From 46b552e075936f58796bdcc591d6a6034894bde0 Mon Sep 17 00:00:00 2001 From: Chintan Shah Date: Tue, 8 Oct 2019 02:44:13 -0400 Subject: [PATCH] updated eps value --- model/pytorch/dcrnn_supervisor.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/model/pytorch/dcrnn_supervisor.py b/model/pytorch/dcrnn_supervisor.py index 481c5da..8ce0224 100644 --- a/model/pytorch/dcrnn_supervisor.py +++ b/model/pytorch/dcrnn_supervisor.py @@ -124,11 +124,11 @@ class DCRNNSupervisor: def _train(self, base_lr, steps, patience=50, epochs=100, lr_decay_ratio=0.1, log_every=1, save_model=1, - test_every_n_epochs=10, **kwargs): + test_every_n_epochs=10, epsilon=1e-8, **kwargs): # steps is used in learning rate - will see if need to use it? min_val_loss = float('inf') wait = 0 - optimizer = torch.optim.Adam(self.dcrnn_model.parameters(), lr=base_lr) + optimizer = torch.optim.Adam(self.dcrnn_model.parameters(), lr=base_lr, eps=epsilon) lr_scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer, milestones=steps, gamma=lr_decay_ratio) @@ -159,7 +159,7 @@ class DCRNNSupervisor: if batches_seen == 0: # this is a workaround to accommodate dynamically registered parameters in DCGRUCell - optimizer = torch.optim.Adam(self.dcrnn_model.parameters(), lr=base_lr) + optimizer = torch.optim.Adam(self.dcrnn_model.parameters(), lr=base_lr, eps=epsilon) loss = self._compute_loss(y, output)