========= Reference ========= Computation graphs ================== .. automodule:: theanets.graph :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Network Feedforward networks ==================== .. automodule:: theanets.feedforward :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Autoencoder Classifier Regressor Recurrent networks ================== .. automodule:: theanets.recurrent :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Autoencoder Classifier Predictor Regressor Recurrent helpers ----------------- .. autosummary:: :toctree: generated/ batches Text Layer types =========== .. automodule:: theanets.layers.base :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ build Layer Feedforward layers ------------------ .. automodule:: theanets.layers.feedforward :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Classifier Feedforward Input Tied Convolution layers ------------------ .. automodule:: theanets.layers.convolution :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Convolution Conv1 Recurrent layers ---------------- .. automodule:: theanets.layers.recurrent :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Recurrent RNN ARRNN LRRNN GRU LSTM Clockwork MRNN Bidirectional Activations =========== .. automodule:: theanets.activations :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ build Activation Prelu LGrelu Maxout Training strategies =================== .. automodule:: theanets.trainer :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ DownhillTrainer SampleTrainer SupervisedPretrainer UnsupervisedPretrainer Drivers ======= .. automodule:: theanets.main :no-members: :no-inherited-members: .. autosummary:: :toctree: generated/ Experiment