remove embed

antialiased_cnns/alexnet.py

@@ -42,7 +42,6 @@
 import torch.utils.model_zoo as model_zoo
 import numpy as np
 from antialiased_cnns import *
-from IPython import embed
 
 __all__ = ['AlexNet', 'alexnet']
 
@@ -153,7 +152,6 @@ def __init__(self, num_classes=1000, filter_size=1):
         )
 
     def forward(self, x):
-        # embed()
         x = self.features(x)
         x = self.avgpool(x)
         x = x.view(x.size(0), 256 * 6 * 6)

antialiased_cnns/blurpool.py

@@ -9,7 +9,6 @@
 import numpy as np
 import torch.nn as nn
 import torch.nn.functional as F
-from IPython import embed
 
 class BlurPool(nn.Module):
     def __init__(self, channels, pad_type='reflect', filt_size=4, stride=2, pad_off=0):

antialiased_cnns/resnet.py

@@ -40,7 +40,6 @@
 import torch.nn as nn
 import torch.utils.model_zoo as model_zoo
 from antialiased_cnns import *
-from IPython import embed
 
 __all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
            'resnet152', 'resnext50_32x4d', 'resnext101_32x8d']

setup.py

@@ -8,7 +8,7 @@
      author_email="rizhang@adobe.com",
      description="Antialiased models and pooling layer from Zhang. Making Convnets Shift-Invariant Again. ICML 2019.",
      long_description=long_description,
-   long_description_content_type="text/markdown",
+     long_description_content_type="text/markdown",
      url="https://github.com/adobe/antialiased-cnns",
      packages=setuptools.find_packages(),
      classifiers=[
@@ -17,3 +17,5 @@
          "Operating System :: OS Independent",
      ],
  )
+
+     # install_requires=[],