Sourcery Starbot ⭐ refactored undo76/PyTorch-GAN #1

SourceryAI · 2021-10-05T10:43:34Z

Thanks for starring sourcery-ai/sourcery ✨ 🌟 ✨

Here's your pull request refactoring your most popular Python repo.

If you want Sourcery to refactor all your Python repos and incoming pull requests install our bot.

Review changes via command line

To manually merge these changes, make sure you're on the master branch, then run:

git fetch https://github.com/sourcery-ai-bot/PyTorch-GAN master
git merge --ff-only FETCH_HEAD
git reset HEAD^

SourceryAI

Due to GitHub API limits, only the first 60 comments can be shown.

SourceryAI · 2021-10-05T10:43:35Z

implementations/aae/aae.py

 img_shape = (opt.channels, opt.img_size, opt.img_size)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 36-36 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:35Z

implementations/aae/aae.py

    sampled_z = Variable(Tensor(np.random.normal(0, 1, (mu.size(0), opt.latent_dim))))
-    z = sampled_z * std + mu
-    return z
+    return sampled_z * std + mu


Function reparameterization refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:35Z

implementations/aae/aae.py

-        z = reparameterization(mu, logvar)
-        return z
+        return reparameterization(mu, logvar)


Function Encoder.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:35Z

implementations/aae/aae.py

-        img = img_flat.view(img_flat.shape[0], *img_shape)
-        return img
+        return img_flat.view(img_flat.shape[0], *img_shape)


Function Decoder.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:35Z

implementations/aae/aae.py

-        validity = self.model(z)
-        return validity
+        return self.model(z)


Function Discriminator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:37Z

implementations/ccgan/ccgan.py

 print(opt)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 39-39 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:37Z

implementations/ccgan/models.py

        x = self.model(x)
-        out = torch.cat((x, skip_input), 1)
-        return out
+        return torch.cat((x, skip_input), 1)


Function UNetUp.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:37Z

implementations/cgan/cgan.py

 img_shape = (opt.channels, opt.img_size, opt.img_size)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 36-36 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:37Z

implementations/cgan/cgan.py

        d_in = torch.cat((img.view(img.size(0), -1), self.label_embedding(labels)), -1)
-        validity = self.model(d_in)
-        return validity
+        return self.model(d_in)


Function Discriminator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:38Z

implementations/cluster_gan/clustergan.py

    for m in net.modules():
-        if isinstance(m, nn.Conv2d):
-            m.weight.data.normal_(0, 0.02)
-            m.bias.data.zero_()
-        elif isinstance(m, nn.ConvTranspose2d):
-            m.weight.data.normal_(0, 0.02)
-            m.bias.data.zero_()
-        elif isinstance(m, nn.Linear):
+        if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d, nn.Linear)):
            m.weight.data.normal_(0, 0.02)
            m.bias.data.zero_()


Function initialize_weights refactored with the following changes:

Merge duplicate blocks in conditional (merge-duplicate-blocks)

Remove redundant conditional (remove-redundant-if)

Merge isinstance calls (merge-is-instance)

SourceryAI · 2021-10-05T10:43:40Z

implementations/cluster_gan/clustergan.py

-        # Get output
-        validity = self.model(img)
-        return validity
+        return self.model(img)


Function Discriminator_CNN.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

This removes the following comments ( why? ):

# Get output

SourceryAI · 2021-10-05T10:43:40Z

implementations/cluster_gan/clustergan.py

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 326-562 refactored with the following changes:

Hoist statements out of for/while loops (hoist-statement-from-loop)

Simplify boolean if expression (boolean-if-exp-identity)

Simplify sequence comparison (simplify-len-comparison)

Replace x * x with x ** 2 (square-identity)

SourceryAI · 2021-10-05T10:43:40Z

implementations/cogan/cogan.py

 img_shape = (opt.channels, opt.img_size, opt.img_size)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 39-39 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:40Z

implementations/cogan/mnistm.py

-            if e.errno == errno.EEXIST:
-                pass
-            else:
+            if e.errno != errno.EEXIST:


Function MNISTM.download refactored with the following changes:

Swap if/else to remove empty if body (remove-pass-body)

SourceryAI · 2021-10-05T10:43:41Z

implementations/context_encoder/context_encoder.py

 2. Save the folder 'img_align_celeba' to '../../data/'
 4. Run the sript using command 'python3 context_encoder.py'
 """



Lines 49-49 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:42Z

implementations/ebgan/ebgan.py

 img_shape = (opt.channels, opt.img_size, opt.img_size)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 35-35 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:43Z

implementations/ebgan/ebgan.py

        out = out.view(out.shape[0], 128, self.init_size, self.init_size)
-        img = self.conv_blocks(out)
-        return img
+        return self.conv_blocks(out)


Function Generator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:43Z

implementations/ebgan/ebgan.py

-    loss_pt = (torch.sum(similarity) - batch_size) / (batch_size * (batch_size - 1))
-    return loss_pt
+    return (torch.sum(similarity) - batch_size) / (batch_size * (batch_size - 1))


Function pullaway_loss refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:43Z

implementations/esrgan/models.py

-            layers = []
-            layers.append(nn.Conv2d(in_filters, out_filters, kernel_size=3, stride=1, padding=1))
+            layers = [
+                nn.Conv2d(in_filters, out_filters, kernel_size=3, stride=1, padding=1)
+            ]
+


Function Discriminator.__init__.discriminator_block refactored with the following changes:

Merge append into list declaration (merge-list-append)

SourceryAI · 2021-10-05T10:43:43Z

implementations/gan/gan.py

 img_shape = (opt.channels, opt.img_size, opt.img_size)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 35-35 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:46Z

implementations/gan/gan.py

-        validity = self.model(img_flat)
-
-        return validity
+        return self.model(img_flat)


Function Discriminator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:46Z

implementations/infogan/infogan.py

 print(opt)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 38-38 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:46Z

implementations/infogan/infogan.py

        out = out.view(out.shape[0], 128, self.init_size, self.init_size)
-        img = self.conv_blocks(out)
-        return img
+        return self.conv_blocks(out)


Function Generator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:46Z

implementations/lsgan/lsgan.py

 print(opt)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 33-33 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

SourceryAI · 2021-10-05T10:43:46Z

implementations/lsgan/lsgan.py

        out = out.view(out.shape[0], 128, self.init_size, self.init_size)
-        img = self.conv_blocks(out)
-        return img
+        return self.conv_blocks(out)


Function Generator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:48Z

implementations/pixelda/pixelda.py

-        validity = self.model(img)
-
-        return validity
+        return self.model(img)


Function Discriminator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:48Z

implementations/pixelda/pixelda.py

-        label = self.output_layer(feature_repr)
-        return label
+        return self.output_layer(feature_repr)


Function Classifier.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:48Z

implementations/relativistic_gan/relativistic_gan.py

        out = out.view(out.shape[0], 128, self.init_size, self.init_size)
-        img = self.conv_blocks(out)
-        return img
+        return self.conv_blocks(out)


Function Generator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:48Z

implementations/relativistic_gan/relativistic_gan.py

-        validity = self.adv_layer(out)
-
-        return validity
+        return self.adv_layer(out)


Function Discriminator.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2021-10-05T10:43:49Z

implementations/sgan/sgan.py

 print(opt)

-cuda = True if torch.cuda.is_available() else False
+cuda = bool(torch.cuda.is_available())


Lines 34-34 refactored with the following changes:

Simplify boolean if expression (boolean-if-exp-identity)

'Refactored by Sourcery'

0c09832

SourceryAI commented Oct 5, 2021

View reviewed changes

		cuda = True if torch.cuda.is_available() else False
		cuda = bool(torch.cuda.is_available())

Sourcery Starbot ⭐ refactored undo76/PyTorch-GAN #1

Are you sure you want to change the base?

Sourcery Starbot ⭐ refactored undo76/PyTorch-GAN #1

Uh oh!

Conversation

SourceryAI commented Oct 5, 2021

Uh oh!

SourceryAI left a comment

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Choose a reason for hiding this comment

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

1 participant