diff --git a/timm/models/eca_module.py b/timm/models/EcaModule.py
similarity index 96%
rename from timm/models/eca_module.py
rename to timm/models/EcaModule.py
index 5cb52d96..74da3170 100644
--- a/timm/models/eca_module.py
+++ b/timm/models/EcaModule.py
@@ -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
diff --git a/timm/models/resnet.py b/timm/models/resnet.py
index 49395c83..da755373 100644
--- a/timm/models/resnet.py
+++ b/timm/models/resnet.py
@@ -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