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Use torch.nn.init in SqueezeNet models #146

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Merged
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Apr 30, 2017
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Use torch.nn.init in SqueezeNet models #146

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8 changes: 3 additions & 5 deletions torchvision/models/squeezenet.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
import math
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.utils.model_zoo as model_zoo


Expand Down Expand Up @@ -87,13 +88,10 @@ def __init__(self, version=1.0, num_classes=1000):

for m in self.modules():
if isinstance(m, nn.Conv2d):
gain = 2.0
if m is final_conv:
m.weight.data.normal_(0, 0.01)
init.normal(m.weight.data, mean=0.0, std=0.01)
else:
fan_in = m.kernel_size[0] * m.kernel_size[1] * m.in_channels
u = math.sqrt(3.0 * gain / fan_in)
m.weight.data.uniform_(-u, u)
init.kaiming_uniform(m.weight.data)
if m.bias is not None:
m.bias.data.zero_()

Expand Down