[HOTFIX] Add missing iris.py and fix knnc bug

prototorch/datasets/iris.py

@@ -0,0 +1,15 @@
+"""Thin wrapper for the Iris classification dataset from sklearn.
+
+URL:
+    https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html
+
+"""
+
+from prototorch.datasets.abstract import NumpyDataset
+from sklearn.datasets import load_iris
+
+
+class Iris(NumpyDataset):
+    def __init__(self):
+        x, y = load_iris(return_X_y=True)
+        super().__init__(x, y)

prototorch/functions/competitions.py

@@ -38,6 +38,7 @@ def wtac(distances, labels):
 
 def knnc(distances, labels, k=1):
     winning_indices = torch.topk(-distances, k=k, dim=1).indices
-    winning_labels = torch.mode(labels[winning_indices].squeeze(),
+    # winning_labels = torch.mode(labels[winning_indices].squeeze(),
-                                dim=1).values
+    #                             dim=1).values
+    winning_labels = torch.mode(labels[winning_indices], dim=1).values
     return winning_labels

tests/test_functions.py

@@ -4,7 +4,6 @@ import unittest
 
 import numpy as np
 import torch
-
 from prototorch.functions import (activations, competitions, distances,
                                   initializers, losses)
 
@@ -139,7 +138,7 @@ class TestCompetitions(unittest.TestCase):
     def test_knnc_k1(self):
         d = torch.tensor([[2.0, 3.0, 1.99, 3.01], [2.0, 3.0, 2.01, 3.0]])
         labels = torch.tensor([0, 1, 2, 3])
-        actual = competitions.knnc(d, labels, k=torch.tensor([1]))
+        actual = competitions.knnc(d, labels, k=1)
         desired = torch.tensor([2, 0])
         mismatch = np.testing.assert_array_almost_equal(actual,
                                                         desired,