# 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) ```