################
# EXAMPLE CODE #
################
# setup the mockingjay model
options = {
'ckpt_file':
'result/result_mockingjay/mockingjay_libri_sd1337_MelBase/mockingjay-500000.ckpt',
'load_pretrain': 'True',
'no_grad': 'False',
'dropout': 'default'
}
model = MOCKINGJAY(options=options, inp_dim=160)
# setup your downstream class model
classifier = example_classifier(input_dim=768, hidden_dim=128,
class_num=2).cuda()
# construct the Mockingjay optimizer
params = list(model.named_parameters()) + list(classifier.named_parameters())
optimizer = get_mockingjay_optimizer(params=params,
lr=4e-3,
warmup_proportion=0.7,
training_steps=50000)
# forward
example_inputs = torch.zeros(
1200, 3,
160) # A batch of spectrograms: (time_step, batch_size, dimension)
reps = model(example_inputs) # returns: (time_step, batch_size, hidden_size)
reps = reps.permute(1, 0,
2) # change to: (batch_size, time_step, feature_size)
def __init__(self, options):
super(Model, self).__init__()
self.model = MOCKINGJAY(options=options, inp_dim=160)
self.classifier = example_classifier(input_dim=768, hidden_dim=128, class_num=133)