Index _ | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W _ __init__() (AdaptiveDecompSettings method), [1] (AdaptiveDecompTransformer method), [1] (ClassifierMessage method), [1] (IncrementalCCA method), [1] (IncrementalDecompSettings method), [1] (IncrementalPCASettings method), [1] (MiniBatchNMFSettings method), [1] (MLP method), [1] (RefitKalmanFilter method), [1] (RNNModel method), [1] (TransformerModel method), [1] A A_state_transition_matrix (RefitKalmanFilter attribute), [1] ADAPTIVE (RegressorType attribute), [1] AdaptiveDecompSettings (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] AdaptiveDecompState (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] AdaptiveDecompTransformer (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] AdaptiveLinearRegressor (class in ezmsg.learn.util), [1] alpha_H (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] alpha_W (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] attention_heads (TransformerModel attribute), [1] attrs (ClassifierMessage attribute) axes (ClassifierMessage attribute) axis (AdaptiveDecompSettings attribute), [1] (IncrementalDecompSettings attribute), [1] axis_groups (AdaptiveDecompState attribute), [1] B BaseAdaptiveDecompUnit (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] batch_size (IncrementalDecompSettings attribute), [1] (IncrementalPCASettings attribute), [1] (MiniBatchNMFSettings attribute), [1] beta_loss (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] C ClassifierMessage (class in ezmsg.learn.util), [1] D data (ClassifierMessage attribute) decoder_layers (TransformerModel attribute), [1] dims (ClassifierMessage attribute) dropout (RNNModel attribute), [1] (TransformerModel attribute), [1] E encoder_layers (TransformerModel attribute), [1] estimator (AdaptiveDecompState attribute), [1] ezmsg.learn.dim_reduce.adaptive_decomp module ezmsg.learn.dim_reduce.incremental_decomp module ezmsg.learn.linear_model.adaptive_linear_regressor module ezmsg.learn.linear_model.cca module ezmsg.learn.linear_model.linear_regressor module ezmsg.learn.linear_model.sgd module ezmsg.learn.linear_model.slda module ezmsg.learn.model.cca module ezmsg.learn.model.mlp module ezmsg.learn.model.refit_kalman module ezmsg.learn.model.rnn module ezmsg.learn.model.transformer module ezmsg.learn.util module F feature_extractor (MLP attribute), [1] fit() (RefitKalmanFilter method), [1] forget_factor (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] forward() (MLP method), [1] (RNNModel method), [1] (TransformerModel method), [1] G get_estimator_type() (AdaptiveDecompTransformer class method), [1] get_message_type() (AdaptiveDecompTransformer class method), [1] get_regressor() (in module ezmsg.learn.util), [1] H H_observation_matrix (RefitKalmanFilter attribute), [1] heads (MLP attribute), [1] hidden_size (RNNModel attribute), [1] (TransformerModel attribute), [1] I IncrementalCCA (class in ezmsg.learn.model.cca), [1] IncrementalDecompSettings (class in ezmsg.learn.dim_reduce.incremental_decomp), [1] IncrementalDecompTransformer (class in ezmsg.learn.dim_reduce.incremental_decomp), [1] IncrementalDecompUnit (class in ezmsg.learn.dim_reduce.incremental_decomp), [1] IncrementalPCASettings (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] IncrementalPCATransformer (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] IncrementalPCAUnit (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] infer_config_from_state_dict() (MLP class method), [1] (RNNModel class method), [1] (TransformerModel class method), [1] init (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] init_hidden() (RNNModel method), [1] initialize() (IncrementalCCA method), [1] INPUT_SAMPLE (BaseAdaptiveDecompUnit attribute), [1] input_size (RNNModel attribute), [1] (TransformerModel attribute), [1] is_fitted (RefitKalmanFilter attribute), [1] K K_kalman_gain (RefitKalmanFilter attribute), [1] L l1_ratio (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] labels (ClassifierMessage attribute), [1] LINEAR (AdaptiveLinearRegressor attribute), [1] (StaticLinearRegressor attribute), [1] LOGISTIC (AdaptiveLinearRegressor attribute), [1] M max_iter (MiniBatchNMFSettings attribute), [1] max_no_improvement (MiniBatchNMFSettings attribute), [1] max_seq_len (TransformerModel attribute), [1] method (IncrementalDecompSettings attribute), [1] MiniBatchNMFSettings (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] MiniBatchNMFTransformer (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] MiniBatchNMFUnit (class in ezmsg.learn.dim_reduce.adaptive_decomp), [1] MLP (class in ezmsg.learn.model.mlp), [1] module ezmsg.learn.dim_reduce.adaptive_decomp ezmsg.learn.dim_reduce.incremental_decomp ezmsg.learn.linear_model.adaptive_linear_regressor ezmsg.learn.linear_model.cca ezmsg.learn.linear_model.linear_regressor ezmsg.learn.linear_model.sgd ezmsg.learn.linear_model.slda ezmsg.learn.model.cca ezmsg.learn.model.mlp ezmsg.learn.model.refit_kalman ezmsg.learn.model.rnn ezmsg.learn.model.transformer ezmsg.learn.util N n_components (AdaptiveDecompSettings attribute), [1] (IncrementalDecompSettings attribute), [1] num_layers (RNNModel attribute), [1] O on_sample() (BaseAdaptiveDecompUnit method), [1] output_size (RNNModel attribute), [1] (TransformerModel attribute), [1] P P_state_covariance (RefitKalmanFilter attribute), [1] PAR (AdaptiveLinearRegressor attribute), [1] partial_fit() (AdaptiveDecompTransformer method), [1] (IncrementalCCA method), [1] predict() (RefitKalmanFilter method), [1] Q Q_measurement_noise_covariance (RefitKalmanFilter attribute), [1] R refit() (RefitKalmanFilter method), [1] RefitKalmanFilter (class in ezmsg.learn.model.refit_kalman), [1] RegressorType (class in ezmsg.learn.util), [1] RIDGE (StaticLinearRegressor attribute), [1] rnn_type (RNNModel attribute), [1] RNNModel (class in ezmsg.learn.model.rnn), [1] S SETTINGS (IncrementalDecompUnit attribute), [1] (IncrementalPCAUnit attribute), [1] (MiniBatchNMFUnit attribute), [1] SGD (AdaptiveLinearRegressor attribute), [1] stateful_op() (IncrementalDecompTransformer method), [1] STATIC (RegressorType attribute), [1] StaticLinearRegressor (class in ezmsg.learn.util), [1] steady_state (RefitKalmanFilter attribute), [1] T template (AdaptiveDecompState attribute), [1] tol (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] transform() (IncrementalCCA method), [1] TransformerModel (class in ezmsg.learn.model.transformer), [1] U update() (RefitKalmanFilter method), [1] update_interval (IncrementalDecompSettings attribute), [1] W W_process_noise_covariance (RefitKalmanFilter attribute), [1] whiten (IncrementalDecompSettings attribute), [1] (IncrementalPCASettings attribute), [1]