Index

_

__getitem__() (wiener_transformer.utils.data_loader.WMT14Dataset method)

__len__() (wiener_transformer.utils.data_loader.WMT14Dataset method)

A

accum_step (wiener_transformer.utils.helpers.TrainState attribute), [1]

all_head_size (wiener_attention.attention_mechanism.WienerSelfAttention attribute) attention_head_size (wiener_attention.attention_mechanism.WienerSelfAttention attribute)

B

Batch (class in wiener_transformer.utils.helpers)

batch_iterator() (in module wiener_transformer.utils.vocab)

C

calculate_bleu() (in module wiener_transformer.utils.helpers) clones() (in module wiener_transformer.transformer)

collate_batch() (in module wiener_transformer.utils.data_loader) create_dataloaders() (in module wiener_transformer.utils.data_loader) create_embedding_weights() (in module wiener_transformer.utils.embeddings)

D

decode() (wiener_transformer.transformer.EncoderDecoder method) Decoder (class in wiener_transformer.transformer) DecoderLayer (class in wiener_transformer.transformer)

dropout (wiener_attention.attention_mechanism.WienerSelfAttention attribute) DummyOptimizer (class in wiener_transformer.utils.helpers) DummyScheduler (class in wiener_transformer.utils.helpers)

E

Embeddings (class in wiener_transformer.transformer) encode() (wiener_transformer.transformer.EncoderDecoder method) Encoder (class in wiener_transformer.transformer)

EncoderDecoder (class in wiener_transformer.transformer) EncoderLayer (class in wiener_transformer.transformer) extract_sentences() (in module wiener_transformer.utils.embeddings)

F

forward() (wiener_attention.attention_mechanism.WienerSelfAttention method) (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.transformer.Decoder method) (wiener_transformer.transformer.DecoderLayer method) (wiener_transformer.transformer.Embeddings method) (wiener_transformer.transformer.Encoder method) (wiener_transformer.transformer.EncoderDecoder method) (wiener_transformer.transformer.EncoderLayer method) (wiener_transformer.transformer.Generator method) (wiener_transformer.transformer.LayerNorm method) (wiener_transformer.transformer.MultiHeadedAttention method) (wiener_transformer.transformer.PositionalEncoding method) (wiener_transformer.transformer.PositionwiseFeedForward method) (wiener_transformer.transformer.SublayerConnection method) (wiener_transformer.utils.wienerloss.WienerLoss method)

G

gamma (wiener_attention.attention_mechanism.WienerSelfAttention attribute) Generator (class in wiener_transformer.transformer)

get_filter_shape() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method)

I

identity() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) init_fasttext_weights() (wiener_transformer.transformer.Embeddings method)

init_glove_weights() (wiener_transformer.transformer.Embeddings method) init_learned_weights() (wiener_transformer.transformer.Embeddings method) init_word2vec_weights() (wiener_transformer.transformer.Embeddings method)

K

key (wiener_attention.attention_mechanism.WienerSelfAttention attribute)

L

LayerNorm (class in wiener_transformer.transformer) load_glove_embeddings() (in module wiener_transformer.utils.embeddings)

load_tokenizers() (in module wiener_transformer.utils.vocab) load_trained_model() (in module wiener_transformer.utils.train) load_wmt() (in module wiener_transformer.utils.vocab)

M

make_bert_model() (in module wiener_attention.model) make_bert_tokenizer() (in module wiener_attention.model) make_delta() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) make_doubly_block() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) make_model() (in module wiener_transformer.transformer) make_penalty() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) make_std_mask() (wiener_transformer.utils.helpers.Batch static method) make_toeplitz() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) module wiener_attention.attention_mechanism wiener_attention.model wiener_attention.wiener_metric wiener_transformer.transformer wiener_transformer.utils.data_loader wiener_transformer.utils.embeddings wiener_transformer.utils.helpers wiener_transformer.utils.train wiener_transformer.utils.vocab wiener_transformer.utils.wienerloss

multigauss() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) MultiHeadedAttention (class in wiener_transformer.transformer)

N

ntokens (wiener_transformer.utils.helpers.Batch attribute)

num_attention_heads (wiener_attention.attention_mechanism.WienerSelfAttention attribute)

P

pad() (in module wiener_transformer.utils.helpers) pad_signal() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method)

PositionalEncoding (class in wiener_transformer.transformer) PositionwiseFeedForward (class in wiener_transformer.transformer)

Q

query (wiener_attention.attention_mechanism.WienerSelfAttention attribute)

R

rate() (in module wiener_transformer.utils.helpers) rms() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method)

run_epoch() (in module wiener_transformer.utils.helpers)

S

samples (wiener_transformer.utils.helpers.TrainState attribute), [1] similarity_function (wiener_attention.attention_mechanism.WienerSelfAttention attribute) src (wiener_transformer.utils.helpers.Batch attribute) src_mask (wiener_transformer.utils.helpers.Batch attribute) step (wiener_transformer.utils.helpers.TrainState attribute), [1]

step() (wiener_transformer.utils.helpers.DummyOptimizer method), [1] (wiener_transformer.utils.helpers.DummyScheduler method), [1] SublayerConnection (class in wiener_transformer.transformer) subsequent_mask() (in module wiener_transformer.transformer) (in module wiener_transformer.utils.helpers)

T

tgt (wiener_transformer.utils.helpers.Batch attribute) tgt_mask (wiener_transformer.utils.helpers.Batch attribute) tgt_y (wiener_transformer.utils.helpers.Batch attribute) tokenize() (in module wiener_transformer.utils.helpers)

tokens (wiener_transformer.utils.helpers.TrainState attribute), [1] train_model() (in module wiener_transformer.utils.train) TrainState (class in wiener_transformer.utils.helpers) transform() (in module wiener_transformer.utils.vocab) transpose_for_scores() (wiener_attention.attention_mechanism.WienerSelfAttention method)

V

value (wiener_attention.attention_mechanism.WienerSelfAttention attribute)

W

wiener() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) wiener_attention.attention_mechanism module wiener_attention.model module wiener_attention.wiener_metric module wiener_transformer.transformer module wiener_transformer.utils.data_loader module wiener_transformer.utils.embeddings module

wiener_transformer.utils.helpers module wiener_transformer.utils.train module wiener_transformer.utils.vocab module wiener_transformer.utils.wienerloss module wienerfft() (wiener_attention.wiener_metric.WienerSimilarityMetric method) (wiener_transformer.utils.wienerloss.WienerLoss method) WienerLoss (class in wiener_transformer.utils.wienerloss) WienerSelfAttention (class in wiener_attention.attention_mechanism) WienerSimilarityMetric (class in wiener_attention.wiener_metric) WMT14Dataset (class in wiener_transformer.utils.data_loader)

Z

zero_grad() (wiener_transformer.utils.helpers.DummyOptimizer method), [1]