Cant run mlnet on Linux

Here is my training-config:
```
{
"Scenario": "Regression",
"DataSource": {
"Type": "TabularFile",
"Version": 1,
"FilePath": "realcsv.txt",
"Delimiter": ";",
"DecimalMarker": ",",
"HasHeader": false,
"ColumnProperties": [
{
"ColumnName": "Date",
"ColumnPurpose": "Feature",
"ColumnDataFormat": "String",
"IsCategorical": false,
"Type": "Column",
"Version": 3
},
{
"ColumnName": "Scans",
"ColumnPurpose": "Label",
"ColumnDataFormat": "Single",
"IsCategorical": false,
"Type": "Column",
"Version": 3
}
]
},
"Environment": {
"Type": "LocalCPU",
"Version": 1
},
"RunHistory": {
"Version": 2,
"Type": "Result",
"Trials": [
{
"Version": 1,
"Type": "Trial",
"TrainerName": "FastForestRegression",
"Score": 0.0,
"RuntimeInSeconds": 0.372,
"Parameter": {
"_SCHEMA_": "e0 * e1 * e3",
"e0": {
"OutputColumnNames": [
"Date"
],
"InputColumnNames": [
"Date"
]
},
"e1": {
"InputColumnNames": [
"Date"
],
"OutputColumnName": "Features"
},
"e3": {
"NumberOfTrees": 4,
"NumberOfLeaves": 4,
"FeatureFraction": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e2": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"NumberOfTrees": 4,
"MaximumBinCountPerFeature": 255,
"FeatureFraction": 1.0,
"LearningRate": 0.099999999999999978,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e4": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"LearningRate": 1.0,
"NumberOfTrees": 4,
"SubsampleFraction": 1.0,
"MaximumBinCountPerFeature": 255,
"FeatureFraction": 1.0,
"L1Regularization": 2E-10,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e5": {
"L1Regularization": 1.0,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e6": {
"L1Regularization": 1.0,
"L2Regularization": 0.1,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
}
}
},
{
"Version": 1,
"Type": "Trial",
"TrainerName": "FastTreeRegression",
"Score": 0.0,
"RuntimeInSeconds": 0.04,
"Parameter": {
"_SCHEMA_": "e0 * e1 * e2",
"e0": {
"OutputColumnNames": [
"Date"
],
"InputColumnNames": [
"Date"
]
},
"e1": {
"InputColumnNames": [
"Date"
],
"OutputColumnName": "Features"
},
"e2": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"NumberOfTrees": 4,
"MaximumBinCountPerFeature": 254,
"FeatureFraction": 1.0,
"LearningRate": 0.099999999999999978,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e3": {
"NumberOfTrees": 4,
"NumberOfLeaves": 4,
"FeatureFraction": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e4": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"LearningRate": 1.0,
"NumberOfTrees": 4,
"SubsampleFraction": 1.0,
"MaximumBinCountPerFeature": 255,
"FeatureFraction": 1.0,
"L1Regularization": 2E-10,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e5": {
"L1Regularization": 1.0,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e6": {
"L1Regularization": 1.0,
"L2Regularization": 0.1,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
}
}
},
{
"Version": 1,
"Type": "Trial",
"TrainerName": "FastForestRegression",
"Score": 0.0,
"RuntimeInSeconds": 0.024,
"Parameter": {
"_SCHEMA_": "e0 * e1 * e3",
"e0": {
"OutputColumnNames": [
"Date"
],
"InputColumnNames": [
"Date"
]
},
"e1": {
"InputColumnNames": [
"Date"
],
"OutputColumnName": "Features"
},
"e3": {
"NumberOfTrees": 4,
"NumberOfLeaves": 4,
"FeatureFraction": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e2": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"NumberOfTrees": 4,
"MaximumBinCountPerFeature": 255,
"FeatureFraction": 1.0,
"LearningRate": 0.099999999999999978,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e4": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"LearningRate": 1.0,
"NumberOfTrees": 4,
"SubsampleFraction": 1.0,
"MaximumBinCountPerFeature": 255,
"FeatureFraction": 1.0,
"L1Regularization": 2E-10,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e5": {
"L1Regularization": 1.0,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e6": {
"L1Regularization": 1.0,
"L2Regularization": 0.1,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
}
}
},
{
"Version": 1,
"Type": "Trial",
"TrainerName": "FastTreeRegression",
"Score": 0.0,
"RuntimeInSeconds": 0.025,
"Parameter": {
"_SCHEMA_": "e0 * e1 * e2",
"e0": {
"OutputColumnNames": [
"Date"
],
"InputColumnNames": [
"Date"
]
},
"e1": {
"InputColumnNames": [
"Date"
],
"OutputColumnName": "Features"
},
"e2": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 28,
"NumberOfTrees": 4,
"MaximumBinCountPerFeature": 575,
"FeatureFraction": 0.99999999,
"LearningRate": 0.083949019229038066,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e3": {
"NumberOfTrees": 4,
"NumberOfLeaves": 4,
"FeatureFraction": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e4": {
"NumberOfLeaves": 4,
"MinimumExampleCountPerLeaf": 20,
"LearningRate": 1.0,
"NumberOfTrees": 4,
"SubsampleFraction": 1.0,
"MaximumBinCountPerFeature": 255,
"FeatureFraction": 1.0,
"L1Regularization": 2E-10,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e5": {
"L1Regularization": 1.0,
"L2Regularization": 1.0,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
},
"e6": {
"L1Regularization": 1.0,
"L2Regularization": 0.1,
"LabelColumnName": "Scans",
"FeatureColumnName": "Features"
}
}
}
],
"Estimators": {
"e0": "ConvertType",
"e1": "Concatenate",
"e2": "FastTreeRegression",
"e3": "FastForestRegression",
"e4": "LightGbmRegression",
"e5": "LbfgsPoissonRegressionRegression",
"e6": "SdcaRegression"
},
"Schema": "e0 * e1 * (e2 + e3 + e4 + e5 + e6)",
"MetricName": "RSquared"
},
"Type": "TrainingConfig",
"Version": 3,
"TrainingOption": {
"Version": 0,
"Type": "RegressionTrainingOption",
"TrainingTime": 10,
"LabelColumn": "Scans",
"Seed": 0
}
}
```
And here is my dataset(realcsv.txt):
```
Date;Scans
01.01.2023;10
02.01.2023;15
03.01.2023;8
04.01.2023;7
05.01.2023;15
06.01.2023;30
07.01.2023;10
08.01.2023;20
09.01.2023;17
10.01.2023;0
```

When running `mlnet train --training-config MLModelExample.mbconfig` on Linux I get following Error:
```
System.ArgumentException: The path is empty. (Parameter 'path')
at System.IO.Path.GetFullPath(String path)
at System.IO.FileInfo..ctor(String fileName)
at Microsoft.ML.ModelBuilder.AutoMLEngine.SaveModel(MLContext context, ITransformer model, DataViewSchema dataViewSchema, String location) in /_/src/Microsoft.ML.ModelBuilder.AutoMLService/AutoMLEngineService/AutoMLEngine.cs:line 365
at Microsoft.ML.ModelBuilder.AutoMLEngine.StartTrainingAsync(ITrainingConfiguration config, PathConfiguration pathConfig, CancellationToken userCancellationToken) in /_/src/Microsoft.ML.ModelBuilder.AutoMLService/AutoMLEngineService/AutoMLEngine.cs:line 153
at Microsoft.ML.CLI.Runners.AutoMLRunner.ExecuteAsync() in /_/src/mlnet/Runners/AutoMLRunner.cs:line 89
at Microsoft.ML.CLI.Program.TrainAsync(TrainingConfiguration trainingConfiguration, PathConfiguration pathConfig, AutoMLServiceLogLevel logLevel) in /_/src/mlnet/Program.cs:line 350
at Microsoft.ML.CLI.Program.<>c.<b__4_4>d.MoveNext() in /_/src/mlnet/Program.cs:line 178
--- 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__DisplayClass4_0.<b__9>d.MoveNext() in /_/src/mlnet/Program.cs:line 292
--- 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()
```