Index

_

__init__() (AdaptiveDecompSettings method), [1] (AdaptiveDecompTransformer method), [1] (AdaptiveLinearRegressorSettings method), [1] (AdaptiveLinearRegressorTransformer method), [1] (ClassifierMessage method), [1] (IncrementalCCA method), [1] (IncrementalDecompSettings method), [1] (IncrementalPCASettings method), [1] (LinearRegressorSettings method), [1] (LinearRegressorTransformer method), [1] (MiniBatchNMFSettings method), [1] (MLP method), [1], [2], [3] (MLPSettings method), [1] (RefitKalmanFilter method), [1] (RefitKalmanFilterSettings method), [1] (RNNModel method), [1] (RNNSettings method), [1] (SGDDecoderSettings method), [1] (SklearnModelSettings method), [1] (SLDASettings method), [1] (TorchModelSettings method), [1] (TorchSimpleSettings method), [1] (TransformerModel method), [1] (TransformerSettings method), [1]

_state (RefitKalmanFilterProcessor attribute), [1]

A

A_state_transition_matrix (RefitKalmanFilter attribute), [1] activation_layer (MLPSettings 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] AdaptiveLinearRegressorSettings (class in ezmsg.learn.process.adaptive_linear_regressor), [1] AdaptiveLinearRegressorState (class in ezmsg.learn.process.adaptive_linear_regressor), [1] AdaptiveLinearRegressorTransformer (class in ezmsg.learn.process.adaptive_linear_regressor), [1] AdaptiveLinearRegressorUnit (class in ezmsg.learn.process.adaptive_linear_regressor), [1] (class in ezmsg.learn.process.linear_regressor), [1]

alpha (SGDDecoderSettings attribute), [1] alpha_H (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] alpha_W (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] ar_head (TransformerState attribute), [1] attention_heads (TransformerModel attribute), [1] autoregressive_head (TransformerSettings attribute), [1] axis (AdaptiveDecompSettings attribute), [1] (IncrementalDecompSettings attribute), [1] (SLDASettings 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]

bias (MLPSettings attribute), [1] buffer_cursor_positions (RefitKalmanFilterState attribute), [1], [2], [3] buffer_hold_flags (RefitKalmanFilterState attribute), [1], [2], [3] buffer_neural (RefitKalmanFilterState attribute), [1], [2], [3] buffer_state (RefitKalmanFilterState attribute), [1], [2], [3] buffer_target_positions (RefitKalmanFilterState attribute), [1], [2], [3]

C

chan_ax (SklearnModelState attribute), [1] (TorchSimpleState attribute), [1] checkpoint_path (MLPSettings attribute), [1] (RefitKalmanFilterSettings attribute), [1], [2], [3] (SklearnModelSettings attribute), [1] (TorchSimpleSettings attribute), [1]

ClassifierMessage (class in ezmsg.learn.util), [1] config_path (TorchSimpleSettings attribute), [1] construct_generator() (SGDDecoder method), [1] current_position (RefitKalmanFilterState attribute), [1]

D

decoder_layers (TransformerModel attribute), [1] device (MLPState attribute), [1] (TorchSimpleSettings attribute), [1] (TorchSimpleState attribute), [1]

dropout (MLPSettings attribute), [1] (RNNModel attribute), [1] (TransformerModel attribute), [1]

E

encoder_layers (TransformerModel attribute), [1] estimator (AdaptiveDecompState attribute), [1] eta0 (SGDDecoderSettings attribute), [1] ezmsg.learn module ezmsg.learn.dim_reduce module ezmsg.learn.dim_reduce.adaptive_decomp module ezmsg.learn.dim_reduce.incremental_decomp module ezmsg.learn.linear_model 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 module ezmsg.learn.model.cca module ezmsg.learn.model.mlp module ezmsg.learn.model.mlp_old module ezmsg.learn.model.refit_kalman module

ezmsg.learn.model.rnn module ezmsg.learn.model.transformer module ezmsg.learn.nlin_model module ezmsg.learn.nlin_model.mlp module ezmsg.learn.process module ezmsg.learn.process.adaptive_linear_regressor module ezmsg.learn.process.base module ezmsg.learn.process.linear_regressor module ezmsg.learn.process.mlp_old module ezmsg.learn.process.refit_kalman module ezmsg.learn.process.rnn module ezmsg.learn.process.sgd module ezmsg.learn.process.sklearn module ezmsg.learn.process.slda module ezmsg.learn.process.torch module ezmsg.learn.process.transformer module ezmsg.learn.util module

F

feature_extractor (MLP attribute), [1] fit() (RefitKalmanFilter method), [1] (RefitKalmanFilterProcessor method), [1] (SklearnModelProcessor 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] has_decoder (TransformerProcessor property), [1] heads (MLP attribute), [1] hello() (in module ezmsg.learn), [1]

hidden_channels (MLPSettings attribute), [1] hidden_size (RNNModel attribute), [1] (TransformerModel attribute), [1] hx (RNNState 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] inplace (MLPSettings attribute), [1] INPUT_SAMPLE (BaseAdaptiveDecompUnit attribute), [1] (SGDDecoder 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] label_weights (SGDDecoderSettings attribute), [1] labels (ClassifierMessage attribute), [1] lda (SLDAState attribute), [1] learning_rate (MLPSettings attribute), [1] (TorchModelSettings attribute), [1] LINEAR (AdaptiveLinearRegressor attribute), [1] (StaticLinearRegressor attribute), [1]

LinearRegressorSettings (class in ezmsg.learn.process.linear_regressor), [1] LinearRegressorState (class in ezmsg.learn.process.linear_regressor), [1] LinearRegressorTransformer (class in ezmsg.learn.process.linear_regressor), [1] load_checkpoint() (SklearnModelProcessor method), [1] load_from_checkpoint() (RefitKalmanFilterProcessor method), [1] log_for_refit() (RefitKalmanFilterProcessor method), [1] LOGISTIC (AdaptiveLinearRegressor attribute), [1] loss (SGDDecoderSettings attribute), [1] loss_fn (TorchModelSettings attribute), [1] loss_weights (TorchModelSettings attribute), [1]

M

max_cache_len (TransformerSettings attribute), [1] 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] (class in ezmsg.learn.model.mlp_old), [1] MLPProcessor (class in ezmsg.learn.process.mlp_old), [1] MLPSettings (class in ezmsg.learn.process.mlp_old), [1] MLPState (class in ezmsg.learn.process.mlp_old), [1] MLPUnit (class in ezmsg.learn.process.mlp_old), [1] model (AdaptiveLinearRegressorState attribute), [1] (LinearRegressorState attribute), [1] (MLPState attribute), [1] (RefitKalmanFilterState attribute), [1], [2], [3] (SklearnModelState attribute), [1] (TorchSimpleState attribute), [1] model_class (RNNSettings attribute), [1] (SklearnModelSettings attribute), [1] (TorchSimpleSettings attribute), [1] (TransformerSettings attribute), [1] model_kwargs (AdaptiveLinearRegressorSettings attribute), [1] (LinearRegressorSettings attribute), [1] (SklearnModelSettings attribute), [1] (TorchSimpleSettings attribute), [1] model_type (AdaptiveLinearRegressorSettings attribute), [1] (LinearRegressorSettings attribute), [1] ModelInitMixin (class in ezmsg.learn.process.base), [1] module ezmsg.learn ezmsg.learn.dim_reduce ezmsg.learn.dim_reduce.adaptive_decomp ezmsg.learn.dim_reduce.incremental_decomp ezmsg.learn.linear_model 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 ezmsg.learn.model.cca ezmsg.learn.model.mlp ezmsg.learn.model.mlp_old ezmsg.learn.model.refit_kalman ezmsg.learn.model.rnn ezmsg.learn.model.transformer ezmsg.learn.nlin_model ezmsg.learn.nlin_model.mlp ezmsg.learn.process ezmsg.learn.process.adaptive_linear_regressor ezmsg.learn.process.base ezmsg.learn.process.linear_regressor ezmsg.learn.process.mlp_old ezmsg.learn.process.refit_kalman ezmsg.learn.process.rnn ezmsg.learn.process.sgd ezmsg.learn.process.sklearn ezmsg.learn.process.slda ezmsg.learn.process.torch ezmsg.learn.process.transformer ezmsg.learn.util

N

n_components (AdaptiveDecompSettings attribute), [1] (IncrementalDecompSettings attribute), [1]

norm_layer (MLPSettings attribute), [1] num_layers (RNNModel attribute), [1]

O

on_sample() (BaseAdaptiveDecompUnit method), [1] (SGDDecoder method), [1] on_signal() (RNNUnit method), [1] (TorchModelUnit method), [1] (TorchSimpleUnit method), [1] (TransformerUnit method), [1]

optimizer (MLPState attribute), [1] (TorchModelState attribute), [1] out_template (SLDAState attribute), [1] output_size (RNNModel attribute), [1] (TransformerModel attribute), [1]

P

P (RefitKalmanFilterState attribute), [1], [2], [3] P_state_covariance (RefitKalmanFilter attribute), [1] PAR (AdaptiveLinearRegressor attribute), [1] partial_fit() (AdaptiveDecompTransformer method), [1] (AdaptiveLinearRegressorTransformer method), [1] (IncrementalCCA method), [1] (LinearRegressorTransformer method), [1] (MLPProcessor method), [1] (RefitKalmanFilterProcessor method), [1] (RNNProcessor method), [1] (SklearnModelProcessor method), [1] (TorchModelProcessor method), [1] (TransformerProcessor method), [1]

partial_fit_classes (SklearnModelSettings attribute), [1] predict() (RefitKalmanFilter method), [1] preserve_state_across_windows (RNNSettings attribute), [1]

Q

Q_measurement_noise_covariance (RefitKalmanFilter attribute), [1]

R

refit() (RefitKalmanFilter method), [1] refit_model() (RefitKalmanFilterProcessor method), [1] RefitKalmanFilter (class in ezmsg.learn.model.refit_kalman), [1] RefitKalmanFilterProcessor (class in ezmsg.learn.process.refit_kalman), [1] RefitKalmanFilterSettings (class in ezmsg.learn.process.refit_kalman), [1] RefitKalmanFilterState (class in ezmsg.learn.process.refit_kalman), [1] RefitKalmanFilterUnit (class in ezmsg.learn.process.refit_kalman), [1] RegressorType (class in ezmsg.learn.util), [1] reset_cache() (TransformerProcessor method), [1]

reset_hidden() (RNNProcessor method), [1] reset_hidden_on_fit (RNNSettings attribute), [1] RIDGE (StaticLinearRegressor attribute), [1] rnn_type (RNNModel attribute), [1] RNNModel (class in ezmsg.learn.model.rnn), [1] RNNProcessor (class in ezmsg.learn.process.rnn), [1] RNNSettings (class in ezmsg.learn.process.rnn), [1] RNNState (class in ezmsg.learn.process.rnn), [1] RNNUnit (class in ezmsg.learn.process.rnn), [1]

S

save_checkpoint() (MLPProcessor method), [1] (RefitKalmanFilterProcessor method), [1] (SklearnModelProcessor method), [1] (TorchProcessorMixin method), [1] scheduler (MLPState attribute), [1] (TorchModelState attribute), [1] scheduler_gamma (MLPSettings attribute), [1] (TorchModelSettings attribute), [1] SETTINGS (AdaptiveLinearRegressorUnit attribute), [1], [2], [3] (IncrementalDecompUnit attribute), [1] (IncrementalPCAUnit attribute), [1] (MiniBatchNMFUnit attribute), [1] (MLPUnit attribute), [1] settings (RefitKalmanFilterProcessor attribute), [1] SETTINGS (RefitKalmanFilterUnit attribute), [1] (RNNUnit attribute), [1] (SGDDecoder attribute), [1] (SklearnModelUnit attribute), [1] (SLDA attribute), [1] (TorchModelUnit attribute), [1] (TorchSimpleUnit attribute), [1] (TransformerUnit attribute), [1]

settings_path (AdaptiveLinearRegressorSettings attribute), [1] (LinearRegressorSettings attribute), [1] (SGDDecoderSettings attribute), [1] (SLDASettings attribute), [1] SGD (AdaptiveLinearRegressor attribute), [1] sgd_decoder() (in module ezmsg.learn.process.sgd), [1] SGDDecoder (class in ezmsg.learn.process.sgd), [1] SGDDecoderSettings (class in ezmsg.learn.process.sgd), [1] single_precision (MLPSettings attribute), [1] (TorchSimpleSettings attribute), [1] SklearnModelProcessor (class in ezmsg.learn.process.sklearn), [1] SklearnModelSettings (class in ezmsg.learn.process.sklearn), [1] SklearnModelState (class in ezmsg.learn.process.sklearn), [1] SklearnModelUnit (class in ezmsg.learn.process.sklearn), [1] SLDA (class in ezmsg.learn.process.slda), [1] SLDASettings (class in ezmsg.learn.process.slda), [1] SLDAState (class in ezmsg.learn.process.slda), [1] SLDATransformer (class in ezmsg.learn.process.slda), [1] stateful_op() (IncrementalDecompTransformer method), [1] STATIC (RegressorType attribute), [1] StaticLinearRegressor (class in ezmsg.learn.util), [1] steady_state (RefitKalmanFilter attribute), [1] (RefitKalmanFilterSettings attribute), [1], [2], [3]

T

template (AdaptiveDecompState attribute), [1] (AdaptiveLinearRegressorState attribute), [1] (LinearRegressorState attribute), [1] (MLPState attribute), [1] tgt_cache (TransformerState attribute), [1] tol (IncrementalDecompSettings attribute), [1] (MiniBatchNMFSettings attribute), [1] TorchModelProcessor (class in ezmsg.learn.process.torch), [1] TorchModelSettings (class in ezmsg.learn.process.torch), [1] TorchModelState (class in ezmsg.learn.process.torch), [1] TorchModelUnit (class in ezmsg.learn.process.torch), [1]

TorchProcessorMixin (class in ezmsg.learn.process.torch), [1] TorchSimpleProcessor (class in ezmsg.learn.process.torch), [1] TorchSimpleSettings (class in ezmsg.learn.process.torch), [1] TorchSimpleState (class in ezmsg.learn.process.torch), [1] TorchSimpleUnit (class in ezmsg.learn.process.torch), [1] transform() (IncrementalCCA method), [1] TransformerModel (class in ezmsg.learn.model.transformer), [1] TransformerProcessor (class in ezmsg.learn.process.transformer), [1] TransformerSettings (class in ezmsg.learn.process.transformer), [1] TransformerState (class in ezmsg.learn.process.transformer), [1] TransformerUnit (class in ezmsg.learn.process.transformer), [1]

U

update() (RefitKalmanFilter method), [1]

update_interval (IncrementalDecompSettings attribute), [1]

V

velocity_indices (RefitKalmanFilterSettings attribute), [1]

W

W_process_noise_covariance (RefitKalmanFilter attribute), [1] weight_decay (TorchModelSettings attribute), [1]

whiten (IncrementalDecompSettings attribute), [1] (IncrementalPCASettings attribute), [1]

X

x (RefitKalmanFilterState attribute), [1], [2], [3]