Add support for multi-dimensional arrays for model input/output.

[jannickj]

I have a fully working tensorflow model and I litterally just need the last step of having C# run my model, but I am stuck on a null exception.

I have a very simple setup, and I've locked down both sequence length and batch size, however no matter what i do it gives me the exception:

  at Microsoft.ML.Data.TypedCursorable`1.TypedRowBase.<>c__DisplayClass8_0`1.<CreateDirectVBufferSetter>b__0(TRow row)
   at Microsoft.ML.Data.TypedCursorable`1.TypedRowBase.FillValues(TRow row)
   at Microsoft.ML.Data.TypedCursorable`1.RowImplementation.FillValues(TRow row)
   at Microsoft.ML.PredictionEngineBase`2.FillValues(TDst prediction)
   at Microsoft.ML.PredictionEngine`2.Predict(TSrc example, TDst& prediction)
   at MyProject.Model.Run() in 

I have tested that the model works in python and I've made 100% sure the dimensions fit exactly.

public record Features
	{

		[ColumnName("x_1")]
		[VectorType(1, 41, 3)]
		public int[,,] UnigramWindows { get; set; } = null!;
		[ColumnName("x_2")]
		[VectorType(1, 41, 3)]
		public int[,,] BigramWindows { get; set; } = null!;
		[ColumnName("x_3")]
		[VectorType(1, 41, 3)]
		public int[,,] CharTypeWindows { get; set; } = null!;
		[ColumnName("x_4")]
		[VectorType(1, 41, 41)]
		public int[,,] WordsStartingAt { get; set; } = null!;
		[ColumnName("x_5")]
		[VectorType(1, 41, 41)]
		public int[,,] WordsEndingAt { get; set; } = null!;
		[ColumnName("x")]
		[VectorType(1)]
		public int[] SeqLen { get; set; } = null!;
	}

private record Output
{
	[VectorType(1, 41, 6)]
	public float[,,] Identity;
}


private static ITransformer LoadModel(
	MLContext mlContext,
	string modelPath)
{
	var tfModel = mlContext.Model
		.LoadTensorFlowModel(modelPath);
	var schema = tfModel.GetModelSchema();
	var revSchema = schema.Reverse().ToArray();
	var pipeline =
		tfModel
		.ScoreTensorFlowModel(
				outputColumnNames: new[] { "Identity" },
				inputColumnNames:
			 	new[] {
			 		"x",
			 		"x_1",
			 		"x_2",
			 		"x_3",
			 		"x_4",
			 		"x_5",
			 	},
				addBatchDimensionInput: false);



	var dataView = mlContext.Data.LoadFromEnumerable(Enumerable.Empty<Features>());
	ITransformer mlModel = pipeline.Fit(dataView);

	return mlModel;
}

public static run() 
{
        var model = LoadModel(mlContext, "model.pb");
	var predictionEngine = mlContext
		.Model
		.CreatePredictionEngine<Features, Output>(model);

        var res = predictionEngine.Predict(features);

	Console.WriteLine(System.Text.Json.JsonSerializer.Serialize(res));
}

[jannickj]

To any unfortunate soul who've had to deal with the same issue, I finally figured it out. 2d Arrays are not supported in dotnet ml, you're supposed to flatten the arrays yourself ><

[michaelgsharp]

@jannickj sorry for the confusion about this. This is something that we are discussing. As we are working on adding TorchSharp support to ML.NET, this will probably become a larger issue, so we are planning on revisiting this and discussing it again in the future.

[jannickj]

I think a simple fix for now would just be to throw an exception that says multidimensional arrays are not supported the problem is null exception makes figuring it out very obscure.

[KonradZaremba]

Ok so just to clarify. If I load tf model to ml.net that needs as input matrix [,] will I get proper output?

[julianogimenez]

Any news on that?
I'm workint in a POC for a customer.
I have a tensortflow model (N,160,6) but Im not able to input an array.
How can I do that?

[jannickj]

@julianogimenez you just have to squeze your multidim array into a single dim array i.e from (N, 160, 6) -> (N * 160 * 6,)