[Test error fix]: Fixed the error caused by flake8

Author: nabenabe0928

.gitignore

@@ -142,3 +142,4 @@ tmp/
 # private
 grep.py
 memo.txt
+private_test.py

autoPyTorch/datasets/base_dataset.py

@@ -184,7 +184,8 @@ def __getitem__(self, index: int, train: bool = True) -> Tuple[np.ndarray, ...]:
 
         return X, Y
 
-    def __len__(self) -> int: return self.train_tensors[0].shape[0]
+    def __len__(self) -> int:
+        return self.train_tensors[0].shape[0]
 
     def _get_indices(self) -> np.ndarray:
         return self.rng.permutation(len(self)) if self.shuffle else np.arange(len(self))

private_test.ipynb

@@ -0,0 +1,99 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(array([7, 6, 2, 5, 9, 1, 0, 8, 3]), array([4])),\n",
+       " (array([1, 2, 5, 4, 6, 9, 0, 8, 7]), array([3])),\n",
+       " (array([7, 0, 9, 3, 4, 6, 5, 1, 8]), array([2]))]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from typing import Protocol, List, Tuple, Dict\n",
+    "import numpy as np\n",
+    "from sklearn.model_selection import ShuffleSplit\n",
+    "\n",
+    "\n",
+    "\"\"\"TEST 1 (The original code)\"\"\"\n",
+    "class CROSS_VAL_FN(Protocol):\n",
+    "    def __call__(self,\n",
+    "                 num_splits: int,\n",
+    "                 indices: np.ndarray) -> List[Tuple[np.ndarray, np.ndarray]]:\n",
+    "        ...\n",
+    "        \n",
+    "\n",
+    "def cv1(num_splits: int, indices: np.ndarray) -> List[Tuple[np.ndarray, np.\n",
+    "    ndarray]]: \n",
+    "    cv = ShuffleSplit(n_splits=num_splits) \n",
+    "    splits = list(cv.split(indices)) \n",
+    "    return splits\n",
+    "\n",
+    "\n",
+    "cvs: Dict[str, CROSS_VAL_FN] = {\"cv1\": cv1}\n",
+    "cvs[\"cv1\"](3, np.arange(10))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(array([6, 0, 3, 7, 5, 9, 4, 1, 8]), array([2])),\n",
+       " (array([3, 9, 0, 4, 1, 7, 5, 2, 6]), array([8])),\n",
+       " (array([3, 8, 1, 4, 9, 5, 2, 7, 6]), array([0]))]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"TEST 3 (expected usage of Protocol)\"\"\"\n",
+    "def cv_func(cv: CROSS_VAL_FN, **kwargs):\n",
+    "    cv(**kwargs)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}