Adding `logical_and` operator (#338)

Relative unit test in `OperationTest`.

src/TensorFlowNET.Core/APIs/tf.math.cs

@@ -189,6 +189,9 @@ namespace Tensorflow
         public static Tensor log1p(Tensor x, string name = null)
             => gen_math_ops.log1p(x, name);
 
+        public static Tensor logical_and(Tensor x, Tensor y, string name = null)
+            => gen_math_ops.logical_and(x, y, name);
+
         /// <summary>
         /// Clips tensor values to a specified min and max.
         /// </summary>

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -350,6 +350,13 @@ namespace Tensorflow
             return _op.outputs[0];
         }
 
+        public static Tensor logical_and(Tensor x, Tensor y, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("LogicalAnd", name, args: new { x, y });
+
+            return _op.outputs[0];
+        }
+
         public static Tensor squared_difference(Tensor x, Tensor y, string name = null)
         {
             var _op = _op_def_lib._apply_op_helper("SquaredDifference", name, args: new { x, y, name });

test/TensorFlowNET.UnitTest/OperationsTest.cs

@@ -130,6 +130,22 @@ namespace TensorFlowNET.UnitTest
             }
         }
 
+        [TestMethod]
+        public void logicalAndTest()
+        {
+            var a = tf.constant(new[] {1f, 2f, 3f, 4f, -4f, -3f, -2f, -1f});
+            var b = tf.less(a, 0f);
+            var c = tf.greater(a, 0f);
+            var d = tf.cast(tf.logical_and(b, c), tf.int32);
+            var check = np.array(new[] { 0, 0, 0, 0, 0, 0, 0, 0 });
+
+            using (var sess = tf.Session())
+            {
+                var o = sess.run(d);
+                Assert.IsTrue(o.array_equal(check));
+            }
+        }
+
         [TestMethod]
         public void addOpTests()
         {