def build_training(model, params):
optimizer = OpenChemOptimizer(
[params['optimizer'], params['optimizer_params']], model.parameters())
lr_scheduler = OpenChemLRScheduler(
[params['lr_scheduler'], params['lr_scheduler_params']],
optimizer.optimizer)
use_cuda = params['use_cuda']
criterion = params['criterion']
if use_cuda:
criterion = criterion.cuda()
# train_loader = params['train_loader']
# val_loader = params['val_loader']
return criterion, optimizer, lr_scheduler #, train_loader, val_loader
def __init__(self, params):
super(Smiles2Label, self).__init__(params)
self.embedding = self.params['embedding']
self.embed_params = self.params['embedding_params']
self.Embedding = self.embedding(self.embed_params)
self.encoder = self.params['encoder']
self.encoder_params = self.params['encoder_params']
self.Encoder = self.encoder(self.encoder_params, self.use_cuda)
self.mlp = self.params['mlp']
self.mlp_params = self.params['mlp_params']
self.MLP = self.mlp(self.mlp_params)
self.optimizer = OpenChemOptimizer(
[self.params['optimizer'], self.params['optimizer_params']],
self.parameters())
self.scheduler = OpenChemLRScheduler(
[self.params['lr_scheduler'], self.params['lr_scheduler_params']],
self.optimizer.optimizer)