6bead0ebd24db4e04d36fe42fb98cdd9280f5ee3,spotlight/sequence/representations.py,LSTMNet,__init__,#LSTMNet#,164

Before Change

        self.embedding_dim = embedding_dim

        self.item_embeddings = ScaledEmbedding(num_items, embedding_dim,
                                               sparse=sparse,
                                               padding_idx=PADDING_IDX)
        self.item_biases = ZeroEmbedding(num_items, 1, sparse=sparse,
                                         padding_idx=PADDING_IDX)

        self.lstm = nn.LSTM(batch_first=True,

After Change

        self.embedding_dim = embedding_dim

        if item_embedding_layer is not None:
            self.item_embeddings = item_embedding_layer
        else:
            self.item_embeddings = ScaledEmbedding(num_items, embedding_dim,
                                                   padding_idx=PADDING_IDX,
                                                   sparse=sparse)

        self.item_biases = ZeroEmbedding(num_items, 1, sparse=sparse,
                                         padding_idx=PADDING_IDX)

        self.lstm = nn.LSTM(batch_first=True,

Instances