ML.NET CLI object detection failed in Linux container

**System Information (please complete the following information):**
- Model Builder Version (`mlnet --version`): 16.18.2+255dca7057095f9c073a8031db28ddf3a2a4ee27
- OS: Ubuntu 22.04.4 LTS (GNU/Linux 6.5.0-41-generic x86_64)
- Image: mcr.microsoft.com/dotnet/sdk:8.0 (sha256:08854ef383c0adf41c67007250258a9583089e7764d2e721763d47b91b58b0e0)
- Image: mcr.microsoft.com/dotnet/nightly/sdk:8.0 (sha256:cc1157cea8b32d43358fbf1d99d608229cb48296ffa63e469f4a67b91ac76b8a)

**Describe the bug**
- On which step of the process did you run into an issue: When running `mlnet object-detection --dataset ./vott-json-export/StopSignObjDetection-export.json` command.
- Clear description of the problem: Message as shown below
```
root@9c01988d3ab8:/# mlnet object-detection --dataset ./vott-json-export/StopSignObjDetection-export.json
Welcome to the ML.NET CLI!
--------------------------
Learn more about the ML.NET CLI: https://aka.ms/mlnet-cli
Use 'mlnet --help' to see available commands and options.

Telemetry
---------
The ML.NET CLI tool collects usage data in order to help us improve your experience.
The data doesn't include personal information or data from your datasets.
You can opt-out of telemetry by setting the MLDOTNET_CLI_TELEMETRY_OPTOUT environment variable to '1' or 'true' using your f avorite shell.

Read more about ML.NET CLI telemetry: https://aka.ms/mlnet-cli-telemetry

Start Training
Image List:
Image: file:/app/Stop-Signs/yannis-h-Sqez8_QTi8o-unsplash.jpg
Image: file:/app/Stop-Signs/will-porada-ZaGcU6BxJEc-unsplash.jpg
Image: file:/app/Stop-Signs/untitled-photo-3d6zCZ4lpBE-unsplash.jpg
Image: file:/app/Stop-Signs/tyler-nix-ahee6DMcUcI-unsplash.jpg
Image: file:/app/Stop-Signs/tom-dillon-t9Eaei-jz7Y-unsplash.jpg
Image: file:/app/Stop-Signs/suad-kamardeen-EcQW_Caifz8-unsplash.jpg
Image: file:/app/Stop-Signs/sandy-ching-ixLUOtNSSHQ-unsplash.jpg
Image: file:/app/Stop-Signs/samuel-sng-Uj5tQyHS2d0-unsplash.jpg
Image: file:/app/Stop-Signs/sam-xu-FgY6bF6emj0-unsplash.jpg
Image: file:/app/Stop-Signs/ron-mcclenny-EpHH_NKwKkE-unsplash.jpg
Image: file:/app/Stop-Signs/renan-kamikoga-vxx6ilmR-W4-unsplash.jpg
Image: file:/app/Stop-Signs/phil-garrison-ezvpHWyqsYg-unsplash.jpg
Image: file:/app/Stop-Signs/pedro-da-silva-unEmGQqdO7Q-unsplash.jpg
Image: file:/app/Stop-Signs/olivia-connell-Tc9KWrlOL0E-unsplash.jpg
Image: file:/app/Stop-Signs/naina-vij--j35s3zjPKU-unsplash.jpg
Image: file:/app/Stop-Signs/melanie-these-mXIViwsTvIc-unsplash.jpg
Image: file:/app/Stop-Signs/mason-wilkes-q-nm36mpsDw-unsplash.jpg
Image: file:/app/Stop-Signs/marcos-mathias-Jd7jw1Vf_aI-unsplash.jpg
Image: file:/app/Stop-Signs/luke-van-zyl-rKSHh6nEG1g-unsplash.jpg
Image: file:/app/Stop-Signs/kevork-kurdoghlian-eB2YX2TzNIA-unsplash.jpg
Image: file:/app/Stop-Signs/kevin-lee-dU8dAD8KoOI-unsplash.jpg
Image: file:/app/Stop-Signs/kelly-sikkema-4KzwQGsDRvA-unsplash.jpg
Image: file:/app/Stop-Signs/juli-kosolapova-DmtblAatFtk-unsplash.jpg
Image: file:/app/Stop-Signs/joshua-hoehne-WPrTKRw8KRQ-unsplash.jpg
Image: file:/app/Stop-Signs/josh-wilburne-3Cs4mF7fL3w-unsplash.jpg
Image: file:/app/Stop-Signs/jose-alonso-fl9kHTSPSvk-unsplash.jpg
Image: file:/app/Stop-Signs/jon-tyson-QNp4m7gU7BA-unsplash.jpg
Image: file:/app/Stop-Signs/jon-tyson-1IqQDH6KgdU-unsplash.jpg
Image: file:/app/Stop-Signs/john-matychuk-dJdcb11aboQ-unsplash.jpg
Image: file:/app/Stop-Signs/joel-mott-9r9Ex5iEc5o-unsplash.jpg
Image: file:/app/Stop-Signs/jad-limcaco-Y_J0phaFy2g-unsplash.jpg
Image: file:/app/Stop-Signs/giorgio-trovato-7PUrk4B18tY-unsplash.jpg
Image: file:/app/Stop-Signs/free-to-use-sounds-Vkt3uDeDkdg-unsplash.jpg
Image: file:/app/Stop-Signs/emiel-van-betsbrugge-rogwZG1NfII-unsplash.jpg
Image: file:/app/Stop-Signs/eilis-garvey-rb_PpjzWKnU-unsplash.jpg
Image: file:/app/Stop-Signs/doyoun-seo-Xe1S9aq2fqg-unsplash.jpg
Image: file:/app/Stop-Signs/diego-lozano-AmZC7bCrsko-unsplash.jpg
Image: file:/app/Stop-Signs/david-preston-mW2NETqR49A-unsplash.jpg
Image: file:/app/Stop-Signs/david-preston--t7S0WPRr4E-unsplash.jpg
Image: file:/app/Stop-Signs/chris-benson-h0UG2Bd_Few-unsplash.jpg
Image: file:/app/Stop-Signs/chris-bair-PJLDC3tA0Sc-unsplash.jpg
Image: file:/app/Stop-Signs/brantley-neal-_CAvB1vYIlY-unsplash.jpg
Image: file:/app/Stop-Signs/branden-tate-XgEHOPn7h_E-unsplash.jpg
Image: file:/app/Stop-Signs/bogomil-mihaylov-OHxTNeAtNRs-unsplash.jpg
Image: file:/app/Stop-Signs/ben-mater-YO3iFGBN6TU-unsplash.jpg
Image: file:/app/Stop-Signs/arthur-osipyan-vLusIJAYy_Q-unsplash.jpg
Image: file:/app/Stop-Signs/anton-mishin-_AR3i6Gck0Q-unsplash.jpg
Image: file:/app/Stop-Signs/andrii-leonov-W_rQAwVRPgg-unsplash.jpg
Image: file:/app/Stop-Signs/alexandre-lecocq-ndBWgMLw6Bc-unsplash.jpg
Image: file:/app/Stop-Signs/ajda-atz-HEKgHLpNgGk-unsplash.jpg
start Object detection
try to load libtorch.so from /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5
env:path: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/root/.dotnet/tools
restore "/root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/RuntimeManager/torchsha rp.cpu.csproj" --configfile "/root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/Run timeManager/NuGet.config" -r linux-x64 /p:UsingToolXliff=false /p:TorchSharpVersion=0.101.5 /p:TorchSharpCudaRuntimeVersion= 2.1.0.1 /p:TensorflowRuntimeVersion=2.3.1 /p:BaseIntermediateOutputPath="/root/.local/share/ModelBuilder/torchsharp-cpu-0.10 1.5\obj"
publish "/root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/RuntimeManager/torchsha rp.cpu.csproj" -r linux-x64 -c Release --no-self-contained -o "/root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5" --no- restore /p:UsingToolXliff=false /p:TorchSharpVersion=0.101.5 /p:TorchSharpCudaRuntimeVersion=2.1.0.1 /p:TensorflowRuntimeVer sion=2.3.1 /p:BaseOutputPath="/root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5\bin\\" /p:BaseIntermediateOutputPath="/ root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5\obj\\"
start installing runtime in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5
Determining projects to restore...
Restored /root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/RuntimeManager/torchsharp.cpu.csproj (in 39.78 sec).

torchsharp.cpu -> /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/bin/Release/netstandard2.0/linux-x64/torchsharp.cpu.dll
torchsharp.cpu -> /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/

install runtime successfully
try to load libtorch.so from /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5
load libtorch.so from /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5 success
[Source=AutoMLExperiment-ChildContext, Kind=Trace] [Source=ObjectDetectionTrainer; TrainModel, Kind=Trace] Channel started
[Source=AutoMLExperiment-ChildContext, Kind=Trace] [Source=ObjectDetectionTrainer; TrainModel, Kind=Trace] Channel finished. Elapsed 00:00:00.8757638.
[Source=AutoMLExperiment-ChildContext, Kind=Trace] [Source=ObjectDetectionTrainer; TrainModel, Kind=Trace] Channel disposed
System.Runtime.InteropServices.ExternalException (0x80004005): select(): index 0 out of range for tensor of size [0, 256, 3, 3] at dimension 0
Exception raised from select_symint at ../aten/src/ATen/native/TensorShape.cpp:1813 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x71cecc086047 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libc10.so)
frame #1: + 0x111a36a (0x718de24ec36a in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #2: + 0x2c01de3 (0x718de3fd3de3 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #3: + 0x2c01fa9 (0x718de3fd3fa9 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #4: at::_ops::select_int::redispatch(c10::DispatchKeySet, at::Tensor const&, long, c10::SymInt) + 0xc5 (0x718de3bcfee5 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #5: + 0x4a85709 (0x718de5e57709 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #6: + 0x4a85a3c (0x718de5e57a3c in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #7: at::_ops::select_int::redispatch(c10::DispatchKeySet, at::Tensor const&, long, c10::SymInt) + 0xc5 (0x718de3bcfee5 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #8: + 0x43931ca (0x718de57651ca in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #9: + 0x439397c (0x718de576597c in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #10: at::_ops::select_int::call(at::Tensor const&, long, c10::SymInt) + 0x1b0 (0x718de3c31670 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #11: + 0x5747b98 (0x718de6b19b98 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #12: + 0x57483c4 (0x718de6b1a3c4 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #13: torch::nn::init::kaiming_uniform_(at::Tensor, double, c10::variant, c10::variant) + 0x64 (0x718de6b1aa64 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #14: + 0x57a94f4 (0x718de6b7b4f4 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #15: + 0x57af5db (0x718de6b815db in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #16: torch::nn::Conv2dImpl::Conv2dImpl(torch::nn::ConvOptions<2ul>) + 0x2a8 (0x718de6b77e98 in /root/.local/share/ModelBuilder/torchsharp-cpu-0.101.5/libtorch_cpu.so)
frame #17: + 0x163578 (0x718da3363578 in /root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/libLibTorchSharp.so)
frame #18: + 0x11028f (0x718da331028f in /root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/libLibTorchSharp.so)
frame #19: THSNN_Conv2d_ctor + 0xfc (0x718da330347c in /root/.dotnet/tools/.store/mlnet-linux-x64/16.18.2/mlnet-linux-x64/16.18.2/tools/net8.0/any/libLibTorchSharp.so)
frame #20: [0x71ced0d2dce3]

at TorchSharp.torch.CheckForErrors()
at TorchSharp.torch.nn.Conv2d(Int64 inputChannel, Int64 outputChannel, Int64 kernelSize, Int64 stride, Int64 padding, Int64 dilation, PaddingModes paddingMode, Int64 groups, Boolean bias, Device device, Nullable`1 dtype)
at Microsoft.ML.TorchSharp.AutoFormerV2.RetinaHead..ctor(Int32 numClasses, Int32 inChannels, Int32 stackedConvs, Int32 featChannels, Int32 numBasePriors)
at Microsoft.ML.TorchSharp.AutoFormerV2.AutoFormerV2..ctor(Int32 numClasses, List`1 embedChannels, List`1 depths, List`1 numHeads, Device device)
at Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer.Trainer..ctor(ObjectDetectionTrainer parent, IChannel ch, IDataView input)
at Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain`1.Fit(IDataView input)
at Microsoft.ML.AutoML.SweepablePipelineRunner.Run(TrialSettings settings)
at Microsoft.ML.AutoML.SweepablePipelineRunner.RunAsync(TrialSettings settings, CancellationToken ct)
at Microsoft.ML.AutoML.AutoMLExperiment.RunAsync(CancellationToken ct)
at Microsoft.ML.ModelBuilder.AutoMLService.LocalObjectDetectionExperiment.ExecuteAsync(IDataView trainData, IDataView validateData, CancellationToken ct) in /_/src/Microsoft.ML.ModelBuilder.AutoMLService/Experiments/LocalObjectDetectionExperiment.cs:line 133
at Microsoft.ML.ModelBuilder.AutoMLEngine.StartTrainingAsync(ITrainingConfiguration config, PathConfiguration pathConfig, CancellationToken userCancellationToken) in /_/src/Microsoft.ML.ModelBuilder.AutoMLService/AutoMLEngineService/AutoMLEngine.cs:line 178
at Microsoft.ML.CLI.Runners.AutoMLRunner.ExecuteAsync() in /_/src/mlnet/Runners/AutoMLRunner.cs:line 95
at Microsoft.ML.CLI.Program.TrainAsync(ITrainingConfiguration trainingConfiguration, PathConfiguration pathConfig, AutoMLServiceLogLevel logLevel) in /_/src/mlnet/Program.cs:line 428
at Microsoft.ML.CLI.Program.<>c.<b__5_4>d.MoveNext() in /_/src/mlnet/Program.cs:line 183
--- End of stack trace from previous location ---
at System.CommandLine.Invocation.CommandHandler.GetExitCodeAsync(Object value, InvocationContext context)
at System.CommandLine.Invocation.ModelBindingCommandHandler.InvokeAsync(InvocationContext context)
at System.CommandLine.Invocation.InvocationPipeline.<>c__DisplayClass4_0.<b__0>d.MoveNext()
--- End of stack trace from previous location ---
at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass23_0.<b__0>d.MoveNext()
--- End of stack trace from previous location ---
at Microsoft.ML.CLI.Program.<>c__DisplayClass5_0.<b__11>d.MoveNext() in /_/src/mlnet/Program.cs:line 360
--- End of stack trace from previous location ---
at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<b__24_0>d.MoveNext()
--- End of stack trace from previous location ---
at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass22_0.<b__0>d.MoveNext()
--- End of stack trace from previous location ---
at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass11_0.<b__0>d.MoveNext()
--- End of stack trace from previous location ---
at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<b__10_0>d.MoveNext()
--- End of stack trace from previous location ---
at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass14_0.<b__0>d.MoveNext()

```

**To Reproduce**
Steps to reproduce the behavior:
1. Follow steps in [ML.NET object detection turorial](https://learn.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-model-builder#create-a-new-vott-project), create project in `$HOME/docker/mlnet/Stop-Signs/` and export `$HOME/docker/mlnet/Stop-Signs/vott-json-export/StopSignObjDetection-export.json` file.
2. Move dataset to `$HOME/docker/mlnet`.
3. Create container `sudo docker run --name sdk8 --gpus all -it --rm --ipc=host -v $HOME/docker/mlnet:/app mcr.microsoft.com/dotnet/nightly/sdk:8.0 bash`
4. (Command in container as shown below)
5. Install mlnet-cli `dotnet tool install --global mlnet-linux-x64`
6. `export PATH=$PATH:/root/.dotnet/tools`
7. `cd /app/Stop-Signs`
8. `mlnet object-detection --dataset ./vott-json-export/StopSignObjDetection-export.json`
9. See error

**Expected behavior**
Finish object detection training.

**Additional context**
Classification and image-classification performed very well. 👏👏👏