Follow layers and sequences pattern

This commit is contained in:
henryruhs
2025-03-10 18:46:25 +01:00
parent e267f9ffd5
commit 54923abf7f
2 changed files with 8 additions and 5 deletions
+1 -1
View File
@@ -70,7 +70,7 @@ kernel_size = 4
[training.model.masker]
input_channels = 67
output_channels = 1
base_channels = 16
num_filters = 16
```
```
+7 -4
View File
@@ -52,20 +52,23 @@ class BottleNeck(nn.Module):
def __init__(self, num_filters : int):
super().__init__()
self.layers = self.create_layers(num_filters)
self.sequences = nn.Sequential(*self.layers)
self.relu = nn.ReLU(inplace = True)
def create_layers(self, num_filters : int) -> nn.Sequential:
return nn.Sequential(
@staticmethod
def create_layers(num_filters : int) -> nn.ModuleList:
return nn.ModuleList(
[
nn.Conv2d(num_filters, num_filters, kernel_size = 3, padding = 1, bias = False),
nn.BatchNorm2d(num_filters),
nn.ReLU(inplace = True),
nn.Conv2d(num_filters, num_filters, kernel_size = 3, padding = 1, bias = False),
nn.BatchNorm2d(num_filters),
nn.ReLU(inplace = True)
)
])
def forward(self, input_tensor : Tensor) -> Tensor:
output_tensor = self.layers(input_tensor) + input_tensor
output_tensor = self.sequences(input_tensor) + input_tensor
output_tensor = self.relu(output_tensor)
return output_tensor