Change paper link

Author: greydanus

README.md

@@ -1,7 +1,7 @@
 The MNIST-1D Dataset
 =======
 
-[Blog post](https://greydanus.github.io/2020/12/01/scaling-down/) | [Paper](https://arxiv.org/abs/2011.14439) | [GitHub](https://github.com/greydanus/mnist1d)
+[Blog post](https://greydanus.github.io/2020/12/01/scaling-down/) | [Paper](https://arxiv.org/abs/2011.14439v4) | [GitHub](https://github.com/greydanus/mnist1d)
 
 
 Most machine learning models get around the same ~99% test accuracy on MNIST. The dataset in this repo, MNIST-1D, is 20x smaller and does a better job of separating between models with/without nonlinearity and models with/without spatial inductive biases.

notebooks/mnist1d-pip.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "id": "733c5564",
    "metadata": {
     "scrolled": true
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 22,
    "id": "87fa18b4-7d57-46e5-aa42-694ac83ef4e6",
    "metadata": {},
    "outputs": [
@@ -24,18 +24,42 @@
        "((4000, 40), (4000,), (40,))"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "from mnist1d.data import make_dataset, get_dataset_args\n",
     "\n",
-    "defaults = get_dataset_args()\n",
-    "data = make_dataset(defaults)\n",
+    "default_args = get_dataset_args()\n",
+    "data = make_dataset(default_args)\n",
+    "x,y,t = data['x'], data['y'], data['t']\n",
+    "x.shape, y.shape, t.shape\n",
+    "# >>> ((4000, 40), (4000,), (40,))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "dae1e6ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((8000, 40), (8000,), (40,))"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "default_args.num_samples = 10000\n",
+    "data = make_dataset(default_args)\n",
     "x,y,t = data['x'], data['y'], data['t']\n",
-    "\n",
     "x.shape, y.shape, t.shape"
    ]
   },