Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Googlenet support bn to fit LR linear scale rule with large batch_size #2789

Open
wants to merge 1 commit into
base: develop
Choose a base branch
from
Open

Googlenet support bn to fit LR linear scale rule with large batch_size #2789

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
96 changes: 73 additions & 23 deletions ppcls/arch/backbone/model_zoo/googlenet.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -50,9 +50,11 @@ def __init__(self,
groups=1,
act=None,
name=None,
data_format="NCHW"):
data_format="NCHW",
insert_bn=True):
super(ConvLayer, self).__init__()

self.insert_bn = insert_bn
self._conv = Conv2D(
in_channels=num_channels,
out_channels=num_filters,
Expand All @@ -63,9 +65,15 @@ def __init__(self,
weight_attr=ParamAttr(name=name + "_weights"),
bias_attr=False,
data_format=data_format)
if insert_bn:
self._bn = BatchNorm(
num_channels=num_filters,
param_attr=ParamAttr(name=name + "_bn"))

def forward(self, inputs):
y = self._conv(inputs)
if self.insert_bn:
y = self._bn(y)
return y


Expand All @@ -80,7 +88,8 @@ def __init__(self,
filter5,
proj,
name=None,
data_format="NCHW"):
data_format="NCHW",
insert_bn=True):
super(Inception, self).__init__()
self.data_format = data_format

Expand All @@ -89,31 +98,36 @@ def __init__(self,
filter1,
1,
name="inception_" + name + "_1x1",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._conv3r = ConvLayer(
input_channels,
filter3R,
1,
name="inception_" + name + "_3x3_reduce",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._conv3 = ConvLayer(
filter3R,
filter3,
3,
name="inception_" + name + "_3x3",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._conv5r = ConvLayer(
input_channels,
filter5R,
1,
name="inception_" + name + "_5x5_reduce",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._conv5 = ConvLayer(
filter5R,
filter5,
5,
name="inception_" + name + "_5x5",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._pool = MaxPool2D(
kernel_size=3, stride=1, padding=1, data_format=data_format)

Expand All @@ -122,7 +136,8 @@ def __init__(self,
proj,
1,
name="inception_" + name + "_3x3_proj",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)

def forward(self, inputs):
conv1 = self._conv1(inputs)
Expand All @@ -145,17 +160,33 @@ def forward(self, inputs):


class GoogLeNetDY(nn.Layer):
def __init__(self, class_num=1000, data_format="NCHW"):
def __init__(self, class_num=1000, data_format="NCHW", insert_bn=True):
super(GoogLeNetDY, self).__init__()
self.data_format = data_format
self._conv = ConvLayer(
3, 64, 7, 2, name="conv1", data_format=data_format)
3,
64,
7,
2,
name="conv1",
data_format=data_format,
insert_bn=insert_bn)
self._pool = MaxPool2D(
kernel_size=3, stride=2, data_format=data_format)
self._conv_1 = ConvLayer(
64, 64, 1, name="conv2_1x1", data_format=data_format)
64,
64,
1,
name="conv2_1x1",
data_format=data_format,
insert_bn=insert_bn)
self._conv_2 = ConvLayer(
64, 192, 3, name="conv2_3x3", data_format=data_format)
64,
192,
3,
name="conv2_3x3",
data_format=data_format,
insert_bn=insert_bn)

self._ince3a = Inception(
192,
Expand All @@ -167,7 +198,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
32,
32,
name="ince3a",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._ince3b = Inception(
256,
256,
Expand All @@ -178,7 +210,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
96,
64,
name="ince3b",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)

self._ince4a = Inception(
480,
Expand All @@ -190,7 +223,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
48,
64,
name="ince4a",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._ince4b = Inception(
512,
512,
Expand All @@ -201,7 +235,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
64,
64,
name="ince4b",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._ince4c = Inception(
512,
512,
Expand All @@ -212,7 +247,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
64,
64,
name="ince4c",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._ince4d = Inception(
512,
512,
Expand All @@ -223,7 +259,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
64,
64,
name="ince4d",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._ince4e = Inception(
528,
528,
Expand All @@ -234,7 +271,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
128,
128,
name="ince4e",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)

self._ince5a = Inception(
832,
Expand All @@ -246,7 +284,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
128,
128,
name="ince5a",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)
self._ince5b = Inception(
832,
832,
Expand All @@ -257,7 +296,8 @@ def __init__(self, class_num=1000, data_format="NCHW"):
128,
128,
name="ince5b",
data_format=data_format)
data_format=data_format,
insert_bn=insert_bn)

self._pool_5 = AdaptiveAvgPool2D(1, data_format=data_format)

Expand All @@ -271,7 +311,12 @@ def __init__(self, class_num=1000, data_format="NCHW"):
self._pool_o1 = AvgPool2D(
kernel_size=5, stride=3, data_format=data_format)
self._conv_o1 = ConvLayer(
512, 128, 1, name="conv_o1", data_format=data_format)
512,
128,
1,
name="conv_o1",
data_format=data_format,
insert_bn=insert_bn)
self._fc_o1 = Linear(
1152,
1024,
Expand All @@ -286,7 +331,12 @@ def __init__(self, class_num=1000, data_format="NCHW"):
self._pool_o2 = AvgPool2D(
kernel_size=5, stride=3, data_format=data_format)
self._conv_o2 = ConvLayer(
528, 128, 1, name="conv_o2", data_format=data_format)
528,
128,
1,
name="conv_o2",
data_format=data_format,
insert_bn=insert_bn)
self._fc_o2 = Linear(
1152,
1024,
Expand Down