From c13dba86b2dbe581353b72602d7fa6e40991964c Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期三, 27 九月 2017 04:11:23 +0800
Subject: [PATCH] next
---
code/train_preangles.py | 10 ++++++----
1 files changed, 6 insertions(+), 4 deletions(-)
diff --git a/code/train_preangles.py b/code/train_preangles.py
index 6622d3f..4752aef 100644
--- a/code/train_preangles.py
+++ b/code/train_preangles.py
@@ -125,6 +125,8 @@
if args.dataset == 'Pose_300W_LP':
pose_dataset = datasets.Pose_300W_LP(args.data_dir, args.filename_list, transformations)
+ if args.dataset == 'Pose_300W_LP_random_ds':
+ pose_dataset = datasets.Pose_300W_LP_random_ds(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFLW2000':
pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'BIWI':
@@ -161,10 +163,10 @@
print 'Ready to train network.'
print 'First phase of training.'
for epoch in range(num_epochs):
- start = time.time()
+ # start = time.time()
for i, (images, labels, cont_labels, name) in enumerate(train_loader):
- print i
- print 'start: ', time.time() - start
+ # print i
+ # print 'start: ', time.time() - start
images = Variable(images).cuda(gpu)
label_yaw = Variable(labels[:,0]).cuda(gpu)
label_pitch = Variable(labels[:,1]).cuda(gpu)
@@ -207,7 +209,7 @@
torch.autograd.backward(loss_seq, grad_seq)
optimizer.step()
- print 'end: ', time.time() - start
+ # print 'end: ', time.time() - start
if (i+1) % 100 == 0:
print ('Epoch [%d/%d], Iter [%d/%d] Losses: Yaw %.4f, Pitch %.4f, Roll %.4f'
--
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