fix AutoNumPy crash when in multiple thread.

src/TensorFlowNET.Core/Graphs/Graph.Import.cs

@@ -52,7 +52,6 @@ namespace Tensorflow
             using (var status = new Status())
             using (var graph_def = new Buffer(bytes))
             {
-                as_default();
                 c_api.TF_ImportGraphDefOptionsSetPrefix(opts.Handle, prefix);
                 c_api.TF_GraphImportGraphDef(_handle, graph_def.Handle, opts.Handle, status.Handle);
                 status.Check(true);

src/TensorFlowNET.Core/NumPy/AutoNumPyAttribute.cs

@@ -2,6 +2,7 @@
 using System;
 using System.Collections.Generic;
 using System.Diagnostics;
+using System.Threading;
 using static Tensorflow.Binding;
 
 namespace Tensorflow.NumPy
@@ -10,9 +11,12 @@ namespace Tensorflow.NumPy
     public sealed class AutoNumPyAttribute : OnMethodBoundaryAspect
     {
         bool _changedMode = false;
-
+        bool _locked = false;
+        static object locker = new Object();
         public override void OnEntry(MethodExecutionArgs args)
         {
+            Monitor.Enter(locker, ref _locked);
+            
             if (!tf.executing_eagerly())
             {
                 tf.Context.eager_mode();
@@ -24,6 +28,9 @@ namespace Tensorflow.NumPy
         {
             if (_changedMode)
                 tf.Context.restore_mode();
+
+            if (_locked)
+                Monitor.Exit(locker);
         }
     }
 }

src/TensorFlowNET.Core/Numpy/NDArray.cs

@@ -30,6 +30,7 @@ namespace Tensorflow.NumPy
 
         [AutoNumPy]
         public NDArray reshape(Shape newshape) => new NDArray(tf.reshape(this, newshape));
+        [AutoNumPy]
         public NDArray astype(TF_DataType dtype) => new NDArray(math_ops.cast(this, dtype));
         public NDArray ravel() => throw new NotImplementedException("");
         public void shuffle(NDArray nd) => np.random.shuffle(nd);

src/TensorFlowNET.Core/Operations/math_ops.cs

@@ -126,7 +126,6 @@ namespace Tensorflow
             return tf_with(ops.name_scope(name, "Cast", new { x }), scope =>
             {
                 name = scope;
-                x = ops.convert_to_tensor(x, name: "x");
                 if (x.dtype.as_base_dtype() != base_type)
                     x = gen_math_ops.cast(x, base_type, name: name);
 

src/TensorFlowNET.Core/Tensors/constant_op.cs

@@ -101,7 +101,7 @@ namespace Tensorflow
                 value is NDArray nd &&
                 nd.dtype != dtype)
             {
-                value = nd.astype(dtype);
+                value = math_ops.cast(nd, dtype);
             }
 
             // non ascii char

test/TensorFlowNET.UnitTest/Utilities/FluentExtension.cs

@@ -197,13 +197,6 @@ namespace TensorFlowNET.UnitTest
             return new AndConstraint<NDArrayAssertions>(this);
         }
 
-        public AndConstraint<NDArrayAssertions> BeScalar(object value)
-        {
-            Subject.shape.IsScalar.Should().BeTrue();
-            Subject.GetValue().Should().Be(value);
-            return new AndConstraint<NDArrayAssertions>(this);
-        }
-
         public AndConstraint<NDArrayAssertions> BeOfType(Type typeCode)
         {
             Subject.dtype.Should().Be(typeCode);