README fixes

Signed-off-by: Rajeev Rao <[email protected]>

Author: rajeevsrao

README.md

@@ -87,7 +87,7 @@ NOTE: Along with the TensorRT OSS components, the following source packages will
 	git clone -b master https://github.com/nvidia/TensorRT TensorRT
 	cd TensorRT
 	git submodule update --init --recursive
-	$Env:TRT_RELEASE_PATH = $(Get-Location)
+	$Env:TRT_SOURCE = $(Get-Location)
 	```
 
 2. #### Download the TensorRT binary release.
@@ -147,15 +147,15 @@ NOTE: Along with the TensorRT OSS components, the following source packages will
 	```powershell
 	cd ~\Downloads
 	Expand-Archive .\TensorRT-7.1.3.4.Windows10.x86_64.cuda-11.0.cudnn8.0.zip
-	$Env:TRT_RELEASE_PATH = '$(Get-Location)\TensorRT-7.1.3.4'
+	$Env:TRT_RELEASE = '$(Get-Location)\TensorRT-7.1.3.4'
 	$Env:PATH += 'C:\Program Files (x86)\Microsoft Visual Studio\2017\Professional\MSBuild\15.0\Bin\'
 	```
 
 3. #### Download JetPack toolchain for cross-compilation.[OPTIONAL]
 
     **JetPack example**
 
-    Using the SDK manager, download the host componets of the PDK version or Jetpack specified in the name of the Dockerfile. To do this:
+    Using the SDK manager, download the host components of the PDK version or Jetpack specified in the name of the Dockerfile. To do this:
     1. [**SDK Manager Step 01**] Log into the SDK manager
     2. [**SDK Manager Step 02**] Select the correct platform and Target OS System  (should be corresponding to the name of the Dockerfile you are building (e.g. Jetson AGX Xavier, `Linux Jetpack 4.4`), then click `Continue`
     3. [**SDK Manager Step 03**] Under `Download & Install Options` make note of or change the download folder **and Select Download now. Install later.** then agree to the license terms and click `Continue`
@@ -207,6 +207,7 @@ NOTE: Along with the TensorRT OSS components, the following source packages will
 
 	> NOTE: To run TensorRT/CUDA programs in the build container, install [NVIDIA Docker support](#prerequisites). Docker versions < 19.03 require `nvidia-docker2` and `--runtime=nvidia` flag for docker run commands. On versions >= 19.03, you need the `nvidia-container-toolkit` package and `--gpus all` flag.
 
+
 ## Building The TensorRT OSS Components
 
 * Generate Makefiles and build.
@@ -294,10 +295,10 @@ NOTE: Along with the TensorRT OSS components, the following source packages will
 
 whl files for the TensorRT python API are in the `python` directory of the TensorRT release
 
-*Example* install for python 3.6:
+*Example* install for python3:
 
 ```
-pip install $TRT_RELEASE/python/tensorrt-7.1.3.4-cp36-none-linux_x86_64.whl
+pip3 install $TRT_RELEASE/python/tensorrt-7.1.3.4-cp36-none-linux_x86_64.whl
 ```
 
 ## Useful Resources
@@ -313,5 +314,4 @@ pip install $TRT_RELEASE/python/tensorrt-7.1.3.4-cp36-none-linux_x86_64.whl
 ## Known Issues
 
 #### TensorRT 7.1
-* [demo/BERT](demo/BERT) has a known accuracy regression for Volta GPUs; F1 score dropped (from 90 in TensorRT 7.0) to 85. A fix is underway.
 * See [Release Notes](https://docs.nvidia.com/deeplearning/tensorrt/release-notes/tensorrt-7.html#rel_7-1-3).