Awesome
Some Pretrained Models for TensorLayer
Feel free to add more.This repository is implemented with TensorLayer2.0+.
Reinforcement Learning Examples
./rl_models/ contains pretrained models for each algorithm in reinforcement learning examples.
CNN for ImageNet
The tl.models API description here, and the discussion for network architecture that can be easily use here.
| Model | Code | Parameter | Top-1 Accuracy | Top-5 Accuracy |
|---|---|---|---|---|
| VGG 16 | code | model | 71.5 | 89.8 |
| VGG 19 | code | model (from machrisaa/tensorflow-vgg) | 71.1 | 89.8 |
| ResNet V1 50 | 75.2 | 92.2 | ||
| ResNet V1 101 | resnet_v1_101_2016_08_28.tar.gz | 76.4 | 92.9 | |
| ResNet V1 152 | resnet_v1_152_2016_08_28.tar.gz | 76.8 | 93.2 | |
| ResNet V2 50 | resnet_v2_50_2017_04_14.tar.gz | 75.6 | 92.8 | |
| ResNet V2 101 | resnet_v2_101_2017_04_14.tar.gz | 77.0 | 93.7 | |
| ResNet V2 152 | resnet_v2_152_2017_04_14.tar.gz | 77.8 | 94.1 | |
| ResNet V2 200 | TBA | 79.9* | 95.2* | |
| Inception V1 | inception_v1_2016_08_28.tar.gz | 69.8 | 89.6 | |
| Inception V2 | inception_v2_2016_08_28.tar.gz | 73.9 | 91.8 | |
| Inception V3 | code | inception_v3_2016_08_28.tar.gz | 78.0 | 93.9 |
| Inception V4 | 80.2 | 95.2 | ||
| Xception | ||||
| Inception-ResNet-v2 | 80.4 | 95.3 | ||
| SqueezeNet V1 | code | model | ||
| SqueezeNet V2 | ||||
| MobileNet V1 | code | model | ||
| MobileNet V2_1.4_224 | 74.9 | 92.5 | ||
| MobileNet V2_1.0_224 | 71.9 | 91.0 | ||
| NASNet-A_Mobile_224 | nasnet-a_mobile_04_10_2017.tar.gz | 74.0 | 91.6 | |
| NASNet-A_Large_331 | nasnet-a_large_04_10_2017.tar.gz | 82.7 | 96.2 | |
| PNASNet-5_Large_331 | pnasnet-5_large_2017_12_13.tar.gz | 82.9 | 96.2 | |
| DenseNet | ||||
| NASNet |
More examples in Awesome-TensorLayer