Index

_

__call__() (replay.metrics.CategoricalDiversity method) (replay.metrics.Coverage method) (replay.metrics.HitRate method) (replay.metrics.MAP method) (replay.metrics.MRR method) (replay.metrics.NDCG method) (replay.metrics.Novelty method) (replay.metrics.OfflineMetrics method) (replay.metrics.Precision method) (replay.metrics.Recall method) (replay.metrics.RocAuc method) (replay.metrics.Unexpectedness method) (replay.models.nn.loss.ScalableCrossEntropyLoss method) (replay.nn.mask.DefaultAttentionMask method) __init__() (replay.data.nn.parquet.ParquetDataset method) (replay.data.nn.ParquetModule method) (replay.data.nn.TorchSequentialDataset method) (replay.data.nn.TorchSequentialValidationDataset method) (replay.experimental.models.ADMMSLIM method) (replay.experimental.models.cql.CQL method) (replay.experimental.models.DDPG method) (replay.experimental.models.dt4rec.dt4rec.DT4Rec method) (replay.experimental.models.HierarchicalRecommender method) (replay.experimental.models.ImplicitWrap method) (replay.experimental.models.lightfm_wrap.LightFMWrap method) (replay.experimental.models.MultVAE method) (replay.experimental.models.NeuralTS method) (replay.experimental.models.NeuroMF method) (replay.experimental.models.ScalaALSWrap method) (replay.experimental.models.ULinUCB method) (replay.experimental.scenarios.obp_wrapper.OBPOfflinePolicyLearner method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.metrics.CategoricalDiversity method) (replay.metrics.Coverage method) (replay.metrics.Experiment method) (replay.metrics.HitRate method) (replay.metrics.MAP method) (replay.metrics.MRR method) (replay.metrics.NDCG method) (replay.metrics.Novelty method) (replay.metrics.OfflineMetrics method) (replay.metrics.Precision method) (replay.metrics.Recall method) (replay.metrics.RocAuc method) (replay.metrics.Unexpectedness method) (replay.models.ALSWrap method) (replay.models.AssociationRulesItemRec method) (replay.models.ClusterRec method) (replay.models.ItemKNN method) (replay.models.KLUCB method) (replay.models.LinUCB method) (replay.models.nn.loss.ScalableCrossEntropyLoss method) (replay.models.nn.sequential.Bert4Rec method) (replay.models.nn.sequential.bert4rec.Bert4RecModel method) (replay.models.nn.sequential.bert4rec.Bert4RecPredictionDataset method) (replay.models.nn.sequential.bert4rec.Bert4RecTrainingDataset method) (replay.models.nn.sequential.bert4rec.Bert4RecValidationDataset method) (replay.models.nn.sequential.SasRec method) (replay.models.nn.sequential.sasrec.SasRecModel method) (replay.models.nn.sequential.sasrec.SasRecPredictionDataset method) (replay.models.nn.sequential.sasrec.SasRecTrainingDataset method) (replay.models.nn.sequential.sasrec.SasRecValidationDataset method) (replay.models.RandomRec method) (replay.models.SLIM method) (replay.models.ThompsonSampling method) (replay.models.UCB method) (replay.models.Word2VecRec method) (replay.nn.agg.ConcatAggregator method) (replay.nn.agg.SumAggregator method) (replay.nn.attention.MultiHeadDifferentialAttention method) (replay.nn.embedding.CategoricalEmbedding method) (replay.nn.embedding.NumericalEmbedding method) (replay.nn.embedding.SequenceEmbedding method) (replay.nn.ffn.PointWiseFeedForward method) (replay.nn.ffn.SwiGLU method) (replay.nn.ffn.SwiGLUEncoder method) (replay.nn.lightning.callback.ComputeMetricsCallback method) (replay.nn.lightning.callback.HiddenStatesCallback method) (replay.nn.lightning.callback.PandasTopItemsCallback method) (replay.nn.lightning.callback.PolarsTopItemsCallback method) (replay.nn.lightning.callback.SparkTopItemsCallback method) (replay.nn.lightning.callback.TorchTopItemsCallback method) (replay.nn.lightning.LightningModule method) (replay.nn.lightning.postprocessor.PostprocessorBase method) (replay.nn.lightning.postprocessor.SeenItemsFilter method) (replay.nn.loss.BCESampled method) (replay.nn.loss.CE method) (replay.nn.loss.CESampled method) (replay.nn.loss.LogInCE method) (replay.nn.loss.LogInCESampled method) (replay.nn.loss.LogOutCE method) (replay.nn.mask.DefaultAttentionMask method) (replay.nn.sequential.DiffTransformerBlock method) (replay.nn.sequential.DiffTransformerLayer method) (replay.nn.sequential.ItemTower method) (replay.nn.sequential.PositionAwareAggregator method) (replay.nn.sequential.QueryTower method) (replay.nn.sequential.SasRec method) (replay.nn.sequential.SasRecBody method) (replay.nn.sequential.SasRecTransformerLayer method) (replay.nn.sequential.TwoTower method) (replay.nn.sequential.twotower.FeaturesReader method) (replay.nn.transform.CopyTransform method) (replay.nn.transform.GroupTransform method) (replay.nn.transform.MultiClassNegativeSamplingTransform method) (replay.nn.transform.NextTokenTransform method) (replay.nn.transform.RenameTransform method) (replay.nn.transform.SequenceRollTransform method) (replay.nn.transform.TokenMaskTransform method) (replay.nn.transform.TrimTransform method) (replay.nn.transform.UniformNegativeSamplingTransform method) (replay.nn.transform.UnsqueezeTransform method) (replay.scenarios.Fallback method) (replay.splitters.cold_user_random_splitter.ColdUserRandomSplitter method) (replay.splitters.last_n_splitter.LastNSplitter method) (replay.splitters.new_users_splitter.NewUsersSplitter method) (replay.splitters.random_next_n_splitter.RandomNextNSplitter method) (replay.splitters.random_splitter.RandomSplitter method) (replay.splitters.ratio_splitter.RatioSplitter method) (replay.splitters.time_splitter.TimeSplitter method) (replay.splitters.two_stage_splitter.TwoStageSplitter method)

_get_metric_value_by_user() (replay.metrics.base_metric.Metric static method)

A

add_absent_log_cols() (replay.experimental.preprocessing.data_preparator.DataPreparator static method) add_result() (replay.metrics.Experiment method) ADMMSLIM (class in replay.experimental.models)

all_features (replay.data.FeatureSchema property) (replay.data.nn.TensorSchema property) ALSWrap (class in replay.models) AssociationRulesItemRec (class in replay.models)

B

BCE (class in replay.nn.loss) BCESampled (class in replay.nn.loss) Bert4Rec (class in replay.models.nn.sequential) Bert4RecCompiled (class in replay.models.nn.sequential.compiled) Bert4RecModel (class in replay.models.nn.sequential.bert4rec)

Bert4RecPredictionBatch (class in replay.models.nn.sequential.bert4rec) Bert4RecPredictionDataset (class in replay.models.nn.sequential.bert4rec) Bert4RecTrainingBatch (class in replay.models.nn.sequential.bert4rec) Bert4RecTrainingDataset (class in replay.models.nn.sequential.bert4rec) Bert4RecValidationBatch (class in replay.models.nn.sequential.bert4rec) Bert4RecValidationDataset (class in replay.models.nn.sequential.bert4rec)

C

cache() (replay.data.Dataset method) candidates_to_score (replay.nn.lightning.LightningModule property) cardinality (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) categorical_features (replay.data.FeatureSchema property) (replay.data.nn.TensorSchema property) CategoricalDiversity (class in replay.metrics) CategoricalEmbedding (class in replay.nn.embedding) CE (class in replay.nn.loss) CESampled (class in replay.nn.loss) check_df() (replay.experimental.preprocessing.data_preparator.DataPreparator method) ClusterRec (class in replay.models) ColdUserRandomSplitter (class in replay.splitters.cold_user_random_splitter)

column (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureSource property) columns (replay.data.FeatureSchema property) compare() (replay.metrics.Experiment method) compile() (replay.models.nn.sequential.compiled.Bert4RecCompiled class method) (replay.models.nn.sequential.compiled.SasRecCompiled class method) ComputeMetricsCallback (class in replay.nn.lightning.callback) ConcatAggregator (class in replay.nn.agg) ConsecutiveDuplicatesFilter (class in replay.preprocessing.filters) copy() (replay.data.FeatureSchema method) CopyTransform (class in replay.nn.transform) Coverage (class in replay.metrics) CQL (class in replay.experimental.models.cql) CSRConverter (class in replay.preprocessing.converter)

D

DataPreparator (class in replay.experimental.preprocessing.data_preparator) Dataset (class in replay.data) DatasetLabelEncoder (class in replay.data.dataset_utils) DDPG (class in replay.experimental.models)

DefaultAttentionMask (class in replay.nn.mask) DiffTransformerBlock (class in replay.nn.sequential) DiffTransformerLayer (class in replay.nn.sequential) drop() (replay.data.FeatureSchema method) DT4Rec (class in replay.experimental.models.dt4rec.dt4rec)

E

embedding_dim (replay.data.nn.TensorFeatureInfo property) (replay.nn.agg.ConcatAggregator property) (replay.nn.agg.SumAggregator property) (replay.nn.embedding.CategoricalEmbedding property) (replay.nn.embedding.NumericalEmbedding property)

embeddings_dim (replay.nn.embedding.SequenceEmbedding property) EmbeddingTyingHead (class in replay.nn.head) EntityDaysFilter (class in replay.preprocessing.filters) Experiment (class in replay.metrics)

F

Fallback (class in replay.scenarios) feature_hint (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) feature_schema (replay.data.Dataset property) feature_source (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) feature_sources (replay.data.nn.TensorFeatureInfo property) feature_type (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) FeatureHint (class in replay.data) FeatureInfo (class in replay.data) features (replay.data.nn.TorchSequentialBatch attribute) (replay.data.nn.TorchSequentialValidationBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecPredictionBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecTrainingBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecValidationBatch attribute) (replay.models.nn.sequential.sasrec.SasRecPredictionBatch attribute) (replay.models.nn.sequential.sasrec.SasRecTrainingBatch attribute) (replay.models.nn.sequential.sasrec.SasRecValidationBatch attribute) FeatureSchema (class in replay.data) FeatureSource (class in replay.data) FeaturesReader (class in replay.nn.sequential.twotower) FeatureType (class in replay.data) filter() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) filter_by_query_id() (replay.data.nn.PandasSequentialDataset method) filter_cold() (in module replay.preprocessing.filters) fit() (replay.data.dataset_utils.DatasetLabelEncoder method) (replay.data.nn.SequenceTokenizer method) (replay.experimental.preprocessing.data_preparator.Indexer method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.models.Recommender method) fit_predict() (replay.models.Recommender method) fit_transform() (replay.data.dataset_utils.DatasetLabelEncoder method) (replay.data.nn.SequenceTokenizer method)

forward() (replay.models.nn.sequential.Bert4Rec method) (replay.models.nn.sequential.bert4rec.Bert4RecModel method) (replay.models.nn.sequential.SasRec method) (replay.models.nn.sequential.sasrec.SasRecModel method) (replay.nn.agg.ConcatAggregator method) (replay.nn.agg.SumAggregator method) (replay.nn.attention.MultiHeadDifferentialAttention method) (replay.nn.embedding.CategoricalEmbedding method) (replay.nn.embedding.NumericalEmbedding method) (replay.nn.embedding.SequenceEmbedding method) (replay.nn.ffn.PointWiseFeedForward method) (replay.nn.ffn.SwiGLU method) (replay.nn.ffn.SwiGLUEncoder method) (replay.nn.head.EmbeddingTyingHead method) (replay.nn.lightning.LightningModule method) (replay.nn.loss.BCE method) (replay.nn.loss.BCESampled method) (replay.nn.loss.CE method) (replay.nn.loss.CESampled method) (replay.nn.loss.LogInCE method) (replay.nn.loss.LogInCESampled method) (replay.nn.loss.LogOutCE method) (replay.nn.sequential.DiffTransformerBlock method) (replay.nn.sequential.DiffTransformerLayer method) (replay.nn.sequential.ItemTower method) (replay.nn.sequential.PositionAwareAggregator method) (replay.nn.sequential.QueryTower method) (replay.nn.sequential.SasRec method) (replay.nn.sequential.SasRecBody method) (replay.nn.sequential.SasRecTransformerLayer method) (replay.nn.sequential.TwoTower method) forward_step() (replay.models.nn.sequential.bert4rec.Bert4RecModel method) (replay.models.nn.sequential.sasrec.SasRecModel method) from_params() (replay.nn.sequential.TwoTower class method)

G

get() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) get_all_query_ids() (replay.data.nn.PandasSequentialDataset method) get_encoder() (replay.data.dataset_utils.DatasetLabelEncoder method) get_features() (replay.models.Recommender method) get_item_recency() (in module replay.utils.time) get_item_weights() (replay.nn.embedding.SequenceEmbedding method) get_logits() (replay.models.nn.sequential.bert4rec.Bert4RecModel method) (replay.models.nn.sequential.sasrec.SasRecModel method) get_max_sequence_length() (replay.data.nn.PandasSequentialDataset method) get_nearest_items() (replay.models.AssociationRulesItemRec method) get_query_embeddings() (replay.models.nn.sequential.bert4rec.Bert4RecModel method) (replay.models.nn.sequential.sasrec.SasRecModel method) get_query_id() (replay.data.nn.PandasSequentialDataset method)

get_result() (replay.nn.lightning.callback.HiddenStatesCallback method) (replay.nn.lightning.callback.PandasTopItemsCallback method) (replay.nn.lightning.callback.PolarsTopItemsCallback method) (replay.nn.lightning.callback.SparkTopItemsCallback method) (replay.nn.lightning.callback.TorchTopItemsCallback method) get_schema() (in module replay.data) get_sequence() (replay.data.nn.PandasSequentialDataset method) get_sequence_by_query_id() (replay.data.nn.PandasSequentialDataset method) get_sequence_length() (replay.data.nn.PandasSequentialDataset method) get_spark_session() (in module replay.utils.session_handler) GlobalDaysFilter (class in replay.preprocessing.filters) ground_truth (replay.data.nn.TorchSequentialValidationBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecValidationBatch attribute) (replay.models.nn.sequential.sasrec.SasRecValidationBatch attribute) GroupTransform (class in replay.nn.transform)

H

HiddenStatesCallback (class in replay.nn.lightning.callback)

HierarchicalRecommender (class in replay.experimental.models) HitRate (class in replay.metrics)

I

ImplicitWrap (class in replay.experimental.models) index (replay.data.nn.TensorFeatureSource property) Indexer (class in replay.experimental.preprocessing.data_preparator) InferenceOutput (class in replay.nn.output) interaction_features (replay.data.FeatureSchema property) InteractionEntriesFilter (class in replay.preprocessing.filters) interactions (replay.data.Dataset property) interactions_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) interactions_rating_column (replay.data.FeatureSchema property) interactions_rating_features (replay.data.FeatureSchema property) interactions_timestamp_column (replay.data.FeatureSchema property) interactions_timestamp_features (replay.data.FeatureSchema property) inverse_transform() (replay.experimental.preprocessing.data_preparator.Indexer method) is_cat (replay.data.nn.TensorFeatureInfo property) is_categorical_encoded (replay.data.Dataset property) is_list (replay.data.nn.TensorFeatureInfo property) is_num (replay.data.nn.TensorFeatureInfo property) is_seq (replay.data.nn.TensorFeatureInfo property)

item() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) item_count (replay.data.Dataset property) item_distribution() (in module replay.utils.distributions) item_features (replay.data.Dataset property) (replay.data.FeatureSchema property) item_features_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) item_id_column (replay.data.FeatureSchema property) item_id_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) item_id_feature (replay.data.FeatureSchema property) item_id_feature_name (replay.data.nn.TensorSchema property) item_id_features (replay.data.nn.TensorSchema property) item_ids (replay.data.Dataset property) ItemKNN (class in replay.models) items() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) ItemTower (class in replay.nn.sequential)

K

keep_common_query_ids() (replay.data.nn.PandasSequentialDataset static method) keys() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method)

KFolds() (in module replay.splitters.k_folds) KLUCB (class in replay.models)

L

labels (replay.models.nn.sequential.bert4rec.Bert4RecTrainingBatch attribute) (replay.models.nn.sequential.sasrec.SasRecTrainingBatch attribute) labels_padding_mask (replay.models.nn.sequential.sasrec.SasRecTrainingBatch attribute) LastNSplitter (class in replay.splitters.last_n_splitter) LightFMWrap (class in replay.experimental.models.lightfm_wrap) LightningModule (class in replay.nn.lightning) LinUCB (class in replay.models) load() (in module replay.utils.model_handler) (replay.data.Dataset class method) (replay.data.nn.PandasSequentialDataset class method) (replay.data.nn.SequenceTokenizer class method)

logger (replay.experimental.preprocessing.data_preparator.DataPreparator property) LogInCE (class in replay.nn.loss) LogInCESampled (class in replay.nn.loss) LogOutCE (class in replay.nn.loss) LowRatingFilter (class in replay.preprocessing.filters)

M

make_default_sasrec_transforms() (in module replay.nn.transform.template) make_default_twotower_transforms() (in module replay.nn.transform.template) MAP (class in replay.metrics) merge_subsets() (in module replay.preprocessing.utils) Metric (class in replay.metrics.base_metric) MinCountFilter (class in replay.preprocessing.filters) module replay.data replay.data.nn replay.experimental.scenarios.obp_wrapper replay.metrics replay.models replay.preprocessing replay.preprocessing.filters replay.preprocessing.utils replay.scenarios replay.splitters

MRR (class in replay.metrics) MultiClassNegativeSamplingTransform (class in replay.nn.transform) MultiHeadDifferentialAttention (class in replay.nn.attention) MultVAE (class in replay.experimental.models)

N

name (replay.data.nn.TensorFeatureInfo property) names (replay.data.nn.TensorSchema property) NDCG (class in replay.metrics) NeuralTS (class in replay.experimental.models) NeuroMF (class in replay.experimental.models) NewUsersSplitter (class in replay.splitters.new_users_splitter)

NextTokenTransform (class in replay.nn.transform) Novelty (class in replay.metrics) numerical_features (replay.data.FeatureSchema property) (replay.data.nn.TensorSchema property) NumericalEmbedding (class in replay.nn.embedding) NumInteractionsFilter (class in replay.preprocessing.filters)

O

OBPOfflinePolicyLearner (class in replay.experimental.scenarios.obp_wrapper) OfflineMetrics (class in replay.metrics) on_prediction() (replay.nn.lightning.postprocessor.PostprocessorBase method) (replay.nn.lightning.postprocessor.SeenItemsFilter method) on_validation() (replay.nn.lightning.postprocessor.PostprocessorBase method) (replay.nn.lightning.postprocessor.SeenItemsFilter method)

optimize() (in module replay.models.base_rec.BaseRecommender) (replay.experimental.scenarios.obp_wrapper.OBPOfflinePolicyLearner method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.scenarios.Fallback method)

P

Padder (class in replay.experimental.preprocessing.padder) padding_mask (replay.data.nn.TorchSequentialBatch attribute) (replay.data.nn.TorchSequentialValidationBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecPredictionBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecTrainingBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecValidationBatch attribute) (replay.models.nn.sequential.sasrec.SasRecPredictionBatch attribute) (replay.models.nn.sequential.sasrec.SasRecTrainingBatch attribute) (replay.models.nn.sequential.sasrec.SasRecValidationBatch attribute) padding_value (replay.data.nn.TensorFeatureInfo property) PandasSequentialDataset (class in replay.data.nn) PandasTopItemsCallback (class in replay.nn.lightning.callback) ParquetDataset (class in replay.data.nn.parquet) ParquetModule (class in replay.data.nn) persist() (replay.data.Dataset method)

PointWiseFeedForward (class in replay.nn.ffn) PolarsTopItemsCallback (class in replay.nn.lightning.callback) PopRec (class in replay.models) PositionAwareAggregator (class in replay.nn.sequential) PostprocessorBase (class in replay.nn.lightning.postprocessor) Precision (class in replay.metrics) predict() (replay.experimental.scenarios.obp_wrapper.OBPOfflinePolicyLearner method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.models.nn.sequential.Bert4Rec method) (replay.models.nn.sequential.bert4rec.Bert4RecModel method) (replay.models.nn.sequential.compiled.Bert4RecCompiled method) (replay.models.nn.sequential.compiled.SasRecCompiled method) (replay.models.nn.sequential.SasRec method) (replay.models.nn.sequential.sasrec.SasRecModel method) (replay.models.Recommender method) predict_pairs() (replay.models.Recommender method)

Q

QuantileItemsFilter (class in replay.preprocessing.filters) query_and_item_id_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) query_count (replay.data.Dataset property) query_features (replay.data.Dataset property) (replay.data.FeatureSchema property) query_features_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) query_id (replay.data.nn.TorchSequentialBatch attribute) (replay.data.nn.TorchSequentialValidationBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecPredictionBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecTrainingBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecValidationBatch attribute) (replay.models.nn.sequential.sasrec.SasRecPredictionBatch attribute) (replay.models.nn.sequential.sasrec.SasRecTrainingBatch attribute) (replay.models.nn.sequential.sasrec.SasRecValidationBatch attribute)

query_id_column (replay.data.FeatureSchema property) query_id_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) query_id_feature (replay.data.FeatureSchema property) query_id_feature_name (replay.data.nn.TensorSchema property) query_id_features (replay.data.nn.TensorSchema property) query_ids (replay.data.Dataset property) QueryPopRec (class in replay.models) QueryTower (class in replay.nn.sequential)

R

RandomNextNSplitter (class in replay.splitters.random_next_n_splitter) RandomRec (class in replay.models) RandomSplitter (class in replay.splitters.random_splitter) rating_feature_name (replay.data.nn.TensorSchema property) rating_features (replay.data.nn.TensorSchema property) RatioSplitter (class in replay.splitters.ratio_splitter) read_as_spark_df() (replay.experimental.preprocessing.data_preparator.DataPreparator static method) Recall (class in replay.metrics) Recommender (class in replay.models) RenameTransform (class in replay.nn.transform) replay.data module replay.data.nn module replay.experimental.scenarios.obp_wrapper module

replay.metrics module replay.models module replay.preprocessing module replay.preprocessing.filters module replay.preprocessing.utils module replay.scenarios module replay.splitters module reset_cardinality() (replay.data.FeatureInfo method) RocAuc (class in replay.metrics)

S

SasRec (class in replay.models.nn.sequential) (class in replay.nn.sequential) SasRecBody (class in replay.nn.sequential) SasRecCompiled (class in replay.models.nn.sequential.compiled) SasRecModel (class in replay.models.nn.sequential.sasrec) SasRecPredictionBatch (class in replay.models.nn.sequential.sasrec) SasRecPredictionDataset (class in replay.models.nn.sequential.sasrec) SasRecTrainingBatch (class in replay.models.nn.sequential.sasrec) SasRecTrainingDataset (class in replay.models.nn.sequential.sasrec) SasRecTransformerLayer (class in replay.nn.sequential) SasRecValidationBatch (class in replay.models.nn.sequential.sasrec) SasRecValidationDataset (class in replay.models.nn.sequential.sasrec) save() (in module replay.utils.model_handler) (replay.data.Dataset method) (replay.data.nn.SequenceTokenizer method) ScalaALSWrap (class in replay.experimental.models) ScalableCrossEntropyLoss (class in replay.models.nn.loss) SCEParams (class in replay.models.nn.loss) schema (replay.data.nn.PandasSequentialDataset property)

SeenItemsFilter (class in replay.nn.lightning.postprocessor) SequenceEmbedding (class in replay.nn.embedding) SequenceGenerator (class in replay.experimental.preprocessing.sequence_generator) SequenceRollTransform (class in replay.nn.transform) SequenceTokenizer (class in replay.data.nn) sequential_features (replay.data.nn.TensorSchema property) Sessionizer (class in replay.preprocessing.sessionizer) SLIM (class in replay.models) smoothe_time() (in module replay.utils.time) source (replay.data.nn.TensorFeatureSource property) SparkTopItemsCallback (class in replay.nn.lightning.callback) split() (in module replay.splitters.base_splitter.Splitter) State (class in replay.utils.session_handler) subset() (replay.data.Dataset method) (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) SumAggregator (class in replay.nn.agg) Surprisal (class in replay.metrics) SwiGLU (class in replay.nn.ffn) SwiGLUEncoder (class in replay.nn.ffn)

T

tensor_dim (replay.data.nn.TensorFeatureInfo property) tensor_schema (replay.data.nn.SequenceTokenizer property) TensorFeatureInfo (class in replay.data.nn) TensorFeatureSource (class in replay.data.nn) TensorSchema (class in replay.data.nn) ThompsonSampling (class in replay.models) TimePeriodFilter (class in replay.preprocessing.filters) TimeSplitter (class in replay.splitters.time_splitter) timestamp_feature_name (replay.data.nn.TensorSchema property) timestamp_features (replay.data.nn.TensorSchema property) to_pandas() (replay.data.Dataset method) to_polars() (replay.data.Dataset method) to_spark() (replay.data.Dataset method) TokenMaskTransform (class in replay.nn.transform) tokens_mask (replay.models.nn.sequential.bert4rec.Bert4RecPredictionBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecTrainingBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecValidationBatch attribute) TorchSequentialBatch (class in replay.data.nn) TorchSequentialDataset (class in replay.data.nn)

TorchSequentialValidationBatch (class in replay.data.nn) TorchSequentialValidationDataset (class in replay.data.nn) TorchTopItemsCallback (class in replay.nn.lightning.callback) train (replay.data.nn.TorchSequentialValidationBatch attribute) (replay.models.nn.sequential.bert4rec.Bert4RecValidationBatch attribute) (replay.models.nn.sequential.sasrec.SasRecValidationBatch attribute) TrainOutput (class in replay.nn.output) transform() (replay.data.dataset_utils.DatasetLabelEncoder method) (replay.data.nn.SequenceTokenizer method) (replay.experimental.preprocessing.data_preparator.DataPreparator method) (replay.experimental.preprocessing.data_preparator.Indexer method) (replay.experimental.preprocessing.padder.Padder method) (replay.experimental.preprocessing.sequence_generator.SequenceGenerator method) (replay.preprocessing.converter.CSRConverter method) (replay.preprocessing.sessionizer.Sessionizer method) TrimTransform (class in replay.nn.transform) TwoStageSplitter (class in replay.splitters.two_stage_splitter) TwoStagesScenario (class in replay.experimental.scenarios) TwoTower (class in replay.nn.sequential) TwoTowerBody (class in replay.nn.sequential)

U

UCB (class in replay.models) ULinUCB (class in replay.experimental.models) Unexpectedness (class in replay.metrics)

UniformNegativeSamplingTransform (class in replay.nn.transform) unpersist() (replay.data.Dataset method) UnsqueezeTransform (class in replay.nn.transform)

V

values() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method)

W

weight (replay.nn.embedding.CategoricalEmbedding property) (replay.nn.embedding.NumericalEmbedding property)

Wilson (class in replay.models) Word2VecRec (class in replay.models)