Fix get_model

gluoncv/model_zoo/danet.py

@@ -90,15 +90,15 @@ def __init__(self, in_channels, out_channels, norm_layer=nn.BatchNorm, norm_kwar
         self.conv52.add(nn.Activation('relu'))
 
         self.conv6 = nn.HybridSequential()
-        self.conv6.add(nn.Dropout(0.1))
+        # self.conv6.add(nn.Dropout(0.1))
         self.conv6.add(nn.Conv2D(in_channels=512, channels=out_channels, kernel_size=1))
 
         self.conv7 = nn.HybridSequential()
-        self.conv7.add(nn.Dropout(0.1))
+        # self.conv7.add(nn.Dropout(0.1))
         self.conv7.add(nn.Conv2D(in_channels=512, channels=out_channels, kernel_size=1))
 
         self.conv8 = nn.HybridSequential()
-        self.conv8.add(nn.Dropout(0.1))
+        # self.conv8.add(nn.Dropout(0.1))
         self.conv8.add(nn.Conv2D(in_channels=512, channels=out_channels, kernel_size=1))
 
     def hybrid_forward(self, F, x):

gluoncv/model_zoo/model_zoo.py

@@ -215,7 +215,7 @@
     'resnext50_32x4d': resnext50_32x4d,
     'resnext101_32x4d': resnext101_32x4d,
     'resnext101_64x4d': resnext101_64x4d,
-    'resnext101b_64x4d': resnext101e_64x4d,
+    'resnext101e_64x4d': resnext101e_64x4d,
     'se_resnext50_32x4d': se_resnext50_32x4d,
     'se_resnext101_32x4d': se_resnext101_32x4d,
     'se_resnext101_64x4d': se_resnext101_64x4d,

gluoncv/model_zoo/resnext.py

@@ -363,6 +363,7 @@ def resnext101_64x4d(**kwargs):
 
 
 def resnext101e_64x4d(**kwargs):
+    # pylint: disable=line-too-long
     r"""ResNext101e 64x4d model modified from
     `"Aggregated Residual Transformations for Deep Neural Network"
     <http://arxiv.org/abs/1611.05431>`_ paper.
@@ -388,6 +389,9 @@ def resnext101e_64x4d(**kwargs):
         for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
     """
     kwargs['use_se'] = False
+    if kwargs['pretrained']:
+        msg = 'GluonCV does not have pretrained weights for resnext101e_64x4d at this moment. Please set pretrained=False.'
+        raise RuntimeError(msg)
     return get_resnext(101, 64, 4, deep_stem=True, avg_down=True, **kwargs)
 
 
@@ -479,6 +483,7 @@ def se_resnext101_64x4d(**kwargs):
 
 
 def se_resnext101e_64x4d(**kwargs):
+    # pylint: disable=line-too-long
     r"""SE-ResNext101e 64x4d model modified from
     `"Aggregated Residual Transformations for Deep Neural Network"
     <http://arxiv.org/abs/1611.05431>`_ paper.
@@ -504,4 +509,7 @@ def se_resnext101e_64x4d(**kwargs):
         for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
     """
     kwargs['use_se'] = True
+    if kwargs['pretrained']:
+        msg = 'GluonCV does not have pretrained weights for resnext101e_64x4d at this moment. Please set pretrained=False.'
+        raise RuntimeError(msg)
     return get_resnext(101, 64, 4, deep_stem=True, avg_down=True, **kwargs)