mirrors
/
PaddleClas
mirror of https://github.com/PaddlePaddle/PaddleClas.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

update pp_hgnet.py

pull/1919/head
cuicheng01 2022-05-13 04:07:41 +00:00
parent 8a760fb85f
commit 713dd6f9eb
1 changed files with 5 additions and 5 deletions
ppcls/arch/backbone/legendary_models

10
ppcls/arch/backbone/legendary_models/pp_hgnet.py
View File

@ -90,7 +90,7 @@ class ESEModule(TheseusLayer):
return paddle.multiply(x=identity, y=x)
class _HG_Block(TheseusLayer):
class HG_Block(TheseusLayer):
def __init__(
self,
in_channels,
@ -140,7 +140,7 @@ class _HG_Block(TheseusLayer):
return x
class _HG_Stage(TheseusLayer):
class HG_Stage(TheseusLayer):
def __init__(self,
in_channels,
mid_channels,
@ -161,7 +161,7 @@ class _HG_Stage(TheseusLayer):
blocks_list = []
blocks_list.append(
_HG_Block(
HG_Block(
in_channels,
mid_channels,
out_channels,
@ -169,7 +169,7 @@ class _HG_Stage(TheseusLayer):
identity=False))
for _ in range(block_num - 1):
blocks_list.append(
_HG_Block(
HG_Block(
out_channels,
mid_channels,
out_channels,
@ -228,7 +228,7 @@ class PPHGNet(TheseusLayer):
in_channels, mid_channels, out_channels, block_num, downsample = stage_config[
k]
self.stages.append(
_HG_Stage(in_channels, mid_channels, out_channels, block_num,
HG_Stage(in_channels, mid_channels, out_channels, block_num,
layer_num, downsample))
self.avg_pool = AdaptiveAvgPool2D(1)