Examples

Run all examples from this dir.

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DL notebooks

1. features – classification

   • cifar10 classification model

   • Runner usage example

2. features – segmentation

   • segmentation with unet

   • model training and inference

   • predictions visialization

3. tutorial – classification

   • dataset preparation (raw images -> train/valid/infer splits)

   • augmentations usage example

   • pretrained model finetuning

   • various classification metrics

   • metrics visualizaiton

   • FocalLoss and OneCycle usage examples

   • class imbalance handling

   • model inference

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DL pipelines

1. features – model training

   • configuration files usage example

   • local and docker runs

   • metrics visualization with tensorboard

2. features – model training with stages

   • pipeline example with stages

3. tutorial – classification pipeline

   • classification model training and inference

   • different augmentations and stages usage

   • knn index model example

   • embeddings projector

   • LrFinder usage

   • grid search metrics visualization

4. tutorial – autolabel - WIP

   • pseudolabeling for your dataset

5. tutorial – segmentation - WIP

6. tutorial – autounet - WIP

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RL pipelines

1. features – OpenAI Gym LunarLander

   • off-policy RL for continuous action space environment

   • DDPG, SAC, TD3 benchmark

   • async multi-cpu, multi-gpu training

2. features – Atari

   • off-policy RL for discrete action space environment

   • DQN

   • image-based environment with various wrappers

   • CNN-based agent with different distribution heads support

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CI tests

1. DL – Mnist with stages

2. RL – OpenAI Gym MountainCarContinuous