From 7d4d80e2721d8b42c8c7d82dc1720980175576b2 Mon Sep 17 00:00:00 2001
From: 1Konny <lee.wonkwang94@gmail.com>
Date: Tue, 17 Apr 2018 10:43:55 +0900
Subject: [PATCH] add traverse
---
solver.py | 45 +++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 45 insertions(+)
diff --git a/solver.py b/solver.py
index 5c63823..a7abcdf 100644
--- a/solver.py
+++ b/solver.py
@@ -163,6 +163,51 @@ class Solver(object):
xlabel='iteration',
ylabel='kl divergence',))
+ def traverse(self):
+ import random
+
+ decoder = self.net.decode
+ encoder = self.net.encode
+ interpolation = torch.arange(-6, 6.1, 2)
+ viz = visdom.Visdom(env=self.viz_name+'/traverse', port=self.viz_port)
+
+ n_dsets = self.data_loader.dataset.__len__()
+ fixed_idx = 0
+ rand_idx = random.randint(1, n_dsets-1)
+
+ fixed_img = self.data_loader.dataset.__getitem__(fixed_idx)
+ random_img = self.data_loader.dataset.__getitem__(rand_idx)
+ fixed_img = Variable(cuda(fixed_img, self.use_cuda), volatile=True).unsqueeze(0)
+ random_img = Variable(cuda(random_img, self.use_cuda), volatile=True).unsqueeze(0)
+ zero_z = Variable(cuda(torch.zeros(1, self.z_dim, 1, 1), self.use_cuda), volatile=True)
+ random_z = Variable(cuda(torch.rand(1, self.z_dim, 1, 1), self.use_cuda), volatile=True)
+
+ src = [fixed_img, random_img, zero_z, random_z]
+ for i, vector in enumerate(src):
+ if i < 2:
+ z_ori = encoder(vector)[:, :self.z_dim]
+ else:
+ z_ori = vector
+
+ samples = []
+ for row in range(self.z_dim):
+ z = z_ori.clone()
+ for val in interpolation:
+ z[:, row] = val
+ sample = F.sigmoid(decoder(z))
+ samples.append(sample)
+ samples = torch.cat(samples, dim=0).data.cpu()
+ if i==0:
+ title = 'traverse representation from fixed image'
+ elif i==1:
+ title = 'traverse representation random image'
+ elif i==2:
+ title = 'traverse zero representation vector'
+ elif i==3:
+ title = 'traverse random gaussian representation vector'
+ title += '(iter:{})'.format(self.global_iter)
+ viz.images(samples, opts=dict(title=title), nrow=len(interpolation))
+
def net_mode(self, train):
if not isinstance(train, bool):
raise('Only bool type is supported. True or False')
--
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