Merge branch 'master' into new-apis_v0.1.0-dev

.devcontainer/onCreateCommand.sh

@@ -1,7 +1,7 @@
 #!/usr/bin/env bash
 
 python -m ensurepip # ensures pip is installed in the current environment
-pip install --upgrade pip
+pip install --upgrade pip==24.0
 pip install wheel
 pip install openvino-dev==2023.0.1 # [OPTIONAL] to generate optimized models for inference
 pip install mlcube_docker          # [OPTIONAL] to deploy GaNDLF models as MLCube-compliant Docker containers

.github/workflows/openfl-test.yml

@@ -100,3 +100,4 @@ jobs:
           config_to_use=$(pwd)/testing/config_segmentation.yaml
           cd openfl
           python -m tests.github.test_gandlf --template gandlf_seg_test --fed_workspace aggregator --col1 one --col2 two --rounds-to-train 1 --gandlf_config $config_to_use
+

GANDLF/models/seg_modules/DownsamplingModule.py

@@ -39,7 +39,7 @@ def __init__(
         if act_kwargs is None:
             act_kwargs = {"negative_slope": 1e-2, "inplace": True}
 
-        self.in_0 = norm(output_channels, **norm_kwargs)
+        self.in_0 = norm(input_channels, **norm_kwargs)
 
         self.conv0 = conv(input_channels, output_channels, **conv_kwargs)
 
@@ -49,14 +49,14 @@ def forward(self, x):
         """
         Applies a downsampling operation to the input tensor.
 
-        [input -- > in --> lrelu --> ConvDS --> output]
+        [input --> in --> lrelu --> ConvDS --> output]
 
         Args:
         x (torch.Tensor): Input tensor of shape (batch_size, channels, height, width)
 
         Returns:
             torch.Tensor: The output tensor, of shape (batch_size, output_channels, height // 2, width // 2).
         """
-        x = self.act(self.in_0(self.conv0(x)))
+        x = self.conv0(self.act(self.in_0(x)))
 
         return x