Updated to latest torchsharp version

bonsai-rx · Jan 21, 2025 · 7f693a5 · 7f693a5
1 parent 30299e1
commit 7f693a5
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Showing 4 changed files with 14 additions and 14 deletions.
diff --git a/src/Bonsai.ML.Torch/Bonsai.ML.Torch.csproj b/src/Bonsai.ML.Torch/Bonsai.ML.Torch.csproj
@@ -8,8 +8,8 @@
   </PropertyGroup>
   <ItemGroup>
     <PackageReference Include="OpenCV.Net" Version="3.4.2" />
-    <PackageReference Include="TorchSharp" Version="0.103.1" />
-    <PackageReference Include="TorchVision" Version="0.103.1" />
+    <PackageReference Include="TorchSharp" Version="0.105.0" />
+    <PackageReference Include="TorchVision" Version="0.105.0" />
   </ItemGroup>
   <ItemGroup>
     <ProjectReference Include="..\Bonsai.ML\Bonsai.ML.csproj" />

diff --git a/src/Bonsai.ML.Torch/NeuralNets/Models/AlexNet.cs b/src/Bonsai.ML.Torch/NeuralNets/Models/AlexNet.cs
@@ -22,19 +22,19 @@ public class AlexNet : Module<Tensor, Tensor>
         public AlexNet(string name, int numClasses, Device device = null) : base(name)
         {
             features = Sequential(
-                ("c1", Conv2d(3, 64, kernelSize: 3, stride: 2, padding: 1)),
+                ("c1", Conv2d(3, 64, kernel_size: 3, stride: 2, padding: 1)),
                 ("r1", ReLU(inplace: true)),
-                ("mp1", MaxPool2d(kernelSize: [ 2, 2 ])),
-                ("c2", Conv2d(64, 192, kernelSize: 3, padding: 1)),
+                ("mp1", MaxPool2d(kernel_size: [ 2, 2 ])),
+                ("c2", Conv2d(64, 192, kernel_size: 3, padding: 1)),
                 ("r2", ReLU(inplace: true)),
-                ("mp2", MaxPool2d(kernelSize: [ 2, 2 ])),
-                ("c3", Conv2d(192, 384, kernelSize: 3, padding: 1)),
+                ("mp2", MaxPool2d(kernel_size: [ 2, 2 ])),
+                ("c3", Conv2d(192, 384, kernel_size: 3, padding: 1)),
                 ("r3", ReLU(inplace: true)),
-                ("c4", Conv2d(384, 256, kernelSize: 3, padding: 1)),
+                ("c4", Conv2d(384, 256, kernel_size: 3, padding: 1)),
                 ("r4", ReLU(inplace: true)),
-                ("c5", Conv2d(256, 256, kernelSize: 3, padding: 1)),
+                ("c5", Conv2d(256, 256, kernel_size: 3, padding: 1)),
                 ("r5", ReLU(inplace: true)),
-                ("mp3", MaxPool2d(kernelSize: [ 2, 2 ])));
+                ("mp3", MaxPool2d(kernel_size: [ 2, 2 ])));
 
             avgPool = AdaptiveAvgPool2d([ 2, 2 ]);
 

diff --git a/src/Bonsai.ML.Torch/NeuralNets/Models/MNIST.cs b/src/Bonsai.ML.Torch/NeuralNets/Models/MNIST.cs
@@ -14,7 +14,7 @@ public class MNIST : Module<Tensor,Tensor>
         private readonly Module<Tensor, Tensor> fc1 = Linear(9216, 128);
         private readonly Module<Tensor, Tensor> fc2 = Linear(128, 128);
 
-        private readonly Module<Tensor, Tensor> pool1 = MaxPool2d(kernelSize: [2, 2]);
+        private readonly Module<Tensor, Tensor> pool1 = MaxPool2d(kernel_size: [2, 2]);
 
         private readonly Module<Tensor, Tensor> relu1 = ReLU();
         private readonly Module<Tensor, Tensor> relu2 = ReLU();

diff --git a/src/Bonsai.ML.Torch/NeuralNets/Models/MobileNet.cs b/src/Bonsai.ML.Torch/NeuralNets/Models/MobileNet.cs
@@ -29,7 +29,7 @@ public MobileNet(string name, int numClasses, Device device = null) : base(name)
 
             var modules = new List<(string, Module<Tensor, Tensor>)>
             {
-                ($"conv2d-first", Conv2d(3, 32, kernelSize: 3, stride: 1, padding: 1, bias: false)),
+                ($"conv2d-first", Conv2d(3, 32, kernel_size: 3, stride: 1, padding: 1, bias: false)),
                 ($"bnrm2d-first", BatchNorm2d(32)),
                 ($"relu-first", ReLU())
             };
@@ -53,10 +53,10 @@ private void MakeLayers(List<(string, Module<Tensor, Tensor>)> modules, long in_
                 var out_planes = planes[i];
                 var stride = strides[i];
 
-                modules.Add(($"conv2d-{i}a", Conv2d(in_planes, in_planes, kernelSize: 3, stride: stride, padding: 1, groups: in_planes, bias: false)));
+                modules.Add(($"conv2d-{i}a", Conv2d(in_planes, in_planes, kernel_size: 3, stride: stride, padding: 1, groups: in_planes, bias: false)));
                 modules.Add(($"bnrm2d-{i}a", BatchNorm2d(in_planes)));
                 modules.Add(($"relu-{i}a", ReLU()));
-                modules.Add(($"conv2d-{i}b", Conv2d(in_planes, out_planes, kernelSize: 1L, stride: 1L, padding: 0L, bias: false)));
+                modules.Add(($"conv2d-{i}b", Conv2d(in_planes, out_planes, kernel_size: 1L, stride: 1L, padding: 0L, bias: false)));
                 modules.Add(($"bnrm2d-{i}b", BatchNorm2d(out_planes)));
                 modules.Add(($"relu-{i}b", ReLU()));