diff --git a/src/TensorFlowNET.Core/APIs/tf.queue.cs b/src/TensorFlowNET.Core/APIs/tf.queue.cs
index a5dfac15..f81f5726 100644
--- a/src/TensorFlowNET.Core/APIs/tf.queue.cs
+++ b/src/TensorFlowNET.Core/APIs/tf.queue.cs
@@ -52,7 +52,6 @@ namespace Tensorflow
             => new PaddingFIFOQueue(capacity,
                 new [] { dtype },
                 new[] { shape },
-                new[] { name },
                 shared_name: shared_name,
                 name: name);
 
diff --git a/src/TensorFlowNET.Core/Gradients/nn_grad.cs b/src/TensorFlowNET.Core/Gradients/nn_grad.cs
index 53ee9699..7b5d2ea7 100644
--- a/src/TensorFlowNET.Core/Gradients/nn_grad.cs
+++ b/src/TensorFlowNET.Core/Gradients/nn_grad.cs
@@ -47,6 +47,15 @@ namespace Tensorflow.Gradients
             return new Tensor[] { gen_nn_ops.relu_grad(grads[0], op.outputs[0]) };
         }
 
+        [RegisterGradient("LeakyRelu")]
+        public static Tensor[] _LeakyReluGrad(Operation op, Tensor[] grads)
+        {
+            var grad = grads[0];
+            var x = op.inputs[0];
+            var alpha = (float)op.get_attr("alpha");
+            return new Tensor[] { gen_nn_ops.leaky_relu_grad(grad, x, alpha: alpha)};
+        }
+
         /// <summary>
         /// The derivative of the softmax nonlinearity.
         /// </summary>
diff --git a/src/TensorFlowNET.Core/Operations/NnOps/gen_nn_ops.cs b/src/TensorFlowNET.Core/Operations/NnOps/gen_nn_ops.cs
index c79f89b2..82085683 100644
--- a/src/TensorFlowNET.Core/Operations/NnOps/gen_nn_ops.cs
+++ b/src/TensorFlowNET.Core/Operations/NnOps/gen_nn_ops.cs
@@ -284,6 +284,18 @@ namespace Tensorflow.Operations
             });
 
             return _op.outputs[0];
+        }
+
+        public static Tensor leaky_relu_grad(Tensor gradients, Tensor features, float alpha = 0.2f, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("LeakyReluGrad", name: name, args: new
+            {
+                gradients,
+                features,
+                alpha
+            });
+
+            return _op.output;
         }
 
         public static Tensor softmax(Tensor logits, string name = null)