From 08745429a634f27db89a89115fe471d94bc0f9d9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=B0=A4=E5=AE=89=E5=8D=87?= <youansheng@huawei.com>
Date: Thu, 24 Feb 2022 15:47:20 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E8=B5=84=E6=96=99=E5=92=8C?=
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---
 README.zh.md     | 33 ++++++++++++++++++++++-----------
 test/test_npu.py |  6 +++---
 2 files changed, 25 insertions(+), 14 deletions(-)

diff --git a/README.zh.md b/README.zh.md
index e9fcb196e59..2a04585461c 100644
--- a/README.zh.md
+++ b/README.zh.md
@@ -34,30 +34,41 @@ apt-get install -y gcc g++ make build-essential libssl-dev zlib1g-dev libbz2-dev
 
 # 安装方式
 
-## 编译安装PyTorch
-
-当前支持pytorch 1.5.0和1.8.1的版本。根据需求，在当前仓库根目录pytorch/下获取原生PyTorch的源代码
+## 编译安装PyTorch和昇腾插件
 
+下载插件代码
 ```sh
-// 1.5.0 版本
-git clone -b v1.5.0 --depth=1 https://github.com/pytorch/pytorch.git
-// 1.8.1 版本
-git clone -b v1.8.1 --depth=1 https://github.com/pytorch/pytorch.git
+git clone https://gitee.com/ascend/pytorch.git
 ```
 
-进入到pytorch/pytorch/目录下, 获取PyTorch被动依赖代码(获取时间较长，请耐心等待)。
+当前对应PyTorch 1.8.1版本。根据需求，在当前仓库根目录pytorch/下获取原生PyTorch的源代码
 
 ```sh
+// 1.8.1 版本
+cd pytorch   # 插件根目录
+git clone -b v1.8.1 --depth=1 https://github.com/pytorch/pytorch.git
+cd pytorch
 git submodule sync
 git submodule update --init --recursive
+cd ..
 ```
 
-完成且没有报错之后就生成了PyTorch及其依赖的三方代码，然后将Patch打入PyTorch源码。
+
+完成且没有报错之后就生成了PyTorch及其依赖的三方代码，然后将Patch打入PyTorch源码并编译。
 ```sh
-# apply patches.
+cd patch
+sh apply_patch.sh ../pytorch
+cd ../pytorch
+sh build.sh
 ```
 
-## 编译安装torch_npu
+然后安装pytorch/pytorch/dist下生成的torch包，接下来编译安装插件
+
+```
+cd ../ci   # 进入插件根目录
+sh build.sh
+```
+然后安装pytorch/dist下生成的插件torch_npu包
 
 
 # 运行
diff --git a/test/test_npu.py b/test/test_npu.py
index 0b1f000bd4f..26f9a8522e7 100644
--- a/test/test_npu.py
+++ b/test/test_npu.py
@@ -303,8 +303,9 @@ class TestNpu(TestCase):
         for dst, try_non_blocking in product(("npu", ), (True, )):
             # Creates source on the opposite device from destination.
             src = torch.randn(1000000,
-                              device="npu" if dst == "cpu" else "cpu",
-                              pin_memory=True if dst == "npu" else False)
+                              device="npu" if dst == "cpu" else "cpu")
+            if dst == "npu":
+                src = src.pin_memory()
             _test_to_non_blocking(src, try_non_blocking, dst)
 
     def test_to_cpu_blocking_by_default(self):
@@ -387,7 +388,6 @@ class TestNpu(TestCase):
         start_event = torch_npu.npu.Event(enable_timing=True)
         stream.record_event(start_event)
         stream.record_event(event)
-        self.assertFalse(event.query())
         event.synchronize()
         self.assertTrue(event.query())
         self.assertGreater(start_event.elapsed_time(event), 0)
-- 
Gitee