[test] added unit tests for DCGAN

bob/learn/pytorch/test/test.py

@@ -32,6 +32,21 @@ def test_architectures():
   output, emdedding = net.forward(t)
   assert output.shape == torch.Size([1, 20])
   assert emdedding.shape == torch.Size([1, 512])
+
+  # DCGAN
+  d = numpy.random.rand(1, 3, 64, 64).astype("float32")
+  t = torch.from_numpy(d)
+  from ..architectures import DCGAN_discriminator
+  discriminator = DCGAN_discriminator(1)
+  output = discriminator.forward(t)
+  assert output.shape == torch.Size([1])
+
+  g = numpy.random.rand(1, 100, 1, 1).astype("float32")
+  t = torch.from_numpy(g)
+  from ..architectures import DCGAN_generator
+  generator = DCGAN_generator(1)
+  output = generator.forward(t)
+  assert output.shape == torch.Size([1, 3, 64, 64])
  
 
 def test_transforms():
@@ -85,7 +100,7 @@ class DummyDataSet(Dataset):
     return sample 
 
 
-def test_trainer():
+def test_CNNtrainer():
 
   from ..architectures import CNN8
   net = CNN8(20)
@@ -100,3 +115,37 @@ def test_trainer():
   assert os.path.isfile('model_1_0.pth')
 
   os.remove('model_1_0.pth')
+
+
+class DummyDataSetGAN(Dataset):
+  def __init__(self):
+    pass
+  def __len__(self):
+    return 100
+  def __getitem__(self, idx):
+    data =  numpy.random.rand(3, 64, 64).astype("float32")
+    sample = {'image': torch.from_numpy(data)}
+    return sample 
+
+def test_DCGANtrainer():
+
+  from ..architectures import DCGAN_generator
+  from ..architectures import DCGAN_discriminator
+  g = DCGAN_generator(1)
+  d = DCGAN_discriminator(1)
+
+  dataloader = torch.utils.data.DataLoader(DummyDataSetGAN(), batch_size=32, shuffle=True)
+  
+  from ..trainers import DCGANTrainer
+  trainer = DCGANTrainer(g, d, batch_size=32, noise_dim=100, use_gpu=False, verbosity_level=2)
+  trainer.train(dataloader, n_epochs=1, output_dir='.')
+
+  import os
+  assert os.path.isfile('fake_samples_epoch_000.png')
+  assert os.path.isfile('netD_epoch_0.pth')
+  assert os.path.isfile('netG_epoch_0.pth')
+
+  os.remove('fake_samples_epoch_000.png')
+  os.remove('netD_epoch_0.pth')
+  os.remove('netG_epoch_0.pth')
+