Avoid setting test_iter.epoch manually (#82)

chainer-community · Mar 7, 2020 · 7e8a134 · 7e8a134
1 parent 8536845
commit 7e8a134
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Showing 2 changed files with 6 additions and 16 deletions.
diff --git a/hands_on_en/chainer/begginers_hands_on/01_Write_the_training_loop.ipynb b/hands_on_en/chainer/begginers_hands_on/01_Write_the_training_loop.ipynb
@@ -583,7 +583,7 @@
         "\n",
         "        test_losses = []\n",
         "        test_accuracies = []\n",
-        "        while True:\n",
+        "        for test_batch in test_iter:\n",
         "            test_batch = test_iter.next()\n",
         "            image_test, target_test = concat_examples(test_batch, gpu_id)\n",
         "\n",
@@ -598,13 +598,8 @@
         "            accuracy = F.accuracy(prediction_test, target_test)\n",
         "            accuracy.to_cpu()\n",
         "            test_accuracies.append(accuracy.data)\n",
-        "            \n",
-        "            if test_iter.is_new_epoch:\n",
-        "                test_iter.epoch = 0\n",
-        "                test_iter.current_position = 0\n",
-        "                test_iter.is_new_epoch = False\n",
-        "                test_iter._pushed_position = None\n",
-        "                break\n",
+        "\n",
+        "        test_iter.reset()\n",
         "\n",
         "        print('val_loss:{:.04f} val_accuracy:{:.04f}'.format(\n",
         "            np.mean(test_losses), np.mean(test_accuracies)))"

diff --git a/hands_on_ja/chainer/begginers_hands_on/11_Write_the_training_loop.ipynb b/hands_on_ja/chainer/begginers_hands_on/11_Write_the_training_loop.ipynb
@@ -547,7 +547,7 @@
         "\n",
         "        test_losses = []\n",
         "        test_accuracies = []\n",
-        "        while True:\n",
+        "        for test_batch in test_iter:\n",
         "            test_batch = test_iter.next()\n",
         "            x_test, t_test = concat_examples(test_batch, gpu_id)\n",
         "\n",
@@ -562,13 +562,8 @@
         "            accuracy = F.accuracy(y_test, t_test)\n",
         "            accuracy.to_cpu()\n",
         "            test_accuracies.append(accuracy.data)\n",
-        "            \n",
-        "            if test_iter.is_new_epoch:\n",
-        "                test_iter.epoch = 0\n",
-        "                test_iter.current_position = 0\n",
-        "                test_iter.is_new_epoch = False\n",
-        "                test_iter._pushed_position = None\n",
-        "                break\n",
+        "\n",
+        "        test_iter.reset()\n",
         "\n",
         "        print('val_loss:{:.04f} val_accuracy:{:.04f}'.format(\n",
         "            np.mean(test_losses), np.mean(test_accuracies)))"