dwSun commented on a change in pull request #9614: MobileNetV2
URL: https://github.com/apache/incubator-mxnet/pull/9614#discussion_r165301357
##########
File path: python/mxnet/gluon/model_zoo/vision/mobilenet.py
##########
@@ -147,57 +143,21 @@ def __init__(self, multiplier=1.0, classes=1000,
**kwargs):
with self.name_scope():
self.features = nn.HybridSequential(prefix='features_')
with self.features.name_scope():
- self.features.add(
- nn.Conv2D(int(32 * multiplier), 3, strides=2, padding=1,
use_bias=False),
- nn.BatchNorm(scale=True),
- nn.Activation('relu')
- )
-
- c_bgn = int(32 * multiplier)
- c_end = int(16 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=1,
s=1))
-
- c_bgn = int(16 * multiplier)
- c_end = int(24 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=6,
s=2))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
-
- c_bgn = int(24 * multiplier)
- c_end = int(32 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=6,
s=2))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
-
- c_bgn = int(32 * multiplier)
- c_end = int(64 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=6,
s=2))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
-
- c_bgn = int(64 * multiplier)
- c_end = int(96 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=6,
s=1))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
-
- c_bgn = int(96 * multiplier)
- c_end = int(160 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=6,
s=2))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
- self.features.add(BottleNeck(c_in=c_end, c_out=c_end, t=6,
s=1))
-
- c_bgn = int(160 * multiplier)
- c_end = int(320 * multiplier)
- self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=6,
s=1))
+ _add_conv(self.features, int(32 * multiplier), kernel=3,
stride=2, pad=1)
+
+ c_bgns = [int(x * multiplier) for x in [32] + [16] + [24] * 2
+ + [32] * 3 + [64] * 4 + [96] * 3 + [160] * 3]
+ c_ends = [int(x * multiplier) for x in [16] + [24] * 2 + [32]
* 3
+ + [64] * 4 + [96] * 3 + [160] * 3 + [320]]
+ ts = [1] + [6] * 16
+ strides = [1, 2] * 2 + [1] * 2 + [2] + [1] * 3 + [1] * 3 + [2]
+ [1] * 3
+
+ for c_bgn, c_end, t, s in zip(c_bgns, c_ends, ts, strides):
+ self.features.add(BottleNeck(c_in=c_bgn, c_out=c_end, t=t,
s=s))
Review comment:
The code here looks ugly and very hard to follow the data flow.
Is this kind of code really necessary?
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