DeepPurpose.models.transformer(nn.Sequential)
Transformer (Source) can be used to encode both drug and protein on SMILES.
constructor create an instance of Transformer.
__init__(self, encoding, **config)
- encoding (string, "drug" or "protein") - specify input type of the model, "drug" or "protein".
- config (kwargs, keyword arguments) - specify the parameter of transformer. The keys include
- transformer_dropout_rate (float) - dropout rate of transformer.
- input_dim_drug (int) - input dimension when encoding drug.
- transformer_emb_size_drug (int) - dimension of embedding in input layer when encoding drug.
- transformer_n_layer_drug (int) - number of layers in transformer when encoding drug.
- todo
Calling functions implement the feedforward procedure of MPNN.
forward(self, v)
- v (tuple of length 2) - input feature of transformer. v[0] (np.array) is index of atoms. v[1] (np.array) is the corresponding mask.