update dataset mode

1 files changed, 0 insertions, 51 deletions

diff --git a/models/one_direction_test_model.py b/models/one_direction_test_model.py
deleted file mode 100644
index d4f6442..0000000
--- a/models/one_direction_test_model.py
+++ /dev/null
@@ -1,51 +0,0 @@
-from torch.autograd import Variable
-from collections import OrderedDict
-import util.util as util
-from .base_model import BaseModel
-from . import networks
-
-
-class OneDirectionTestModel(BaseModel):
-    def name(self):
-        return 'OneDirectionTestModel'
-
-    def initialize(self, opt):
-        BaseModel.initialize(self, opt)
-
-        nb = opt.batchSize
-        size = opt.fineSize
-        self.input_A = self.Tensor(nb, opt.input_nc, size, size)
-
-        assert(not self.isTrain)
-        self.netG_A = networks.define_G(opt.input_nc, opt.output_nc,
-                                        opt.ngf, opt.which_model_netG,
-                                        opt.norm, opt.use_dropout,
-                                        self.gpu_ids)
-        which_epoch = opt.which_epoch
-        #AtoB = self.opt.which_direction == 'AtoB'
-        #which_network = 'G_A' if AtoB else 'G_B'
-        self.load_network(self.netG_A, 'G', which_epoch)
-
-        print('---------- Networks initialized -------------')
-        networks.print_network(self.netG_A)
-        print('-----------------------------------------------')
-
-    def set_input(self, input):
-        AtoB = self.opt.which_direction == 'AtoB'
-        input_A = input['A' if AtoB else 'B']
-        self.input_A.resize_(input_A.size()).copy_(input_A)
-        self.image_paths = input['A_paths' if AtoB else 'B_paths']
-
-    def test(self):
-        self.real_A = Variable(self.input_A)
-        self.fake_B = self.netG_A.forward(self.real_A)
-
-    #get image paths
-    def get_image_paths(self):
-        return self.image_paths
-
-    def get_current_visuals(self):
-        real_A = util.tensor2im(self.real_A.data)
-        fake_B = util.tensor2im(self.fake_B.data)
-        return OrderedDict([('real_A', real_A), ('fake_B', fake_B)])
-