using Tensorflow.NumPy;

using System.Collections.Generic;

using Tensorflow.Data;

namespace Tensorflow

{

public class DatasetManager

{

public IDatasetV2 from_generator<T>(IEnumerable<T> generator, TF_DataType[] output_types, Shape[] output_shapes)

=> new GeneratorDataset();

/// <summary>

/// Creates a `Dataset` with a single element, comprising the given tensors.

/// </summary>

/// <param name="tensors"></param>

/// <returns></returns>

public IDatasetV2 from_tensors(NDArray tensors)

=> new TensorDataset(tensors);

public IDatasetV2 from_tensors(Tensors tensors)

=> new TensorDataset(tensors);

public IDatasetV2 from_tensor_slices(Tensor features, Tensor labels)

=> new TensorSliceDataset(features, labels);

public IDatasetV2 from_tensor_slices(Tensor tensor)

=> new TensorSliceDataset(tensor);

public IDatasetV2 from_tensor_slices(string[] array)

=> new TensorSliceDataset(array);

public IDatasetV2 from_tensor_slices(NDArray array)

=> new TensorSliceDataset(array);

public IDatasetV2 range(int count, TF_DataType output_type = TF_DataType.TF_INT64)

=> new RangeDataset(count, output_type: output_type);

public IDatasetV2 range(int start, int stop, int step = 1, TF_DataType output_type = TF_DataType.TF_INT64)

=> new RangeDataset(stop, start: start, step: step, output_type: output_type);

public IDatasetV2 zip(params IDatasetV2[] ds)

=> new ZipDataset(ds);

}

}