compiled.

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -35,7 +35,7 @@ Docs: https://tensorflownet.readthedocs.io</Description>
 13. Fix default graph and operation issue when import model.
 14. Fix TF_String endcode and decode.
 15. Fix Tensor memory leak.</PackageReleaseNotes>
-    <LangVersion>7.2</LangVersion>
+    <LangVersion>7.3</LangVersion>
     <FileVersion>0.10.7.2</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
     <PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>

src/TensorFlowNET.Core/Tensors/Tensor.Creation.cs

@@ -486,7 +486,7 @@ namespace Tensorflow
         {
             if (tensorDType == TF_DataType.TF_STRING && nd.dtype.Name == "Byte")
             {
-                var buffer = nd.Data<byte>();
+                var buffer = nd.ToArray<byte>();
                 var size = c_api.TF_StringEncodedSize((UIntPtr)buffer.Length);
                 var handle = TF_AllocateTensor(TF_DataType.TF_STRING, IntPtr.Zero, 0, (UIntPtr)((ulong)size + 8));
 
@@ -524,29 +524,30 @@ namespace Tensorflow
             switch (nd.dtype.Name)
             {
                 case "Boolean":
-                    var boolVals = Array.ConvertAll(nd1.Data<bool>(), x => Convert.ToByte(x));
+                    var boolVals = Array.ConvertAll(nd1.ToArray<bool>(), x => Convert.ToByte(x));
                     Marshal.Copy(boolVals, 0, dotHandle, nd.size);
                     break;
                 case "Int16":
-                    Marshal.Copy(nd1.Data<short>(), 0, dotHandle, nd.size);
+                    Marshal.Copy(nd1.ToArray<short>(), 0, dotHandle, nd.size);
                     break;
                 case "Int32":
-                    Marshal.Copy(nd1.Data<int>(), 0, dotHandle, nd.size);
+                    Marshal.Copy(nd1.ToArray<int>(), 0, dotHandle, nd.size);
                     break;
                 case "Int64":
-                    Marshal.Copy(nd1.Data<long>(), 0, dotHandle, nd.size);
+                    Marshal.Copy(nd1.ToArray<long>(), 0, dotHandle, nd.size);
                     break;
                 case "Single":
-                    Marshal.Copy(nd1.Data<float>(), 0, dotHandle, nd.size);
+                    Marshal.Copy(nd1.ToArray<float>(), 0, dotHandle, nd.size);
                     break;
                 case "Double":
-                    Marshal.Copy(nd1.Data<double>(), 0, dotHandle, nd.size);
+                    Marshal.Copy(nd1.ToArray<double>(), 0, dotHandle, nd.size);
                     break;
                 case "Byte":
-                    Marshal.Copy(nd1.Data<byte>(), 0, dotHandle, nd.size);
+                    Marshal.Copy(nd1.ToArray<byte>(), 0, dotHandle, nd.size);
                     break;
                 case "String":
-                    return new Tensor(UTF8Encoding.UTF8.GetBytes(nd.Data<string>(0)), TF_DataType.TF_STRING);
+                    throw new NotImplementedException($"Marshal.Copy failed for {nd.dtype.Name}.");
+                    //return new Tensor(UTF8Encoding.UTF8.GetBytes(nd.ToArray<string>(0)), TF_DataType.TF_STRING);
                 default:
                     throw new NotImplementedException($"Marshal.Copy failed for {nd.dtype.Name}.");
             }

src/TensorFlowNET.Core/Tensors/Tensor.cs

@@ -196,7 +196,7 @@ namespace Tensorflow
             // [offset1, offset2,...,offsetn, s1size, s1bytes, s2size, s2bytes,...,snsize,snbytes]
             //
             long size = 1;
-            foreach (var s in TensorShape.Dimensions)
+            foreach (var s in TensorShape.dims)
                 size *= s;
 
             var buffer = new byte[size][];

test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionNN.cs

@@ -127,7 +127,7 @@ namespace TensorFlowNET.Examples
         public void Train(Session sess)
         {
             // Number of training iterations in each epoch
-            var num_tr_iter = mnist.Train.Labels.len / batch_size;
+            var num_tr_iter = mnist.Train.Labels.shape[0] / batch_size;
 
             var init = tf.global_variables_initializer();
             sess.run(init);