From b9f158514946dc8e853952514610bd56150598c5 Mon Sep 17 00:00:00 2001
From: "Daniel.Frisinghelli" <daniel.frisinghelli@eurac.edu>
Date: Mon, 6 Jul 2020 17:12:03 +0200
Subject: [PATCH] Changed super method to py3 standard
---
pytorch/models.py | 15 +--------------
1 file changed, 1 insertion(+), 14 deletions(-)
diff --git a/pytorch/models.py b/pytorch/models.py
index 40d5417..24b75eb 100644
--- a/pytorch/models.py
+++ b/pytorch/models.py
@@ -25,7 +25,7 @@ from pytorch.layers import (Encoder, Decoder, Conv2dPool, Conv2dUnpool,
class SegNet(nn.Module):
def __init__(self, in_channels, nclasses, filters, skip, **kwargs):
- super(SegNet, self).__init__()
+ super().__init__()
# get the configuration for the convolutional layers of the encoder
self.filters = np.hstack([np.array(in_channels), np.array(filters)])
@@ -102,16 +102,3 @@ class SegNet(nn.Module):
optimizer.load_state_dict(model_state['optim_state_dict'])
return state
-
-
-if __name__ == '__main__':
-
- # initialize segmentation network
- net = SegNet(in_channels=3,
- nclasses=7,
- filters=[32, 64, 128, 256],
- skip=True,
- kernel_size=3)
-
- # print network structure
- print(net)
--
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