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new 5ebf682 rename and restructure model zoo models (#8446)
5ebf682 is described below
commit 5ebf682b0b79260a976b57e123c82c649b785b6c
Author: Sheng Zha <[email protected]>
AuthorDate: Fri Oct 27 16:39:09 2017 -0700
rename and restructure model zoo models (#8446)
---
python/mxnet/gluon/model_zoo/vision/alexnet.py | 14 ++++++-------
python/mxnet/gluon/model_zoo/vision/densenet.py | 4 ++--
python/mxnet/gluon/model_zoo/vision/inception.py | 15 +++++++-------
python/mxnet/gluon/model_zoo/vision/mobilenet.py | 6 ++----
python/mxnet/gluon/model_zoo/vision/resnet.py | 7 +++----
python/mxnet/gluon/model_zoo/vision/squeezenet.py | 14 ++++++-------
python/mxnet/gluon/model_zoo/vision/vgg.py | 25 +++++++++++------------
7 files changed, 39 insertions(+), 46 deletions(-)
diff --git a/python/mxnet/gluon/model_zoo/vision/alexnet.py
b/python/mxnet/gluon/model_zoo/vision/alexnet.py
index 884e531..05669d0 100644
--- a/python/mxnet/gluon/model_zoo/vision/alexnet.py
+++ b/python/mxnet/gluon/model_zoo/vision/alexnet.py
@@ -52,18 +52,16 @@ class AlexNet(HybridBlock):
activation='relu'))
self.features.add(nn.MaxPool2D(pool_size=3, strides=2))
self.features.add(nn.Flatten())
+ self.features.add(nn.Dense(4096, activation='relu'))
+ self.features.add(nn.Dropout(0.5))
+ self.features.add(nn.Dense(4096, activation='relu'))
+ self.features.add(nn.Dropout(0.5))
- self.classifier = nn.HybridSequential(prefix='')
- with self.classifier.name_scope():
- self.classifier.add(nn.Dense(4096, activation='relu'))
- self.classifier.add(nn.Dropout(0.5))
- self.classifier.add(nn.Dense(4096, activation='relu'))
- self.classifier.add(nn.Dropout(0.5))
- self.classifier.add(nn.Dense(classes))
+ self.output = nn.Dense(classes)
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
# Constructor
diff --git a/python/mxnet/gluon/model_zoo/vision/densenet.py
b/python/mxnet/gluon/model_zoo/vision/densenet.py
index 82fb468..16afb2d 100644
--- a/python/mxnet/gluon/model_zoo/vision/densenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/densenet.py
@@ -103,11 +103,11 @@ class DenseNet(HybridBlock):
self.features.add(nn.AvgPool2D(pool_size=7))
self.features.add(nn.Flatten())
- self.classifier = nn.Dense(classes)
+ self.output = nn.Dense(classes)
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
diff --git a/python/mxnet/gluon/model_zoo/vision/inception.py
b/python/mxnet/gluon/model_zoo/vision/inception.py
index 632fefb..3ef0fb9 100644
--- a/python/mxnet/gluon/model_zoo/vision/inception.py
+++ b/python/mxnet/gluon/model_zoo/vision/inception.py
@@ -182,18 +182,17 @@ class Inception3(HybridBlock):
self.features.add(_make_C(160, 'C2_'))
self.features.add(_make_C(160, 'C3_'))
self.features.add(_make_C(192, 'C4_'))
+ self.features.add(_make_D('D_'))
+ self.features.add(_make_E('E1_'))
+ self.features.add(_make_E('E2_'))
+ self.features.add(nn.AvgPool2D(pool_size=8))
+ self.features.add(nn.Dropout(0.5))
- self.classifier = nn.HybridSequential(prefix='')
- self.classifier.add(_make_D('D_'))
- self.classifier.add(_make_E('E1_'))
- self.classifier.add(_make_E('E2_'))
- self.classifier.add(nn.AvgPool2D(pool_size=8))
- self.classifier.add(nn.Dropout(0.5))
- self.classifier.add(nn.Dense(classes))
+ self.output = nn.Dense(classes)
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
# Constructor
diff --git a/python/mxnet/gluon/model_zoo/vision/mobilenet.py
b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
index 27b76da..0ba0933 100644
--- a/python/mxnet/gluon/model_zoo/vision/mobilenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
@@ -65,13 +65,11 @@ class MobileNet(HybridBlock):
self.features.add(nn.GlobalAvgPool2D())
self.features.add(nn.Flatten())
- self.classifier = nn.HybridSequential(prefix='')
- with self.classifier.name_scope():
- self.classifier.add(nn.Dense(classes))
+ self.output = nn.Dense(classes)
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
# Constructor
diff --git a/python/mxnet/gluon/model_zoo/vision/resnet.py
b/python/mxnet/gluon/model_zoo/vision/resnet.py
index c45b854..f2c06c3 100644
--- a/python/mxnet/gluon/model_zoo/vision/resnet.py
+++ b/python/mxnet/gluon/model_zoo/vision/resnet.py
@@ -261,10 +261,9 @@ class ResNetV1(HybridBlock):
stride = 1 if i == 0 else 2
self.features.add(self._make_layer(block, num_layer,
channels[i+1],
stride, i+1,
in_channels=channels[i]))
+ self.features.add(nn.GlobalAvgPool2D())
- self.classifier = nn.HybridSequential(prefix='')
- self.classifier.add(nn.GlobalAvgPool2D())
- self.classifier.add(nn.Dense(classes, in_units=channels[-1]))
+ self.output = nn.Dense(classes, in_units=channels[-1])
def _make_layer(self, block, layers, channels, stride, stage_index,
in_channels=0):
layer = nn.HybridSequential(prefix='stage%d_'%stage_index)
@@ -277,7 +276,7 @@ class ResNetV1(HybridBlock):
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
diff --git a/python/mxnet/gluon/model_zoo/vision/squeezenet.py
b/python/mxnet/gluon/model_zoo/vision/squeezenet.py
index b9b038c..60ef393 100644
--- a/python/mxnet/gluon/model_zoo/vision/squeezenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/squeezenet.py
@@ -93,17 +93,17 @@ class SqueezeNet(HybridBlock):
self.features.add(_make_fire(48, 192, 192))
self.features.add(_make_fire(64, 256, 256))
self.features.add(_make_fire(64, 256, 256))
+ self.features.add(nn.Dropout(0.5))
- self.classifier = nn.HybridSequential(prefix='')
- self.classifier.add(nn.Dropout(0.5))
- self.classifier.add(nn.Conv2D(classes, kernel_size=1))
- self.classifier.add(nn.Activation('relu'))
- self.classifier.add(nn.AvgPool2D(13))
- self.classifier.add(nn.Flatten())
+ self.output = nn.HybridSequential(prefix='')
+ self.output.add(nn.Conv2D(classes, kernel_size=1))
+ self.output.add(nn.Activation('relu'))
+ self.output.add(nn.AvgPool2D(13))
+ self.output.add(nn.Flatten())
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
# Constructor
diff --git a/python/mxnet/gluon/model_zoo/vision/vgg.py
b/python/mxnet/gluon/model_zoo/vision/vgg.py
index 11269b5..c524e8e 100644
--- a/python/mxnet/gluon/model_zoo/vision/vgg.py
+++ b/python/mxnet/gluon/model_zoo/vision/vgg.py
@@ -50,18 +50,17 @@ class VGG(HybridBlock):
assert len(layers) == len(filters)
with self.name_scope():
self.features = self._make_features(layers, filters, batch_norm)
- self.classifier = nn.HybridSequential(prefix='')
- self.classifier.add(nn.Dense(4096, activation='relu',
- weight_initializer='normal',
- bias_initializer='zeros'))
- self.classifier.add(nn.Dropout(rate=0.5))
- self.classifier.add(nn.Dense(4096, activation='relu',
- weight_initializer='normal',
- bias_initializer='zeros'))
- self.classifier.add(nn.Dropout(rate=0.5))
- self.classifier.add(nn.Dense(classes,
- weight_initializer='normal',
- bias_initializer='zeros'))
+ self.features.add(nn.Dense(4096, activation='relu',
+ weight_initializer='normal',
+ bias_initializer='zeros'))
+ self.features.add(nn.Dropout(rate=0.5))
+ self.features.add(nn.Dense(4096, activation='relu',
+ weight_initializer='normal',
+ bias_initializer='zeros'))
+ self.features.add(nn.Dropout(rate=0.5))
+ self.output = nn.Dense(classes,
+ weight_initializer='normal',
+ bias_initializer='zeros')
def _make_features(self, layers, filters, batch_norm):
featurizer = nn.HybridSequential(prefix='')
@@ -80,7 +79,7 @@ class VGG(HybridBlock):
def hybrid_forward(self, F, x):
x = self.features(x)
- x = self.classifier(x)
+ x = self.output(x)
return x
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