API Reference

• Algorithms
  • Continuous control algorithms
  • Discrete control algorithms
• Q Functions
  • d3rlpy.q_functions.MeanQFunctionFactory
  • d3rlpy.q_functions.QRQFunctionFactory
  • d3rlpy.q_functions.IQNQFunctionFactory
  • d3rlpy.q_functions.FQFQFunctionFactory
• MDPDataset
  • d3rlpy.dataset.MDPDataset
  • d3rlpy.dataset.Episode
  • d3rlpy.dataset.Transition
  • d3rlpy.dataset.TransitionMiniBatch
• Datasets
  • d3rlpy.datasets.get_cartpole
  • d3rlpy.datasets.get_pendulum
  • d3rlpy.datasets.get_pybullet
  • d3rlpy.datasets.get_atari
• Preprocessing
  • d3rlpy.preprocessing.PixelScaler
  • d3rlpy.preprocessing.MinMaxScaler
  • d3rlpy.preprocessing.StandardScaler
• Optimizers
  • d3rlpy.optimizers.OptimizerFactory
  • d3rlpy.optimizers.SGDFactory
  • d3rlpy.optimizers.AdamFactory
  • d3rlpy.optimizers.RMSpropFactory
• Network Architectures
  • d3rlpy.encoders.DefaultEncoderFactory
  • d3rlpy.encoders.PixelEncoderFactory
  • d3rlpy.encoders.VectorEncoderFactory
  • d3rlpy.encoders.DenseEncoderFactory
• Data Augmentation
  • Image Observation
  • Vector Observation
  • Augmentation Pipeline
• Metrics
  • Algorithms
  • Dynamics
• Off-Policy Evaluation
  • For continuous control algorithms
  • For discrete control algorithms
• Save and Load
  • save_model and load_model
  • from_json
  • save_policy
• Logging
  • TensorBoard
• scikit-learn compatibility
  • train_test_split
  • cross_validate
  • GridSearchCV
  • parallel execution with multiple GPUs
• Online Training
  • Replay Buffer
  • Explorers
  • Iterators
• Model-based Data Augmentation
  • d3rlpy.dynamics.mopo.MOPO