Added unit-tests for autocasting mechanism.

test/TensorFlowNET.UnitTest/SessionTest.cs

@@ -7,6 +7,7 @@ using System.Runtime.CompilerServices;
 using System.Text;
 using FluentAssertions;
 using Google.Protobuf;
+using NumSharp.Backends;
 using Tensorflow;
 using Tensorflow.Util;
 using static Tensorflow.Binding;
@@ -131,5 +132,61 @@ namespace TensorFlowNET.UnitTest
                 }
             }
         }
+
+        [TestMethod]
+        public void Autocast_Case1()
+        {
+            var sess = tf.Session().as_default();
+            var input = tf.placeholder(tf.float64, shape: new TensorShape(6));
+            var op = tf.reshape(input, new int[] {2, 3});
+            sess.run(tf.global_variables_initializer());
+            var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6)));
+
+            ret.Should().BeOfType<double>().And.BeShaped(2, 3).And.BeOfValues(1, 2, 3, 4, 5, 6);
+            print(ret.dtype);
+            print(ret);
+        }
+
+        [TestMethod]
+        public void Autocast_Case2()
+        {
+            var sess = tf.Session().as_default();
+            var input = tf.placeholder(tf.float64, shape: new TensorShape(6));
+            var op = tf.reshape(input, new int[] {2, 3});
+            sess.run(tf.global_variables_initializer());
+            var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6).astype(NPTypeCode.Single) + 0.1f));
+
+            ret.Should().BeOfType<double>().And.BeShaped(2, 3).And.BeOfValuesApproximately(0.001d, 1.1, 2.1, 3.1, 4.1, 5.1, 6.1);
+            print(ret.dtype);
+            print(ret);
+        }
+
+        [TestMethod]
+        public void Autocast_Case3()
+        {
+            var sess = tf.Session().as_default();
+            var input = tf.placeholder(tf.int16, shape: new TensorShape(6));
+            var op = tf.reshape(input, new int[] {2, 3});
+            sess.run(tf.global_variables_initializer());
+            var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6).astype(NPTypeCode.Single) + 0.1f));
+
+            ret.Should().BeOfType<short>().And.BeShaped(2, 3).And.BeOfValues(1, 2, 3, 4, 5, 6);
+            print(ret.dtype);
+            print(ret);
+        }
+
+        [TestMethod]
+        public void Autocast_Case4()
+        {
+            var sess = tf.Session().as_default();
+            var input = tf.placeholder(tf.@byte, shape: new TensorShape(6));
+            var op = tf.reshape(input, new int[] {2, 3});
+            sess.run(tf.global_variables_initializer());
+            var ret = sess.run(op, feed_dict: (input, np.array(1, 2, 3, 4, 5, 6).astype(NPTypeCode.Single) + 0.1f));
+
+            ret.Should().BeOfType<byte>().And.BeShaped(2, 3).And.BeOfValues(1, 2, 3, 4, 5, 6);
+            print(ret.dtype);
+            print(ret);
+        }
     }
 }