np.argsort

src/TensorFlowNET.Core/NumPy/NumPy.Sorting.Searching.Counting.cs

@@ -14,7 +14,7 @@ namespace Tensorflow.NumPy
 
         [AutoNumPy]
         public static NDArray argsort(NDArray a, Axis axis = null)
-            => new NDArray(math_ops.argmax(a, axis ?? -1));
+            => new NDArray(sort_ops.argsort(a, axis: axis ?? -1));
 
         [AutoNumPy]
         public static (NDArray, NDArray) unique(NDArray a)

src/TensorFlowNET.Core/Operations/NnOps/gen_nn_ops.cs

@@ -281,7 +281,7 @@ namespace Tensorflow.Operations
                         data_format
                     }));
 
-        public static Tensor[] top_kv2(Tensor input, int k, bool sorted = true, string name = null)
+        public static Tensor[] top_kv2<T>(Tensor input, T k, bool sorted = true, string name = null)
         {
             var _op = tf.OpDefLib._apply_op_helper("TopKV2", name: name, args: new
             {

src/TensorFlowNET.Core/Operations/sort_ops.cs

@@ -0,0 +1,44 @@
+/*****************************************************************************
+   Copyright 2018 The TensorFlow.NET Authors. All Rights Reserved.
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+******************************************************************************/
+
+using Tensorflow.Operations;
+using static Tensorflow.Binding;
+
+namespace Tensorflow
+{
+    public class sort_ops
+    {
+        public static Tensor argsort(Tensor values, Axis axis = null, string direction = "ASCENDING", bool stable = false, string name = null)
+        {
+            axis = axis ?? new Axis(-1);
+            var k = array_ops.shape(values)[axis];
+            values = -values;
+            var (_, indices) = tf.Context.ExecuteOp("TopKV2", name,
+                new ExecuteOpArgs(values, k).SetAttributes(new
+                {
+                    sorted = true
+                }));
+            return indices;
+        }
+
+        public Tensor matrix_inverse(Tensor input, bool adjoint = false, string name = null)
+            => tf.Context.ExecuteOp("MatrixInverse", name,
+                new ExecuteOpArgs(input).SetAttributes(new
+                {
+                    adjoint
+                }));
+    }
+}

test/TensorFlowNET.UnitTest/NumPy/Array.Sorting.Test.cs

@@ -0,0 +1,34 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using Tensorflow;
+using Tensorflow.NumPy;
+using static Tensorflow.Binding;
+
+namespace TensorFlowNET.UnitTest.NumPy
+{
+    /// <summary>
+    /// https://numpy.org/doc/stable/user/basics.indexing.html
+    /// </summary>
+    [TestClass]
+    public class ArraySortingTest : EagerModeTestBase
+    {
+        /// <summary>
+        /// https://numpy.org/doc/stable/reference/generated/numpy.argsort.html
+        /// </summary>
+        [TestMethod]
+        public void argsort()
+        {
+            var x = np.array(new[] { 3, 1, 2 });
+            var ind = np.argsort(x);
+            Assert.AreEqual(ind, new[] { 1, 2, 0 });
+
+            var y = np.array(new[,] { { 0, 3 }, { 2, 2 } });
+            ind = np.argsort(y, axis: 0);
+            Assert.AreEqual(ind[0], new[] { 0, 1 });
+            Assert.AreEqual(ind[1], new[] { 1, 0 });
+        }
+    }
+}