diff --git a/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs b/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
index fd4f93fc..45b236c7 100644
--- a/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
+++ b/src/TensorFlowNET.Core/NumPy/NDArray.Implicit.cs
@@ -107,9 +107,15 @@ namespace Tensorflow.NumPy
         public static implicit operator NDArray(bool value)
             => new NDArray(value);
 
+        public static implicit operator NDArray(byte value)
+            => new NDArray(value);
+
         public static implicit operator NDArray(int value)
             => new NDArray(value);
 
+        public static implicit operator NDArray(long value)
+            => new NDArray(value);
+
         public static implicit operator NDArray(float value)
             => new NDArray(value);
 
diff --git a/test/TensorFlowNET.UnitTest/Dataset/DatasetTest.cs b/test/TensorFlowNET.UnitTest/Dataset/DatasetTest.cs
index 8317346e..875e5001 100644
--- a/test/TensorFlowNET.UnitTest/Dataset/DatasetTest.cs
+++ b/test/TensorFlowNET.UnitTest/Dataset/DatasetTest.cs
@@ -2,6 +2,7 @@
 using System;
 using System.Linq;
 using static Tensorflow.Binding;
+using static Tensorflow.KerasApi;
 
 namespace TensorFlowNET.UnitTest.Dataset
 {
@@ -195,5 +196,19 @@ namespace TensorFlowNET.UnitTest.Dataset
 
             Assert.IsFalse(allEqual);
         }
+        [TestMethod]
+        public void GetData()
+        {
+            var vocab_size = 20000;
+            var dataset = keras.datasets.imdb.load_data(num_words: vocab_size);
+            var x_train = dataset.Train.Item1;
+            Assert.AreEqual(x_train.dims[0], 25000);
+            var y_train = dataset.Train.Item2;
+            Assert.AreEqual(y_train.dims[0], 25000);
+            var x_val = dataset.Test.Item1;
+            Assert.AreEqual(x_val.dims[0], 25000);
+            var y_val = dataset.Test.Item2;
+            Assert.AreEqual(y_val.dims[0], 25000);
+        }
     }
 }