深度学习100+经典模型TensorFlow与Pytorch代码实现大合集

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【导读】深度学习在过去十年获得了极大进展，出现很多新的模型，并且伴随TensorFlow和Pytorch框架的出现，有很多实现，但对于初学者和很多从业人员，如何选择合适的实现，是个选择。rasbt大神在Github上整理了关于深度学习模型TensorFlow和Pytorch代码实现集合，含有100个，各种各样的深度学习架构，模型，和技巧的集合Jupyter Notebooks，从基础的逻辑回归到神经网络到CNN到GNN等，可谓一网打尽，值得收藏！

地址：https://github.com/rasbt/deeplearning-models

传统机器学习

• 感知器 Perceptron
     [TensorFlow 1: GitHub | Nbviewer]

  https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/basic-ml/perceptron.ipynb
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/perceptron.ipynb

• 逻辑回归 Logistic Regression
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/basic-ml/logistic-regression.ipynb
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/logistic-regression.ipynb

• Softmax Regression (Multinomial Logistic Regression)
     [TensorFlow 1: GitHub | Nbviewer]

  https://github.com/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/basic-ml/softmax-regression.ipynb
     [PyTorch: GitHub | Nbviewer]

  https://github.com/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/softmax-regression.ipynb

• Softmax Regression with MLxtend's plot_decision_regions on Iris
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/basic-ml/softmax-regression-mlxtend-1.ipynb

多层感知器

• 多层感知器 Multilayer Perceptron
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/mlp/mlp-basic.ipynb
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/mlp/mlp-basic.ipynb

• 带Dropout的多层感知器 Multilayer Perceptron with Dropout
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

• 具有批处理规范化的多层感知器 Multilayer Perceptron with Batch Normalization
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

• Multilayer Perceptron with Backpropagation from Scratch
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

卷积神经网络

基础

• 卷积神经网络 Convolutional Neural Network
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/cnn/cnn-basic.ipynb
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-basic.ipynb

• Convolutional Neural Network with He Initialization
     [PyTorch: GitHub | Nbviewer]

Concepts

• Replacing Fully-Connnected by Equivalent Convolutional Layers
     [PyTorch: GitHub | Nbviewer]

Fully Convolutional

• Fully Convolutional Neural Network
     [PyTorch: GitHub | Nbviewer]

LeNet

• LeNet-5 on MNIST
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-lenet5-mnist.ipynb

• LeNet-5 on CIFAR-10
     [PyTorch: GitHub | Nbviewer]

• LeNet-5 on QuickDraw
     [PyTorch: GitHub | Nbviewer]

AlexNet

• AlexNet on CIFAR-10
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-alexnet-cifar10.ipynb

VGG

• Convolutional Neural Network VGG-16
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/cnn/cnn-vgg16.ipynb
     [PyTorch: GitHub | Nbviewer]

• VGG-16 Gender Classifier Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

• Convolutional Neural Network VGG-19
     [PyTorch: GitHub | Nbviewer]

DenseNet

• DenseNet-121 Digit Classifier Trained on MNIST
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/cnn-densenet121-mnist.ipynb

• DenseNet-121 Image Classifier Trained on CIFAR-10
     [PyTorch: GitHub | Nbviewer]

ResNet

• ResNet and Residual Blocks
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/resnet-ex-1.ipynb

• ResNet-18 Digit Classifier Trained on MNIST
     [PyTorch: GitHub | Nbviewer]

• ResNet-18 Gender Classifier Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

• ResNet-34 Digit Classifier Trained on MNIST
     [PyTorch: GitHub | Nbviewer]

• ResNet-34 Object Classifier Trained on QuickDraw
     [PyTorch: GitHub | Nbviewer]

• ResNet-34 Gender Classifier Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

• ResNet-50 Digit Classifier Trained on MNIST
     [PyTorch: GitHub | Nbviewer]

• ResNet-50 Gender Classifier Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

• ResNet-101 Gender Classifier Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

• ResNet-101 Trained on CIFAR-10
     [PyTorch: GitHub | Nbviewer]

• ResNet-152 Gender Classifier Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

Network in Network

• Network in Network CIFAR-10 Classifier
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/nin-cifar10.ipynb

归一化层 Normalization Layers

• BatchNorm before and after Activation for Network-in-Network CIFAR-10 Classifier
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/cnn/nin-cifar10_batchnorm.ipynb

• Filter Response Normalization for Network-in-Network CIFAR-10 Classifier
     [PyTorch: GitHub | Nbviewer]

 度量学习 Metric Learning

• Siamese Network with Multilayer Perceptrons
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/metric/siamese-1.ipynb

自编码器 Autoencoders

全连接自编码器 Fully-connected Autoencoders

• Autoencoder (MNIST)
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/autoencoder/ae-basic.ipynb
     [PyTorch: GitHub | Nbviewer]

• Autoencoder (MNIST) + Scikit-Learn Random Forest Classifier
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

Convolutional Autoencoders

• Convolutional Autoencoder with Deconvolutions / Transposed Convolutions
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

• Convolutional Autoencoder with Deconvolutions and Continuous Jaccard Distance
     [PyTorch: GitHub | Nbviewer]

• Convolutional Autoencoder with Deconvolutions (without pooling operations)
     [PyTorch: GitHub | Nbviewer]

• Convolutional Autoencoder with Nearest-neighbor Interpolation
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

• Convolutional Autoencoder with Nearest-neighbor Interpolation -- Trained on CelebA
     [PyTorch: GitHub | Nbviewer]

• Convolutional Autoencoder with Nearest-neighbor Interpolation -- Trained on Quickdraw
     [PyTorch: GitHub | Nbviewer]

Variational Autoencoders

• Variational Autoencoder
     [PyTorch: GitHub | Nbviewer]

• Convolutional Variational Autoencoder
     [PyTorch: GitHub | Nbviewer]

Conditional Variational Autoencoders

• Conditional Variational Autoencoder (with labels in reconstruction loss)
     [PyTorch: GitHub | Nbviewer]

• Conditional Variational Autoencoder (without labels in reconstruction loss)
     [PyTorch: GitHub | Nbviewer]

• Convolutional Conditional Variational Autoencoder (with labels in reconstruction loss)
     [PyTorch: GitHub | Nbviewer]

• Convolutional Conditional Variational Autoencoder (without labels in reconstruction loss)
     [PyTorch: GitHub | Nbviewer]

 生成式对抗网络 Generative Adversarial Networks (GANs)

• Fully Connected GAN on MNIST
     [TensorFlow 1: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/tensorflow1_ipynb/gan/gan.ipynb
     [PyTorch: GitHub | Nbviewer]

• Fully Connected Wasserstein GAN on MNIST
     [PyTorch: GitHub | Nbviewer]

• Convolutional GAN on MNIST
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

• Convolutional GAN on MNIST with Label Smoothing
     [TensorFlow 1: GitHub | Nbviewer]
     [PyTorch: GitHub | Nbviewer]

• Convolutional Wasserstein GAN on MNIST
     [PyTorch: GitHub | Nbviewer]

 图神经网络 Graph Neural Networks (GNNs)

• Most Basic Graph Neural Network with Gaussian Filter on MNIST
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/gnn/gnn-basic-1.ipynb

• Basic Graph Neural Network with Edge Prediction on MNIST
     [PyTorch: GitHub | Nbviewer]

• Basic Graph Neural Network with Spectral Graph Convolution on MNIST
     [PyTorch: GitHub | Nbviewer]

循环神经网络 Recurrent Neural Networks (RNNs)

Many-to-one: Sentiment Analysis / Classification

• A simple single-layer RNN (IMDB)
     [PyTorch: GitHub | Nbviewer]

  https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/rnn/rnn_simple_imdb.ipynb

• A simple single-layer RNN with packed sequences to ignore padding characters (IMDB)
     [PyTorch: GitHub | Nbviewer]

• RNN with LSTM cells (IMDB)
     [PyTorch: GitHub | Nbviewer]

• RNN with LSTM cells (IMDB) and pre-trained GloVe word vectors
     [PyTorch: GitHub | Nbviewer]

• RNN with LSTM cells and Own Dataset in CSV Format (IMDB)
     [PyTorch: GitHub | Nbviewer]

• RNN with GRU cells (IMDB)
     [PyTorch: GitHub | Nbviewer]

• Multilayer bi-directional RNN (IMDB)
     [PyTorch: GitHub | Nbviewer]

• Bidirectional Multi-layer RNN with LSTM with Own Dataset in CSV Format (AG News)
     [PyTorch: GitHub | Nbviewer]

• Bidirectional Multi-layer RNN with LSTM with Own Dataset in CSV Format (Yelp Review Polarity)
     [PyTorch: GitHub | Nbviewer]

• Bidirectional Multi-layer RNN with LSTM with Own Dataset in CSV Format (Amazon Review Polarity)
     [PyTorch: GitHub | Nbviewer]

Many-to-Many / Sequence-to-Sequence

• A simple character RNN to generate new text (Charles Dickens)
     [PyTorch: GitHub | Nbviewer]

Ordinal Regression

• Ordinal Regression CNN -- CORAL w. ResNet34 on AFAD-Lite
     [PyTorch: GitHub | Nbviewer]

• Ordinal Regression CNN -- Niu et al. 2016 w. ResNet34 on AFAD-Lite
     [PyTorch: GitHub | Nbviewer]

• Ordinal Regression CNN -- Beckham and Pal 2016 w. ResNet34 on AFAD-Lite
     [PyTorch: GitHub | Nbviewer]

Tips and Tricks

• Cyclical Learning Rate
     [PyTorch: GitHub | Nbviewer]

• Annealing with Increasing the Batch Size (w. CIFAR-10 & AlexNet)
     [PyTorch: GitHub | Nbviewer]

• Gradient Clipping (w. MLP on MNIST)
     [PyTorch: GitHub | Nbviewer]

 迁移学习 Transfer Learning

• Transfer Learning Example (VGG16 pre-trained on ImageNet for Cifar-10)

   [PyTorch: GitHub | Nbviewer

https://nbviewer.jupyter.org/github/rasbt/deeplearning-models/blob/master/pytorch_ipynb/transfer/transferlearning-vgg16-cifar10-1.ipynb

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