Configuration

generate_config generate all the configuration that can be used in learning and inference.

utils.generate_config(
       drug_encoding,
       target_encoding,
       result_folder = "./result/",
       input_dim_drug = 1024,
       input_dim_protein = 8420,
       hidden_dim_drug = 256,
       hidden_dim_protein = 256,
       cls_hidden_dims = [1024, 1024, 512],
       mlp_hidden_dims_drug = [1024, 256, 64],
       mlp_hidden_dims_target = [1024, 256, 64],
       batch_size = 256,
       train_epoch = 10,
       test_every_X_epoch = 20,
       LR = 1e-4,
       transformer_emb_size_drug = 128,
       transformer_intermediate_size_drug = 512,
       transformer_num_attention_heads_drug = 8,
       transformer_n_layer_drug = 8,
       transformer_emb_size_target = 128,
       transformer_intermediate_size_target = 512,
       transformer_num_attention_heads_target = 8,
       transformer_n_layer_target = 4,
       transformer_dropout_rate = 0.1,
       transformer_attention_probs_dropout = 0.1,
       transformer_hidden_dropout_rate = 0.1,
       mpnn_hidden_size = 50,
       mpnn_depth = 3,
       cnn_drug_filters = [32,64,96],
       cnn_drug_kernels = [4,6,8],
       cnn_target_filters = [32,64,96],
       cnn_target_kernels = [4,8,12],
       rnn_Use_GRU_LSTM_drug = 'GRU',
       rnn_drug_hid_dim = 64,
       rnn_drug_n_layers = 2,
       rnn_drug_bidirectional = True,
       rnn_Use_GRU_LSTM_target = 'GRU',
       rnn_target_hid_dim = 64,
       rnn_target_n_layers = 2,
       rnn_target_bidirectional = True
       )

• drug_encoding (str) - Encoder mode for drug. It can be “transformer”, “MPNN”, “CNN”, “CNN_RNN” …,

• target_encoding (str) - Encoder mode for protein. It can be “transformer”, “CNN”, “CNN_RNN” …,

• input_dim_drug (int) - Dimension of input drug feature.

• input_dim_protein (int) - Dimension of input protein feature.

• hidden_dim_drug (int) - Dimension of hidden layer of drug feature.

• hidden_dim_protein (int) - Dimension of hidden layer of protein feature.

• batch_size (int) - batch size

• train_epoch (int) - training epoch

• test_every_X_epoch (int) - test every X epochs

• LR (float) - Learning rate.

• cls_hidden_dims (list of int) - hidden dimensions of classifier.

• mlp_hidden_dims_drug (list of int) - hidden dimension of MLP when encoding drug.

• mlp_hidden_dims_target (list of int) - hidden dimension of MLP when encoding protein.

• transformer_emb_size_drug (int) - embedding size of transformer when encoding drug.

• transformer_intermediate_size_drug (int) -

• transformer_num_attention_heads_drug (int) -

• transformer_n_layer_drug (int) -

• transformer_emb_size_target (int) -

• transformer_intermediate_size_target (int) -

• transformer_num_attention_heads_target (int) -

• transformer_n_layer_target (int) -

• transformer_dropout_rate (float) -