Index

_

__init__() (theanets.activations.Activation method) (theanets.activations.LGrelu method) (theanets.activations.Maxout method) (theanets.activations.Prelu method) (theanets.feedforward.Autoencoder method) (theanets.feedforward.Classifier method) (theanets.feedforward.Regressor method) (theanets.graph.Network method) (theanets.layers.base.Layer method) (theanets.layers.convolution.Conv1 method) (theanets.layers.convolution.Convolution method) (theanets.layers.feedforward.Classifier method) (theanets.layers.feedforward.Feedforward method) (theanets.layers.feedforward.Input method) (theanets.layers.feedforward.Tied method) (theanets.layers.recurrent.ARRNN method) (theanets.layers.recurrent.Bidirectional method) (theanets.layers.recurrent.Clockwork method) (theanets.layers.recurrent.GRU method) (theanets.layers.recurrent.LRRNN method) (theanets.layers.recurrent.LSTM method) (theanets.layers.recurrent.MRNN method) (theanets.layers.recurrent.RNN method) (theanets.layers.recurrent.Recurrent method) (theanets.main.Experiment method) (theanets.recurrent.Autoencoder method) (theanets.recurrent.Classifier method) (theanets.recurrent.Predictor method) (theanets.recurrent.Regressor method) (theanets.recurrent.Text method) (theanets.trainer.DownhillTrainer method) (theanets.trainer.SampleTrainer method) (theanets.trainer.SupervisedPretrainer method) (theanets.trainer.UnsupervisedPretrainer method)

A

accuracy() (theanets.feedforward.Classifier method) Activation (class in theanets.activations) add_bias() (theanets.layers.base.Layer method) add_conv_weights() (theanets.layers.convolution.Convolution method)

add_layer() (theanets.graph.Network method) add_weights() (theanets.layers.base.Layer method) (theanets.layers.recurrent.Recurrent method) ARRNN (class in theanets.layers.recurrent) Autoencoder (class in theanets.feedforward) (class in theanets.recurrent)

B

batches() (in module theanets.recurrent) Bidirectional (class in theanets.layers.recurrent)

build() (in module theanets.activations) (in module theanets.layers.base) build_graph() (theanets.graph.Network method)

C

Classifier (class in theanets.feedforward) (class in theanets.layers.feedforward) (class in theanets.recurrent) classifier_batches() (theanets.recurrent.Text method) Clockwork (class in theanets.layers.recurrent) connect() (theanets.layers.base.Layer method)

Conv1 (class in theanets.layers.convolution) Convolution (class in theanets.layers.convolution) create_dataset() (theanets.main.Experiment method) create_trainer() (theanets.main.Experiment method)

D

decode() (theanets.feedforward.Autoencoder method) (theanets.recurrent.Text method)

DownhillTrainer (class in theanets.trainer)

E

encode() (theanets.feedforward.Autoencoder method) (theanets.recurrent.Text method) error() (theanets.feedforward.Classifier method) (theanets.feedforward.Regressor method) (theanets.graph.Network method) (theanets.recurrent.Classifier method) (theanets.recurrent.Predictor method)

Experiment (class in theanets.main)

F

feed_forward() (theanets.graph.Network method) Feedforward (class in theanets.layers.feedforward)

find() (theanets.graph.Network method) (theanets.layers.base.Layer method)

G

generate_prediction() (theanets.recurrent.Predictor method)

GRU (class in theanets.layers.recurrent)

I

initial_state() (theanets.layers.recurrent.Recurrent method) Input (class in theanets.layers.feedforward)

input_size (theanets.layers.base.Layer attribute) itertrain() (theanets.main.Experiment method) (theanets.trainer.DownhillTrainer method) (theanets.trainer.SampleTrainer method) (theanets.trainer.SupervisedPretrainer method) (theanets.trainer.UnsupervisedPretrainer method)

L

Layer (class in theanets.layers.base) LGrelu (class in theanets.activations) load() (theanets.graph.Network class method) (theanets.main.Experiment method) log() (theanets.layers.base.Layer method) (theanets.layers.feedforward.Input method) (theanets.layers.recurrent.Clockwork method)

loss() (theanets.graph.Network method) LRRNN (class in theanets.layers.recurrent) LSTM (class in theanets.layers.recurrent)

M

Maxout (class in theanets.activations) monitors() (theanets.feedforward.Classifier method) (theanets.graph.Network method)

MRNN (class in theanets.layers.recurrent)

N

Network (class in theanets.graph)

num_params (theanets.graph.Network attribute) (theanets.layers.base.Layer attribute) (theanets.layers.recurrent.Bidirectional attribute)

O

output_name() (theanets.graph.Network method) (theanets.layers.base.Layer method)

P

params (theanets.graph.Network attribute) (theanets.layers.base.Layer attribute) (theanets.layers.recurrent.Bidirectional attribute) predict() (theanets.feedforward.Classifier method) (theanets.graph.Network method) predict_logit() (theanets.feedforward.Classifier method) predict_proba() (theanets.feedforward.Classifier method)

predict_sequence() (theanets.recurrent.Classifier method) Predictor (class in theanets.recurrent) Prelu (class in theanets.activations)

R

Recurrent (class in theanets.layers.recurrent) Regressor (class in theanets.feedforward) (class in theanets.recurrent)

reservoir() (theanets.trainer.SampleTrainer static method) RNN (class in theanets.layers.recurrent)

S

SampleTrainer (class in theanets.trainer) save() (theanets.graph.Network method) (theanets.main.Experiment method) score() (theanets.feedforward.Autoencoder method) (theanets.feedforward.Classifier method) (theanets.graph.Network method)

setup() (theanets.layers.base.Layer method) (theanets.layers.convolution.Conv1 method) (theanets.layers.feedforward.Feedforward method) (theanets.layers.feedforward.Tied method) (theanets.layers.recurrent.ARRNN method) (theanets.layers.recurrent.LRRNN method) (theanets.layers.recurrent.LSTM method) (theanets.layers.recurrent.MRNN method) (theanets.layers.recurrent.RNN method) SupervisedPretrainer (class in theanets.trainer)

T

Text (class in theanets.recurrent) theanets.activations (module) theanets.feedforward (module) theanets.graph (module) theanets.layers.base (module) theanets.layers.convolution (module) theanets.layers.feedforward (module) theanets.layers.recurrent (module)

theanets.main (module) theanets.recurrent (module) theanets.trainer (module) Tied (class in theanets.layers.feedforward) tied_weights (theanets.feedforward.Autoencoder attribute) to_spec() (theanets.layers.base.Layer method) (theanets.layers.feedforward.Input method) (theanets.layers.feedforward.Tied method) (theanets.layers.recurrent.Bidirectional method) (theanets.layers.recurrent.Clockwork method) (theanets.layers.recurrent.MRNN method) train() (theanets.main.Experiment method) transform() (theanets.layers.base.Layer method) (theanets.layers.convolution.Conv1 method) (theanets.layers.feedforward.Feedforward method) (theanets.layers.feedforward.Tied method) (theanets.layers.recurrent.ARRNN method) (theanets.layers.recurrent.Bidirectional method) (theanets.layers.recurrent.Clockwork method) (theanets.layers.recurrent.GRU method) (theanets.layers.recurrent.LRRNN method) (theanets.layers.recurrent.LSTM method) (theanets.layers.recurrent.MRNN method) (theanets.layers.recurrent.RNN method)

U

UnsupervisedPretrainer (class in theanets.trainer)

updates() (theanets.graph.Network method)