add flip_left_right, flip_up_down

adds flip_left_right, flip_up_down, and a couple of functions that those two depend on (_flip & fix_image_flip_shape)

src/TensorFlowNET.Core/Operations/image_ops_impl.cs

@@ -71,6 +71,18 @@ namespace Tensorflow
                 return new Operation[] {};
             }
         }
+       
+        internal static Tensor fix_image_flip_shape(Tensor image, Tensor result)
+        {
+            TensorShape image_shape = image.get_shape();
+            if (image_shape == tensor_shape.unknown_shape())
+            {
+                result.set_shape(new { null, null, null });
+            } else {
+                result.set_shape(image_shape);
+            }
+            return result;
+        }
 
         public static Tensor random_flip_up_down(Tensor image, int seed = 0)
             => _random_flip(image: image,
@@ -122,6 +134,32 @@ namespace Tensorflow
             }
         }
        
+        public static Tensor flip_left_right(Tensor image)
+            => _flip(image, 1, "flip_left_right");
+
+        public static Tensor flip_up_down(Tensor image)
+            => _flip(image, 1, "flip_up_down");
+
+        internal static Tensor _flip(Tensor image, int flip_index, string scope_name)
+        {
+            return tf_with(ops.name_scope(null, scope_name, new { image }), delegate
+            {
+                image = ops.convert_to_tensor(image, name: "image");
+                image = _AssertAtLeast3DImage(image);
+                TensorShape shape = image.get_shape();
+                if ( shape.NDims == 3 || shape.NDims == null )
+                {
+                    return fix_image_flip_shape(image, array_ops.reverse(image, new { flip_index }));
+                } else if ( shape.NDims == 4 )
+                {
+                    return array_ops.reverse(image, new { flip_index + 1 });
+                } else
+                {
+                    throw new ValueError("\'image\' must have either 3 or 4 dimensions.");
+                }
+            });
+        }
+       
         public static Tensor decode_image(Tensor contents, int channels = 0, TF_DataType dtype = TF_DataType.TF_UINT8,
             string name = null, bool expand_animations = true)
         {