelism and pipeline parallelism, in addition, they can combine with AMP and the new ReCompute strategy to achieve better efficiency.

Custom OP

Model saving and loading

Performance optimization (including distributed)

Inference Deployment

Model Quantization

Paddle Inference

Function Upgrade

Performance Optimization

Ease-of-use optimization

BugFix

Environment Adaptation

Compile and install

New hardware training support

Thanks to our Contributors

This release contains contributions from:

123malin, Adam Osewski, alncat, arlesniak, AshburnLee, Aurelius84, Bai Yifan, Baibaifan, Bin Lu, cc, ceci3, chajchaj, chalsliu, channings, Chen Long, Chen Weihang, chen zhiyu, Chengmo, chentianyu03, cnn, CtfGo, cucuzg, danleifeng, denglin-github, Double_V, fangshuixun007, Feiyu Chan, fluffyrita, FlyingQianMM, FNRE, furnace, GaoWei8, GeminiCarrie, gongweibao, Gradie, GT-Zhang, Guanghua Yu, Guo Sheng, guofei, hong, houj04, huangjun12, huangxu96, Huihuang Zheng, hutuxian, iducn, Jacek Czaja, Jack Zhou, jakpiase, JamesLim, Jiabin Yang, jiangcheng, Jiaqi Liu, Jiawei Wang, joanna.wozna.intel, joejiong, JZ-LIANG, Kaipeng Deng, Kqnonrime, kuizhiqing, Lei.C, Leo Chen, lidanqing, LielinJiang, lijianshe02, lilong12, limingshu, littletomatodonkey, liu zhengxi, LiuChiachi, liuyuhui, liym27, LoveAn, LutaoChu, minghaoBD, mls1999725, niuliling123, Ouyang Chao, pangyoki, parap1uie-s, Pei Yang, procr, Qi Li, qingqing01, QingshuChen, Ren Wei (任卫), ronnywang, ruri, seemingwang, Shang Zhizhou, shanliang1992, ShenLiang, Shibo Tao, Steffy-zxf, syyxsxx, taixiurong, tangwei12, Tao Luo, Thomas Young, Thunderbrook, tianshuo78520a, TTerror, wangchaochaohu, wangguanzhong, wanghuancoder, wangna11BD, WangXi, wangxinxin08, wawltor, Wei Shengyu, weihaoji, WeiXin, wenbin, Wenyu, whs, Wilber, winter-wang, Wojciech Uss, wuhuanzhou, wuyefeilin, XGZhang, XiangGao, XiaoguangHu, xiaoting, xiegegege, xiemoyuan, xingfeng01, Yang Zhang, yaoxuefeng, yiak, yingshengBD, yinhaofeng, Yiqun Liu, ykkk2333, yongqiangma, Yuang Liu, yukavio, YUNSHEN XIE, Y_Xuan, Zhang Jun, Zhang Ting, zhang wenhui, Zhang Zheng, zhangchunle, Zhen Wang, zhiboniu, Zhong Hui, Zhou Wei, zhulei, zhupengyang, zlsh80826, 卖鱼的哲学, 石晓伟

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