Tutorial mnist: improve 1.3 Remove contradictory (#505)

* Tutorial mnist: improve 1.3 Remove contradictory * Tutorial mnist: improve 1.3 data report Co-authored-by: MichaelBroughton <[email protected]>
tensorflow · Mar 19, 2021 · c49f0f1 · c49f0f1
1 parent 52ccd82
commit c49f0f1
Showing 1 changed file with 14 additions and 11 deletions.
diff --git a/docs/tutorials/mnist.ipynb b/docs/tutorials/mnist.ipynb
@@ -382,32 +382,35 @@
       "source": [
         "def remove_contradicting(xs, ys):\n",
         "    mapping = collections.defaultdict(set)\n",
+        "    orig_x = {}\n",
         "    # Determine the set of labels for each unique image:\n",
         "    for x,y in zip(xs,ys):\n",
+        "       orig_x[tuple(x.flatten())] = x\n",
         "       mapping[tuple(x.flatten())].add(y)\n",
         "    \n",
         "    new_x = []\n",
         "    new_y = []\n",
-        "    for x,y in zip(xs, ys):\n",
-        "      labels = mapping[tuple(x.flatten())]\n",
+        "    for flatten_x in mapping:\n",
+        "      x = orig_x[flatten_x]\n",
+        "      labels = mapping[flatten_x]\n",
         "      if len(labels) == 1:\n",
         "          new_x.append(x)\n",
-        "          new_y.append(labels.pop())\n",
+        "          new_y.append(next(iter(labels)))\n",
         "      else:\n",
         "          # Throw out images that match more than one label.\n",
         "          pass\n",
         "    \n",
-        "    num_3 = sum(1 for value in mapping.values() if True in value)\n",
-        "    num_6 = sum(1 for value in mapping.values() if False in value)\n",
-        "    num_both = sum(1 for value in mapping.values() if len(value) == 2)\n",
+        "    num_uniq_3 = sum(1 for value in mapping.values() if len(value) == 1 and True in value)\n",
+        "    num_uniq_6 = sum(1 for value in mapping.values() if len(value) == 1 and False in value)\n",
+        "    num_uniq_both = sum(1 for value in mapping.values() if len(value) == 2)\n",
         "\n",
         "    print(\"Number of unique images:\", len(mapping.values()))\n",
-        "    print(\"Number of 3s: \", num_3)\n",
-        "    print(\"Number of 6s: \", num_6)\n",
-        "    print(\"Number of contradictory images: \", num_both)\n",
+        "    print(\"Number of unique 3s: \", num_uniq_3)\n",
+        "    print(\"Number of unique 6s: \", num_uniq_6)\n",
+        "    print(\"Number of unique contradicting labels (both 3 and 6): \", num_uniq_both)\n",
         "    print()\n",
-        "    print(\"Initial number of examples: \", len(xs))\n",
-        "    print(\"Remaining non-contradictory examples: \", len(new_x))\n",
+        "    print(\"Initial number of images: \", len(xs))\n",
+        "    print(\"Remaining non-contradicting unique images: \", len(new_x))\n",
         "    \n",
         "    return np.array(new_x), np.array(new_y)"
       ]