deepctr_torch.inputs module

Author:

Weichen Shen,wcshen1994@163.com

class deepctr_torch.inputs.DenseFeat

class deepctr_torch.inputs.SparseFeat

class deepctr_torch.inputs.VarLenSparseFeat

deepctr_torch.inputs.embedding_lookup(X, sparse_embedding_dict, sparse_input_dict, sparse_feature_columns, return_feat_list=(), mask_feat_list=(), to_list=False)

Args:

X: input Tensor [batch_size x hidden_dim] sparse_embedding_dict: nn.ModuleDict, {embedding_name: nn.Embedding} sparse_input_dict: OrderedDict, {feature_name:(start, start+dimension)} sparse_feature_columns: list, sparse features return_feat_list: list, names of feature to be returned, defualt () -> return all features mask_feat_list, list, names of feature to be masked in hash transform

Return:

group_embedding_dict: defaultdict(list)