deepcarskit.model¶
- class deepcarskit.model.context_recommender.ContextRecommender(config, dataset)¶
Bases:
recbole.model.abstract_recommender.AbstractRecommender
This is a abstract context-aware recommender. All the context-aware model should implement this class. The base context-aware recommender class provide the basic embedding function of feature fields which also contains a first-order part of feature fields.
- concat_embed_input_fields(interaction)¶
- double_tower_embed_input_fields(interaction)¶
Embed the whole feature columns in a double tower way.
- Args:
interaction (Interaction): The input data collection.
- Returns:
torch.FloatTensor: The embedding tensor of token sequence columns in the first part. torch.FloatTensor: The embedding tensor of float sequence columns in the first part. torch.FloatTensor: The embedding tensor of token sequence columns in the second part. torch.FloatTensor: The embedding tensor of float sequence columns in the second part.
- embed_float_fields(float_fields, embed=True)¶
Embed the float feature columns
- Args:
float_fields (torch.FloatTensor): The input dense tensor. shape of [batch_size, num_float_field] embed (bool): Return the embedding of columns or just the columns itself. Defaults to
True
.- Returns:
torch.FloatTensor: The result embedding tensor of float columns.
- embed_input_fields(interaction)¶
Embed the whole feature columns.
- Args:
interaction (Interaction): The input data collection.
- Returns:
torch.FloatTensor: The embedding tensor of token sequence columns. torch.FloatTensor: The embedding tensor of float sequence columns.
- embed_token_fields(token_fields)¶
Embed the token feature columns
- Args:
token_fields (torch.LongTensor): The input tensor. shape of [batch_size, num_token_field]
- Returns:
torch.FloatTensor: The result embedding tensor of token columns.
- embed_token_seq_fields(token_seq_fields, mode='mean')¶
Embed the token feature columns
- Args:
token_seq_fields (torch.LongTensor): The input tensor. shape of [batch_size, seq_len] mode (str): How to aggregate the embedding of feature in this field. default=mean
- Returns:
torch.FloatTensor: The result embedding tensor of token sequence columns.
- getContextSituationDict(interaction, context_dims)¶
- getContextSituationList(interaction, context_dims)¶
- input_type = 1¶
- training: bool¶
- type = 3¶
deepcarskit.model.layers¶
Common Layers in recommender system
- class deepcarskit.model.layers.FMFirstOrderLinear(config, dataset, output_dim=1)¶
Bases:
recbole.model.layers.FMFirstOrderLinear
Calculate the first order score of the input features. This class is a member of ContextRecommender, you can call it easily when inherit ContextRecommender.
- training: bool¶