From e2b5e871ff10a21f7a62a5cca0b8630edd4ff7d7 Mon Sep 17 00:00:00 2001
From: Muli Yang <31494617+mattmoevil@users.noreply.github.com>
Date: Tue, 19 Feb 2019 17:32:23 +0800
Subject: [PATCH] Update 5_data_parallel_tutorial.ipynb

---
 chapter1/5_data_parallel_tutorial.ipynb | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/chapter1/5_data_parallel_tutorial.ipynb b/chapter1/5_data_parallel_tutorial.ipynb
index 55a763fc..0be5795f 100644
--- a/chapter1/5_data_parallel_tutorial.ipynb
+++ b/chapter1/5_data_parallel_tutorial.ipynb
@@ -14,13 +14,13 @@
    "metadata": {},
    "source": [
     "\n",
-    "数据并行(选读)\n",
+    "数据并行（选读）\n",
     "==========================\n",
-    "**Authors**: `Sung Kim <https://github.com/hunkim>`_ and `Jenny Kang <https://github.com/jennykang>`_\n",
+    "**Authors**: [Sung Kim](https://github.com/hunkim) and [Jenny Kang](https://github.com/jennykang)\n",
     "\n",
-    "在这个教程里,我们将学习如何使用``DataParallel``来使用多GPU. \n",
+    "在这个教程里，我们将学习如何使用 ``DataParallel`` 来使用多GPU。 \n",
     "\n",
-    "PyTorch非常容易的就可以使用多GPU,用如下方式把一个模型放到GPU上\n",
+    "PyTorch非常容易就可以使用多GPU，用如下方式把一个模型放到GPU上：\n",
     "\n",
     "```python\n",
     "\n",
@@ -28,12 +28,12 @@
     "    model.to(device)\n",
     "```\n",
     " GPU:\n",
-    "然后复制所有的张量到GPU上\n",
+    "然后复制所有的张量到GPU上：\n",
     "```python\n",
     "\n",
     "    mytensor = my_tensor.to(device)\n",
     "```\n",
-    "请注意,只调用``my_tensor.to(device)``并没有复制张量到GPU上,而是返回了一个copy。所以你需要把它赋值给一个新的张量并在GPU上使用这个张量。\n",
+    "请注意，只调用``my_tensor.to(device)``并没有复制张量到GPU上，而是返回了一个copy。所以你需要把它赋值给一个新的张量并在GPU上使用这个张量。\n",
     "\n",
     "在多GPU上执行前向和反向传播是自然而然的事。\n",
     "但是PyTorch默认将只是用一个GPU。\n",
@@ -104,7 +104,7 @@
     "虚拟数据集\n",
     "-------------\n",
     "\n",
-    "制作一个虚拟（随机）数据集\n",
+    "制作一个虚拟（随机）数据集，\n",
     "你只需实现 `__getitem__`\n",
     "\n",
     "\n"