minor dcgan-import fix (#921)

* minor dcgan-import fix
* fix under_review import
* update docstring

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

pl_bolts/models/gans/dcgan/components.py

@@ -1,10 +1,8 @@
 # Based on https://github.com/pytorch/examples/blob/master/dcgan/main.py
-from torch import Tensor, nn
+import torch.nn as nn
+from torch import Tensor
 
-from pl_bolts.utils.stability import under_review
 
-
-@under_review()
 class DCGANGenerator(nn.Module):
     def __init__(self, latent_dim: int, feature_maps: int, image_channels: int) -> None:
         """
@@ -50,7 +48,6 @@ def forward(self, noise: Tensor) -> Tensor:
         return self.gen(noise)
 
 
-@under_review()
 class DCGANDiscriminator(nn.Module):
     def __init__(self, feature_maps: int, image_channels: int) -> None:
         """

pl_bolts/models/gans/dcgan/dcgan_module.py

@@ -2,14 +2,14 @@
 from typing import Any
 
 import torch
+import torch.nn as nn
 from pytorch_lightning import LightningModule, Trainer, seed_everything
-from torch import Tensor, nn
+from torch import Tensor
 from torch.utils.data import DataLoader
 
 from pl_bolts.callbacks import LatentDimInterpolator, TensorboardGenerativeModelImageSampler
 from pl_bolts.models.gans.dcgan.components import DCGANDiscriminator, DCGANGenerator
 from pl_bolts.utils import _TORCHVISION_AVAILABLE
-from pl_bolts.utils.stability import under_review
 from pl_bolts.utils.warnings import warn_missing_pkg
 
 if _TORCHVISION_AVAILABLE:
@@ -19,7 +19,6 @@
     warn_missing_pkg("torchvision")
 
 
-@under_review()
 class DCGAN(LightningModule):
     """DCGAN implementation.
 
@@ -28,7 +27,7 @@ class DCGAN(LightningModule):
         from pl_bolts.models.gans import DCGAN
 
         m = DCGAN()
-        Trainer(gpus=2).fit(m)
+        Trainer(accelerator="gpu", devices=2).fit(m)
 
     Example CLI::
 
@@ -80,10 +79,10 @@ def _get_discriminator(self) -> nn.Module:
     def _weights_init(m):
         classname = m.__class__.__name__
         if classname.find("Conv") != -1:
-            torch.nn.init.normal_(m.weight, 0.0, 0.02)
+            nn.init.normal_(m.weight, 0.0, 0.02)
         elif classname.find("BatchNorm") != -1:
-            torch.nn.init.normal_(m.weight, 1.0, 0.02)
-            torch.nn.init.zeros_(m.bias)
+            nn.init.normal_(m.weight, 1.0, 0.02)
+            nn.init.zeros_(m.bias)
 
     def configure_optimizers(self):
         lr = self.hparams.learning_rate
@@ -173,7 +172,6 @@ def add_model_specific_args(parent_parser: ArgumentParser) -> ArgumentParser:
         return parser
 
 
-@under_review()
 def cli_main(args=None):
     seed_everything(1234)