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Added device option to Wasserstein #3

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Added device option to Wasserstein #3

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11 changes: 6 additions & 5 deletions layers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,11 +20,12 @@ class SinkhornDistance(nn.Module):
- Input: :math:`(N, P_1, D_1)`, :math:`(N, P_2, D_2)`
- Output: :math:`(N)` or :math:`()`, depending on `reduction`
"""
def __init__(self, eps, max_iter, reduction='none'):
def __init__(self, eps, max_iter, device, reduction='none'):
super(SinkhornDistance, self).__init__()
self.eps = eps
self.max_iter = max_iter
self.reduction = reduction
self.device = device

def forward(self, x, y):
# The Sinkhorn algorithm takes as input three variables :
Expand All @@ -38,12 +39,12 @@ def forward(self, x, y):

# both marginals are fixed with equal weights
mu = torch.empty(batch_size, x_points, dtype=torch.float,
requires_grad=False).fill_(1.0 / x_points).squeeze()
requires_grad=False, device=self.device).fill_(1.0 / x_points).squeeze()
nu = torch.empty(batch_size, y_points, dtype=torch.float,
requires_grad=False).fill_(1.0 / y_points).squeeze()
requires_grad=False, device=self.device).fill_(1.0 / y_points).squeeze()

u = torch.zeros_like(mu)
v = torch.zeros_like(nu)
u = torch.zeros_like(mu, device=self.device)
v = torch.zeros_like(nu, device=self.device)
# To check if algorithm terminates because of threshold
# or max iterations reached
actual_nits = 0
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