# oneflow-models
**Repository Path**: gangbai/oneflow-models
## Basic Information
- **Project Name**: oneflow-models
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: AutoParallel/test_model
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-12-15
- **Last Updated**: 2021-12-15
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# OneFlow-Models
**本仓库包含了基于最新OneFlow(version >= 0.5.0)实现的主流深度学习模型**
## Introduction
[English](/README.md) | **简体中文**
OneFlow-Models目录下提供了各种经典图形分类、目标检测、图像分割、对抗生成网络、自然语言处理、强化学习、量化感知学习以及语音模型的官方实现。对于每个模型,我们同时提供了模型的定义、训练以及推理的代码。并且对于每个模型,我们至少提供两个脚本`train.sh`和`infer.sh`,分别对应模型的训练和推理,便于使用者快速上手。并且保证该仓库适配OneFlow最新的API,同时提供优质的模型实现。并且与此同时我们会提供详细且高质量的学习文档,帮助使用者能够快速入手OneFlow。
## 主要特性
- 提供丰富的模型实现
- 提供对应预训练模型
- 便于上手,简单易用
## 快速上手
欢迎体验OneFlow的入门Demo
- **图像分类:** [LeNet](Demo/quick_start_demo_lenet/lenet.py)
- **说话人识别:** [Speaker Identification](Demo/speaker_identification_demo)
## 模型目录
图像分类
- [Lenet](https://github.com/Oneflow-Inc/models/blob/main/Demo/quick_start_demo_lenet/lenet.py)
- [Alexnet](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/alexnet)
- [VGG16/19](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/vgg)
- [Resnet50](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/resnet50)
- [InceptionV3](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/inception_v3)
- [Densenet](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/densenet)
- [Resnext50_32x4d](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/resnext50_32x4d)
- [Shufflenetv2](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/shufflenetv2)
- [MobilenetV2](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/mobilenetv2)
- [mobilenetv3](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/mobilenetv3)
- [Ghostnet](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/ghostnet)
- [RepVGG](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/repvgg)
- [DLA](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/DLA)
- [PoseNet](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/poseNet)
- [Scnet](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/scnet)
- [Mnasnet](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/mnasnet)
- [ViT](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/image/ViT)
视频分类
- [TSN](https://github.com/Oneflow-Inc/models/tree/main/Vision/classification/video/TSN)
目标检测
- [CSRNet](https://github.com/Oneflow-Inc/models/tree/main/Vision/detection/CSRNet)
语义分割
- [FODDet](https://github.com/Oneflow-Inc/models/tree/main/Vision/segmentation/FODDet)
- [FaceSeg](https://github.com/Oneflow-Inc/models/tree/main/Vision/segmentation/FaceSeg)
对抗生成网络
- [DCGAN](https://github.com/Oneflow-Inc/models/tree/main/Vision/gan/DCGAN)
- [SRGAN](https://github.com/Oneflow-Inc/models/tree/main/Vision/gan/SRGAN)
- [Pix2Pix](https://github.com/Oneflow-Inc/models/tree/main/Vision/gan/Pix2Pix)
- [CycleGAN](https://github.com/Oneflow-Inc/models/tree/main/Vision/gan/CycleGAN)
图像风格迁移
- [FastNeuralStyle](https://github.com/Oneflow-Inc/models/tree/main/Vision/style_transform/fast_neural_style)
行人重识别
- [BoT](https://github.com/Oneflow-Inc/models/tree/main/Vision/reid/BoT)
自然语言处理
- [RNN](https://github.com/Oneflow-Inc/models/tree/main/NLP/rnn)
- [Seq2Seq](https://github.com/Oneflow-Inc/models/tree/main/NLP/seq2seq)
- [LSTMText](https://github.com/Oneflow-Inc/models/tree/main/NLP/LSTMText)
- [TextCNN](https://github.com/Oneflow-Inc/models/tree/main/NLP/TextCNN)
- [Transformer](https://github.com/Oneflow-Inc/models/tree/main/NLP/Transformer)
- [Bert](https://github.com/Oneflow-Inc/models/tree/main/NLP/bert-oneflow)
- [CPT](https://github.com/Oneflow-Inc/models/tree/main/NLP/CPT)
语音
- [SincNet](https://github.com/Oneflow-Inc/models/tree/main/Audio/SincNet)
- [Wav2Letter](https://github.com/Oneflow-Inc/models/tree/main/Audio/Wav2Letter)
- [AM_MobileNet1D](https://github.com/Oneflow-Inc/models/tree/main/Audio/AM-MobileNet1D)
- [Speech-Emotion-Analyer](https://github.com/Oneflow-Inc/models/tree/main/Audio/Speech-Emotion-Analyzer)
- [Speech-Transformer](https://github.com/Oneflow-Inc/models/tree/main/Audio/Speech-Transformer)
- [CycleGAN-VC2](https://github.com/Oneflow-Inc/models/tree/main/Audio/CycleGAN-VC2)
- [MaskCycleGAN-VC](https://github.com/Oneflow-Inc/models/tree/main/Audio/MaskCycleGAN-VC)
- [StarGAN-VC](https://github.com/Oneflow-Inc/models/tree/main/Audio/StarGAN-VC)
- [Adaptive_Voice_Conversion](https://github.com/Oneflow-Inc/models/tree/main/Audio/Adaptive_Voice_Conversion)
深度强化学习
- [FlappyBird](https://github.com/Oneflow-Inc/models/tree/main/DeepReinforcementLearning/FlappyBird)
量化感知学习
- [Quantization](https://github.com/Oneflow-Inc/models/tree/main/Quantization)
## 安装与环境配置
**安装最新的OneFlow**
https://github.com/Oneflow-Inc/oneflow#install-with-pip-package
**环境配置**
在根目录下执行以下命令即可调用一些定制化的算子:
```bash
mkdir build
cd build
cmake ..
make -j$(nrpoc)
```
使用示例:
```bash
from ops import RoIAlign
pooler = RoIAlign(output_size=(14, 14), spatial_scale=2.0, sampling_ratio=2)
```