np.random.normal

src/TensorFlowNET.Core/NumPy/Implementation/RandomizedImpl.cs

@@ -37,6 +37,6 @@ namespace Tensorflow.NumPy
         }
 
         public NDArray normal(float loc = 0.0f, float scale = 1.0f, Shape size = null)
-            => throw new NotImplementedException("");
+            => new NDArray(random_ops.random_normal(size ?? Shape.Scalar, mean: loc, stddev: scale));
     }
 }

src/TensorFlowNET.Core/NumPy/NDArray.Index.cs

@@ -47,6 +47,8 @@ namespace Tensorflow.NumPy
                     return GetData(mask.ToArray<int>());
                 else if (mask.dtype == TF_DataType.TF_INT64)
                     return GetData(mask.ToArray<long>().Select(x => Convert.ToInt32(x)).ToArray());
+                else if (mask.dtype == TF_DataType.TF_FLOAT)
+                    return GetData(mask.ToArray<float>().Select(x => Convert.ToInt32(x)).ToArray());
 
                 throw new NotImplementedException("");
             }

src/TensorFlowNET.Core/NumPy/Numpy.Math.cs

@@ -18,6 +18,9 @@ namespace Tensorflow.NumPy
         [AutoNumPy]
         public static NDArray log(NDArray x) => new NDArray(tf.log(x));
 
+        [AutoNumPy]
+        public static NDArray mean(NDArray x) => new NDArray(math_ops.reduce_mean(x));
+
         [AutoNumPy]
         public static NDArray multiply(NDArray x1, NDArray x2) => new NDArray(tf.multiply(x1, x2));
 

test/TensorFlowNET.UnitTest/EagerModeTestBase.cs

@@ -14,6 +14,12 @@ namespace TensorFlowNET.UnitTest
             tf.Context.ensure_initialized();
         }
 
+        public bool Equal(float f1, float f2)
+        {
+            var tolerance = .000001f;
+            return Math.Abs(f1 - f2) <= tolerance;
+        }
+
         public bool Equal(float[] f1, float[] f2)
         {
             bool ret = false;

test/TensorFlowNET.UnitTest/NumPy/Randomize.Test.cs

@@ -23,5 +23,15 @@ namespace TensorFlowNET.UnitTest.NumPy
             Assert.AreEqual(x.shape, 10);
             Assert.AreNotEqual(x.ToArray<int>(), y.ToArray<int>());
         }
+
+        /// <summary>
+        /// https://numpy.org/doc/stable/reference/random/generated/numpy.random.normal.html
+        /// </summary>
+        [TestMethod]
+        public void normal()
+        {
+            var x = np.random.normal(0, 0.1f, 1000);
+            Equal(np.mean(x), 0f);
+        }
     }
 }