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This commit is contained in:
weishengyu 2021-05-26 00:31:08 +08:00
parent 0e568006a8
commit 1d39358358
1 changed files with 4 additions and 12 deletions
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16
ppcls/arch/backbone/legendary_models/hrnet.py
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@ -218,7 +218,6 @@ class SELayer(TheseusLayer):
class Stage(TheseusLayer):
def __init__(self,
num_channels,
num_modules,
num_filters,
has_se=False,
@ -234,7 +233,6 @@ class Stage(TheseusLayer):
stage_func = self.add_sublayer(
"stage_{}_{}".format(name, i + 1),
HighResolutionModule(
num_channels=num_channels,
num_filters=num_filters,
has_se=has_se,
multi_scale_output=False,
@ -243,7 +241,6 @@ class Stage(TheseusLayer):
stage_func = self.add_sublayer(
"stage_{}_{}".format(name, i + 1),
HighResolutionModule(
num_channels=num_channels,
num_filters=num_filters,
has_se=has_se,
name=name + '_' + str(i + 1)))
@ -259,7 +256,6 @@ class Stage(TheseusLayer):
class HighResolutionModule(TheseusLayer):
def __init__(self,
num_channels,
num_filters,
has_se=False,
multi_scale_output=True,
@ -271,7 +267,7 @@ class HighResolutionModule(TheseusLayer):
for i in range(len(num_filters)):
self.basic_block_list.append([])
for j in range(4):
in_ch = num_channels[i] if j == 0 else num_channels[i]
in_ch = num_filters[i]
basic_block_func = self.add_sublayer(
"bb_{}_branch_layer_{}_{}".format(name, i + 1, j + 1),
BasicBlock(
@ -425,7 +421,6 @@ class HRNet(TheseusLayer):
self._class_dim = class_dim
channels_2, channels_3, channels_4 = self.channels[width]
num_modules_2, num_modules_3, num_modules_4 = 1, 4, 3
self.conv_layer1_1 = ConvBNLayer(
num_channels=3,
@ -462,8 +457,7 @@ class HRNet(TheseusLayer):
)
self.st2 = Stage(
num_channels=channels_2,
num_modules=num_modules_2,
num_modules=1,
num_filters=channels_2,
has_se=self.has_se,
name="st2")
@ -475,8 +469,7 @@ class HRNet(TheseusLayer):
stride=2
)
self.st3 = Stage(
num_channels=channels_3,
num_modules=num_modules_3,
num_modules=4,
num_filters=channels_3,
has_se=self.has_se,
name="st3")
@ -489,8 +482,7 @@ class HRNet(TheseusLayer):
)
self.st4 = Stage(
num_channels=channels_4,
num_modules=num_modules_4,
num_modules=3,
num_filters=channels_4,
has_se=self.has_se,
name="st4")