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EcaModule(CamelCase)

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CamelCased EcaModule.
Renamed all instances of ecalayer to EcaModule.
eca_module.py->EcaModule.py
This commit is contained in:
Chris Ha 2020-02-07 19:28:07 +09:00
parent d04ff95eda
commit db91ba053b
2 changed files with 7 additions and 7 deletions
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8
timm/models/eca_module.py → timm/models/EcaModule.py
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@ -36,7 +36,7 @@ from torch import nn
from torch.nn.parameter import Parameter
class eca_layer(nn.Module):
class EcaModule(nn.Module):
"""Constructs a ECA module.
Args:
@ -44,7 +44,7 @@ class eca_layer(nn.Module):
k_size: Adaptive selection of kernel size
"""
def __init__(self, channel, k_size=3):
super(eca_layer, self).__init__()
super(EcaModule, self).__init__()
assert k_size % 2 == 1
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.conv = nn.Conv1d(1, 1, kernel_size=k_size, padding=(k_size - 1) // 2, bias=False)
@ -79,7 +79,7 @@ class eca_layer(nn.Module):
class ceca_layer(nn.Module):
class CecaModule(nn.Module):
"""Constructs a circular ECA module.
the primary difference is that the conv uses a circular padding rather than zero padding.
This is because unlike images, the channels themselves do not have inherent ordering nor
@ -94,7 +94,7 @@ class ceca_layer(nn.Module):
k_size: Adaptive selection of kernel size
"""
def __init__(self, channel, k_size=3):
super(ceca_layer, self).__init__()
super(CecaModule, self).__init__()
assert k_size % 2 == 1
self.avg_pool = nn.AdaptiveAvgPool2d(1)
#pytorch circular padding mode is bugged as of pytorch 1.4

6
timm/models/resnet.py
View File

@ -14,7 +14,7 @@ import torch.nn.functional as F
from .registry import register_model
from .helpers import load_pretrained
from .adaptive_avgmax_pool import SelectAdaptivePool2d
from .eca_module import eca_layer
from .EcaModule import EcaModule
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
@ -157,7 +157,7 @@ class BasicBlock(nn.Module):
self.bn2 = norm_layer(outplanes)
self.se = SEModule(outplanes, planes // 4) if use_se else None
self.eca = eca_layer(outplanes) if use_eca else None
self.eca = EcaModule(outplanes) if use_eca else None
self.act2 = act_layer(inplace=True)
self.downsample = downsample
@ -212,7 +212,7 @@ class Bottleneck(nn.Module):
self.bn3 = norm_layer(outplanes)
self.se = SEModule(outplanes, planes // 4) if use_se else None
self.eca = eca_layer(outplanes) if use_eca else None
self.eca = Eca_Module(outplanes) if use_eca else None
self.act3 = act_layer(inplace=True)
self.downsample = downsample