using NumSharp.Core;

using System;

using System.Collections.Generic;

using System.Text;

using tensor_pb2 = Tensorflow;

namespace Tensorflow

{

public static class tensor_util

{

public static TensorProto make_tensor_proto(object values, Type dtype = null)

{

NDArray nparray;

TensorProto tensor_proto = null;

TensorShape tensor_shape = new TensorShape(0);

switch (values)

{

case float val:

nparray = np.array(new float[] { val }, np.float32);

tensor_proto = new tensor_pb2.TensorProto

{

Dtype = DataType.DtFloat,

TensorShape = tensor_shape.as_shape().as_proto()

};

tensor_proto.FloatVal.Add(val);

break;

case double val:

nparray = np.array(new double[] { val }, np.float64);

tensor_proto = new tensor_pb2.TensorProto

{

Dtype = DataType.DtDouble,

TensorShape = tensor_shape.as_shape().as_proto()

};

tensor_proto.DoubleVal.Add(val);

break;

case string val:

nparray = np.array(new string[] { val }, np.chars);

tensor_proto = new tensor_pb2.TensorProto

{

Dtype = DataType.DtString,

TensorShape = tensor_shape.as_shape().as_proto()

};

tensor_proto.StringVal.Add(Google.Protobuf.ByteString.CopyFrom(val, Encoding.UTF8));

break;

}

return tensor_proto;

}

}

}