Fix testing for mac OS (#399)

* fix test for MacOS

* formatting

* fix pkg names

Author: Borda

.travis.yml

@@ -35,7 +35,7 @@ matrix:
       addons:
         homebrew:
           # update: true
-          packages: python3
+          packages: python3.6
       before_install:
         - pip3 install virtualenv
         - virtualenv -p python3 ~/venv

MANIFEST.in

@@ -16,9 +16,9 @@ exclude *.svg
 recursive-include pytorch_lightning *.py
 
 # include examples
-recursive-include examples *.py
-recursive-include examples *.md
-recursive-include examples *.sh
+recursive-include pl_examples *.py
+recursive-include pl_examples *.md
+recursive-include pl_examples *.sh
 
 # exclude tests from package
 recursive-exclude tests *

pl_examples/domain_templates/gan.py

@@ -136,7 +136,8 @@ def training_step(self, batch, batch_nb, optimizer_i):
 
             # how well can it label as fake?
             fake = torch.zeros(imgs.size(0), 1)
-            fake_loss = self.adversarial_loss(self.discriminator(self.generated_imgs.detach()), fake)
+            fake_loss = self.adversarial_loss(
+                self.discriminator(self.generated_imgs.detach()), fake)
 
             # discriminator loss is the average of these
             d_loss = (real_loss + fake_loss) / 2
@@ -146,8 +147,6 @@ def training_step(self, batch, batch_nb, optimizer_i):
                 'progress_bar': tqdm_dict,
                 'log': tqdm_dict
             })
-
-
             return output
 
     def configure_optimizers(self):
@@ -200,9 +199,12 @@ def main(hparams):
     parser = ArgumentParser()
     parser.add_argument("--batch_size", type=int, default=64, help="size of the batches")
     parser.add_argument("--lr", type=float, default=0.0002, help="adam: learning rate")
-    parser.add_argument("--b1", type=float, default=0.5, help="adam: decay of first order momentum of gradient")
-    parser.add_argument("--b2", type=float, default=0.999, help="adam: decay of first order momentum of gradient")
-    parser.add_argument("--latent_dim", type=int, default=100, help="dimensionality of the latent space")
+    parser.add_argument("--b1", type=float, default=0.5,
+                        help="adam: decay of first order momentum of gradient")
+    parser.add_argument("--b2", type=float, default=0.999,
+                        help="adam: decay of first order momentum of gradient")
+    parser.add_argument("--latent_dim", type=int, default=100,
+                        help="dimensionality of the latent space")
 
     hparams = parser.parse_args()
 

tox.ini

@@ -35,7 +35,7 @@ commands =
     check-manifest --ignore tox.ini
     python setup.py check -m -s
     flake8 .
-    coverage run --source pytorch_lightning -m py.test pytorch_lightning tests examples -v --doctest-modules
+    coverage run --source pytorch_lightning -m py.test pytorch_lightning tests pl_examples -v --doctest-modules
 
 [flake8]
 exclude = .tox,*.egg,build,temp,examples/*