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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 from torch.nn.parameter import Parameter
class eca_layer(nn.Module): class EcaModule(nn.Module):
"""Constructs a ECA module. """Constructs a ECA module.
Args: Args:
@ -44,7 +44,7 @@ class eca_layer(nn.Module):
k_size: Adaptive selection of kernel size k_size: Adaptive selection of kernel size
""" """
def __init__(self, channel, k_size=3): def __init__(self, channel, k_size=3):
super(eca_layer, self).__init__() super(EcaModule, self).__init__()
assert k_size % 2 == 1 assert k_size % 2 == 1
self.avg_pool = nn.AdaptiveAvgPool2d(1) self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.conv = nn.Conv1d(1, 1, kernel_size=k_size, padding=(k_size - 1) // 2, bias=False) 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. """Constructs a circular ECA module.
the primary difference is that the conv uses a circular padding rather than zero padding. 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 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 k_size: Adaptive selection of kernel size
""" """
def __init__(self, channel, k_size=3): def __init__(self, channel, k_size=3):
super(ceca_layer, self).__init__() super(CecaModule, self).__init__()
assert k_size % 2 == 1 assert k_size % 2 == 1
self.avg_pool = nn.AdaptiveAvgPool2d(1) self.avg_pool = nn.AdaptiveAvgPool2d(1)
#pytorch circular padding mode is bugged as of pytorch 1.4 #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 .registry import register_model
from .helpers import load_pretrained from .helpers import load_pretrained
from .adaptive_avgmax_pool import SelectAdaptivePool2d 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 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
@ -157,7 +157,7 @@ class BasicBlock(nn.Module):
self.bn2 = norm_layer(outplanes) self.bn2 = norm_layer(outplanes)
self.se = SEModule(outplanes, planes // 4) if use_se else None 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.act2 = act_layer(inplace=True)
self.downsample = downsample self.downsample = downsample
@ -212,7 +212,7 @@ class Bottleneck(nn.Module):
self.bn3 = norm_layer(outplanes) self.bn3 = norm_layer(outplanes)
self.se = SEModule(outplanes, planes // 4) if use_se else None 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.act3 = act_layer(inplace=True)
self.downsample = downsample self.downsample = downsample