shuffle=False)
for phase in ['valid']
}
use_gpu = torch.cuda.is_available()
module = Module()
module.load_state_dict(torch.load(pretrained))
fid = open('parameters', 'wb+')
for param in module.parameters():
b = param.data.numpy()
fid.write(b)
fid.close()
if use_gpu:
module.cuda()
module = nn.DataParallel(module, gpu)
for stage in ([0] * 1):
# for epoch in range(1):
for phase in ["valid"]:
print("Testing...")
module.train(False)
for param in module.parameters():
param.requires_grad_(False)
running_dist = 0.
for batch, data in enumerate(dataloader[phase], 1):
x, t, idx = data
if use_gpu:
x = x.cuda()
