From e65c915e5bdbcca56b37aa13bcff4911beffbe37 Mon Sep 17 00:00:00 2001
From: hyhmrright <hyhmrright@163.com>
Date: 星期五, 31 五月 2019 13:13:35 +0800
Subject: [PATCH] change py2 to py3
---
code/train_resnet50_regression.py | 10 +++++-----
1 files changed, 5 insertions(+), 5 deletions(-)
diff --git a/code/train_resnet50_regression.py b/code/train_resnet50_regression.py
index 04d27c7..da4a047 100644
--- a/code/train_resnet50_regression.py
+++ b/code/train_resnet50_regression.py
@@ -87,7 +87,7 @@
model = hopenet.ResNet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 3)
load_filtered_state_dict(model, model_zoo.load_url('https://download.pytorch.org/models/resnet50-19c8e357.pth'))
- print 'Loading data.'
+ print('Loading data.')
transformations = transforms.Compose([transforms.Scale(240),
transforms.RandomCrop(224), transforms.ToTensor(),
@@ -108,7 +108,7 @@
elif args.dataset == 'AFW':
pose_dataset = datasets.AFW(args.data_dir, args.filename_list, transformations)
else:
- print 'Error: not a valid dataset name'
+ print('Error: not a valid dataset name')
sys.exit()
train_loader = torch.utils.data.DataLoader(dataset=pose_dataset,
batch_size=batch_size,
@@ -123,8 +123,8 @@
{'params': get_fc_params(model), 'lr': args.lr * 5}],
lr = args.lr)
- print 'Ready to train network.'
- print 'First phase of training.'
+ print('Ready to train network.')
+ print('First phase of training.')
for epoch in range(num_epochs):
for i, (images, labels, cont_labels, name) in enumerate(train_loader):
images = Variable(images).cuda(gpu)
@@ -143,6 +143,6 @@
# Save models at numbered epochs.
if epoch % 1 == 0 and epoch < num_epochs:
- print 'Taking snapshot...'
+ print('Taking snapshot...')
torch.save(model.state_dict(),
'output/snapshots/' + args.output_string + '_epoch_'+ str(epoch+1) + '.pkl')
--
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