diff options
Diffstat (limited to 'dnn/torch/lossgen/train_lossgen.py')
| -rw-r--r-- | dnn/torch/lossgen/train_lossgen.py | 13 |
1 files changed, 8 insertions, 5 deletions
diff --git a/dnn/torch/lossgen/train_lossgen.py b/dnn/torch/lossgen/train_lossgen.py index 26e0f012..4dda3190 100644 --- a/dnn/torch/lossgen/train_lossgen.py +++ b/dnn/torch/lossgen/train_lossgen.py @@ -27,9 +27,11 @@ class LossDataset(torch.utils.data.Dataset): return self.nb_sequences def __getitem__(self, index): - r0 = np.random.normal(scale=.02, size=(1,1)).astype('float32') - r1 = np.random.normal(scale=.02, size=(self.sequence_length,1)).astype('float32') - return [self.loss[index, :, :], self.perc[index, :, :]+r0+r1] + r0 = np.random.normal(scale=.1, size=(1,1)).astype('float32') + r1 = np.random.normal(scale=.1, size=(self.sequence_length,1)).astype('float32') + perc = self.perc[index, :, :] + perc = perc + (r0+r1)*perc*(1-perc) + return [self.loss[index, :, :], perc] adam_betas = [0.8, 0.98] @@ -61,7 +63,7 @@ scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer=optimizer, lr_lambda=lam if __name__ == '__main__': model.to(device) - + states = None for epoch in range(1, epochs + 1): running_loss = 0 @@ -73,7 +75,8 @@ if __name__ == '__main__': loss = loss.to(device) perc = perc.to(device) - out, _ = model(loss, perc) + out, states = model(loss, perc, states=states) + states = [state.detach() for state in states] out = torch.sigmoid(out[:,:-1,:]) target = loss[:,1:,:] |