From d041e045ee6f820f48ceca18acbc430b3b298dc9 Mon Sep 17 00:00:00 2001
From: ShusenTang <tangshusen@pku.edu.cn>
Date: Wed, 16 Oct 2019 15:14:27 +0900
Subject: [PATCH] fix bug: issue #29 #30

---
 code/chapter05_CNN/5.5_lenet.ipynb | 10 ++++++----
 code/d2lzh_pytorch/utils.py        |  2 +-
 docs/chapter05_CNN/5.5_lenet.md    |  6 ++++--
 3 files changed, 11 insertions(+), 7 deletions(-)

diff --git a/code/chapter05_CNN/5.5_lenet.ipynb b/code/chapter05_CNN/5.5_lenet.ipynb
index 6b837de..bc79777 100644
--- a/code/chapter05_CNN/5.5_lenet.ipynb
+++ b/code/chapter05_CNN/5.5_lenet.ipynb
@@ -159,8 +159,10 @@
    "outputs": [],
    "source": [
     "# 本函数已保存在d2lzh_pytorch包中方便以后使用。该函数将被逐步改进：它的完整实现将在“图像增广”一节中描述\n",
-    "def evaluate_accuracy(data_iter, net):\n",
-    "    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
+    "def evaluate_accuracy(data_iter, net, device=None):\n",
+    "    if device is None and isinstance(net, torch.nn.Module):\n",
+    "        # 如果没指定device就使用net的device\n",
+    "        device = list(net.parameters())[0].device\n",
     "    acc_sum, n = 0.0, 0\n",
     "    with torch.no_grad():\n",
     "        for X, y in data_iter:\n",
@@ -253,7 +255,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -267,7 +269,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.7.3"
   },
   "varInspector": {
    "cols": {
diff --git a/code/d2lzh_pytorch/utils.py b/code/d2lzh_pytorch/utils.py
index 7bcfdc6..0171e42 100644
--- a/code/d2lzh_pytorch/utils.py
+++ b/code/d2lzh_pytorch/utils.py
@@ -205,7 +205,7 @@ def corr2d(X, K):
 
 # ############################ 5.5 #########################
 def evaluate_accuracy(data_iter, net, device=None):
-    if device is None:
+    if device is None and isinstance(net, torch.nn.Module):
         # 如果没指定device就使用net的device
         device = list(net.parameters())[0].device 
     acc_sum, n = 0.0, 0
diff --git a/docs/chapter05_CNN/5.5_lenet.md b/docs/chapter05_CNN/5.5_lenet.md
index b1a1cd2..1341ae0 100644
--- a/docs/chapter05_CNN/5.5_lenet.md
+++ b/docs/chapter05_CNN/5.5_lenet.md
@@ -102,8 +102,10 @@ train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size=batch_size)
 
 ``` python
 # 本函数已保存在d2lzh_pytorch包中方便以后使用。该函数将被逐步改进。
-def evaluate_accuracy(data_iter, net, 
-        device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')):
+def evaluate_accuracy(data_iter, net, device=None):
+    if device is None and isinstance(net, torch.nn.Module):
+        # 如果没指定device就使用net的device
+        device = list(net.parameters())[0].device
     acc_sum, n = 0.0, 0
     with torch.no_grad():
         for X, y in data_iter:
-- 
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