Index

A

annotated (langvae.encoders.sentence.SentenceEncoder property) annotations (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute)

args (langvae.decoders.sentence.SentenceDecoder attribute) automodel_preset (langvae.encoders.sentence.SentenceEncoder attribute) AutoModelPreset (class in langvae.encoders.automodel_presets)

C

cache_persistence (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute) (langvae.data_conversion.tokenization.TokenizedDataSet attribute) caching (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute) (langvae.data_conversion.tokenization.TokenizedDataSet attribute) (langvae.encoders.sentence.SentenceEncoder attribute) cls (langvae.encoders.automodel_presets.AutoModelPreset attribute), [1]

CLS (langvae.encoders.automodel_presets.PoolingMethod attribute) cls_token_pooling() (in module langvae.encoders.sentence) cls_type (langvae.encoders.automodel_presets.AutoModelPreset property) collate_sparse_fn() (in module langvae.data_conversion.tokenization) copy_model_ptref() (in module langvae.trainers.cyclical_schedule_kl) CyclicalScheduleKLThresholdTrainer (class in langvae.trainers.cyclical_schedule_kl) CyclicalScheduleKLThresholdTrainerConfig (class in langvae.trainers.cyclical_schedule_kl)

D

debug (langvae.encoders.sentence.SentenceEncoder attribute) decode_sentences() (langvae.arch.vae.LangVAE method) decoder (langvae.decoders.sentence.SentenceDecoder property) decoder_tokenizer (langvae.encoders.sentence.SentenceEncoder attribute) (langvae.encoders.sentence.SentenceEncoder property)

densify_w_padding() (in module langvae.data_conversion.sparse) device (langvae.decoders.sentence.SentenceDecoder attribute) (langvae.encoders.sentence.SentenceEncoder attribute) device_map (langvae.decoders.sentence.SentenceDecoder attribute)

E

encode_z() (langvae.arch.vae.LangVAE method) encoder (langvae.encoders.sentence.SentenceEncoder attribute) (langvae.encoders.sentence.SentenceEncoder property)

eval_step() (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainer method)

F

forward() (langvae.arch.vae.LangVAE method) (langvae.decoders.sentence.SentenceDecoder method) (langvae.encoders.sentence.SentenceEncoder method)

frange_cycle_zero_linear() (in module langvae.trainers.cyclical_schedule_kl)

G

generate() (langvae.decoders.sentence.SentenceDecoder method) get_eval_dataloader() (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainer method)

get_hash() (in module langvae.data_conversion.tokenization) get_train_dataloader() (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainer method)

I

init_pretrained_model() (langvae.decoders.sentence.SentenceDecoder method) (langvae.encoders.sentence.SentenceEncoder method)

L

LanguageTrainingPipeline (class in langvae.pipelines.lang_training) langvae module LangVAE (class in langvae.arch.vae) langvae.arch module langvae.arch.vae module langvae.data_conversion module langvae.data_conversion.sparse module langvae.data_conversion.tokenization module langvae.decoders module langvae.decoders.sentence module langvae.encoders module

langvae.encoders.automodel_presets module langvae.encoders.sentence module langvae.pipelines module langvae.pipelines.lang_training module langvae.trainers module langvae.trainers.cyclical_schedule_kl module LAST (langvae.encoders.automodel_presets.PoolingMethod attribute) last_token_pooling() (in module langvae.encoders.sentence) latent_size (langvae.decoders.sentence.SentenceDecoder attribute) linear (langvae.encoders.sentence.SentenceEncoder attribute) load_from_folder() (langvae.arch.vae.LangVAE class method) load_from_hf_hub() (langvae.arch.vae.LangVAE class method) loss_function() (langvae.arch.vae.LangVAE method)

M

max_beta (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainerConfig attribute) max_len (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute) (langvae.data_conversion.tokenization.TokenizedDataSet attribute) (langvae.decoders.sentence.SentenceDecoder attribute) MEAN (langvae.encoders.automodel_presets.PoolingMethod attribute) mean_pooling() (in module langvae.encoders.sentence) model_path (langvae.decoders.sentence.SentenceDecoder attribute) module langvae langvae.arch langvae.arch.vae langvae.data_conversion langvae.data_conversion.sparse langvae.data_conversion.tokenization langvae.decoders langvae.decoders.sentence langvae.encoders langvae.encoders.automodel_presets langvae.encoders.sentence langvae.pipelines langvae.pipelines.lang_training langvae.trainers langvae.trainers.cyclical_schedule_kl

N

n_cycles (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainerConfig attribute)

normalize (langvae.encoders.automodel_presets.AutoModelPreset attribute), [1]

P

pooling_method (langvae.encoders.automodel_presets.AutoModelPreset attribute), [1]

PoolingMethod (class in langvae.encoders.automodel_presets) push_to_hf_hub() (langvae.arch.vae.LangVAE method)

R

recode() (langvae.encoders.sentence.SentenceEncoder method)

S

save() (langvae.arch.vae.LangVAE method) SentenceDecoder (class in langvae.decoders.sentence) SentenceEncoder (class in langvae.encoders.sentence)

source (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute) (langvae.data_conversion.tokenization.TokenizedDataSet attribute) start_beta (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainerConfig attribute)

T

target_kl (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainerConfig attribute) to() (langvae.decoders.sentence.SentenceDecoder method) (langvae.encoders.sentence.SentenceEncoder method) TokenizedAnnotatedDataSet (class in langvae.data_conversion.tokenization) TokenizedDataSet (class in langvae.data_conversion.tokenization) tokenizer (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute) (langvae.data_conversion.tokenization.TokenizedDataSet attribute) (langvae.decoders.sentence.SentenceDecoder property) (langvae.encoders.sentence.SentenceEncoder attribute) (langvae.encoders.sentence.SentenceEncoder property)

tokenizer_options (langvae.data_conversion.tokenization.TokenizedAnnotatedDataSet attribute) (langvae.data_conversion.tokenization.TokenizedDataSet attribute) train() (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainer method) train_step() (langvae.trainers.cyclical_schedule_kl.CyclicalScheduleKLThresholdTrainer method)

V

vae_nll_loss() (in module langvae.arch.vae)

vocab_size (langvae.data_conversion.tokenization.TokenizedDataSet attribute)