examples.rst

Examples

We list some examples here, but more tutorials and applications can be found in Github examples.

Commonly used dataset and pretrained models

• MNIST, see OpenI. or MNIST.
• CIFAR10, see OpenI. or CIFAR10.
• YOLOv4 Pretrained Model, see OpenI. or Baidu. password: idsz
• VGG16 Pretrained Model, see OpenI. or Baidu. password: t36u
• VGG19 Pretrained Model, see OpenI. or Baidu. password: rb8w
• ResNet50 Pretrained Model, see OpenI. or Baidu. password: 3nui

Basics

• Multi-layer perceptron (MNIST), simple usage and supports multiple backends. Classification task, see mnist_mlp.py.
• Generative Adversarial Networks (MNIST), simple usage and supports multiple backends. See mnist_gan.py.
• Convolutional Network (CIFAR-10), simple usage and supports multiple backends. Classification task, see cifar10_cnn.py.
• Recurrent Neural Network (IMDB), simple usage and supports multiple backends. Text classification task, see imdb_LSTM_simple.py.
• Using tensorlayerx to automatic inference input shape. See automatic_inference_input _shape.py.
• Using ModuleList in tensorlayerx. See tutorial_ModuleList.py.
• Using Sequential in tensorlayerx. See mnist_Sequential.py.
• Using Dataflow in tensorlayerx. See mnist_dataflow.py.
• Using nested layer in tensorlayerx. See nested_usage_of_layer.py.
• Using tensorlayerx to save tensorflow model to pb. See tensorflow_model_save_to_pb.py.
• Using tensorlayerx to load model from npz. See tutorial_tensorlayer_model_load.py.

Pretrained Models

• VGG 16 (ImageNet). Classification task demo, see pretrained_vgg16. and VGG model, see vgg.py.
• Resnet50 (ImageNet). Classification task demo, see pretrained_resnet50.py. and Resnet model, see resnet.py.
• YOLOv4 (MS-COCO). Object Detection demo, see pretrained_yolov4.py. and YOLOv4 model, see yolo.py.
• All pretrained models in pretrained-models.

Vision

Warning:These examples below only support Tensorlayer 2.0. TensorlayerX is under development.

• Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization, see examples.
• ArcFace: Additive Angular Margin Loss for Deep Face Recognition, see InsignFace.
• BinaryNet. Model compression, see mnist cifar10.
• Ternary Weight Network. Model compression, see mnist cifar10.
• DoReFa-Net. Model compression, see mnist cifar10.
• QuanCNN. Model compression, sees mnist cifar10.
• Wide ResNet (CIFAR) by ritchieng.
• Spatial Transformer Networks by zsdonghao.
• U-Net for brain tumor segmentation by zsdonghao.
• Variational Autoencoder (VAE) for (CelebA) by yzwxx.
• Variational Autoencoder (VAE) for (MNIST) by BUPTLdy.
• Image Captioning - Reimplementation of Google's im2txt by zsdonghao.

Adversarial Learning

Warning:These examples below only support Tensorlayer 2.0. TensorlayerX is under development.

• DCGAN (CelebA). Generating images by Deep Convolutional Generative Adversarial Networks by zsdonghao.
• Generative Adversarial Text to Image Synthesis by zsdonghao.
• Unsupervised Image to Image Translation with Generative Adversarial Networks by zsdonghao.
• Improved CycleGAN with resize-convolution by luoxier.
• Super Resolution GAN by zsdonghao.
• BEGAN: Boundary Equilibrium Generative Adversarial Networks by 2wins.
• DAGAN: Fast Compressed Sensing MRI Reconstruction by nebulaV.

Natural Language Processing

Warning:These examples below only support Tensorlayer 2.0. TensorlayerX is under development.

• Word Embedding (Word2vec). Train a word embedding matrix, see tutorial_word2vec_basic.py.
• Restore Embedding matrix. Restore a pre-train embedding matrix, see tutorial_generate_text.py.
• Text Generation. Generates new text scripts, using LSTM network, see tutorial_generate_text.py.
• Chinese Text Anti-Spam by pakrchen.
• Chatbot in 200 lines of code for Seq2Seq.
• FastText Sentence Classification (IMDB), see tutorial_imdb_fasttext.py by tomtung.

Reinforcement Learning

Warning:These examples below only support Tensorlayer 2.0. TensorlayerX is under development.

• Policy Gradient / Network (Atari Ping Pong), see tutorial_atari_pong.py.
• Deep Q-Network (Frozen lake), see tutorial_frozenlake_dqn.py.
• Q-Table learning algorithm (Frozen lake), see tutorial_frozenlake_q_table.py.
• Asynchronous Policy Gradient using TensorDB (Atari Ping Pong) by nebulaV.
• AC for discrete action space (Cartpole), see tutorial_cartpole_ac.py.
• A3C for continuous action space (Bipedal Walker), see tutorial_bipedalwalker_a3c*.py.
• DAGGER for (Gym Torcs) by zsdonghao.
• TRPO for continuous and discrete action space by jjkke88.

Miscellaneous

Warning:These examples below only support Tensorlayer 2.0. TensorlayerX is under development.

• Sipeed : Run TensorLayer on AI Chips