Update customized workspace create doc (#84)

docs/builder/overview.md

@@ -20,7 +20,7 @@ nn-meter create --tflite-workspace <path/to/place/workspace/>
 nn-meter create --openvino-workspace <path/to/place/workspace/>
 
 # for customized platform
-nn-meter create --customized-workspace <backend-name> <path/to/place/workspace/>
+nn-meter create --customized-workspace <path/to/place/workspace/> --backend <backend-name>
 ```
 
 After running the command, a workspace folder will be created, and a series of configuration file will be placed in `<workspace-path>/configs/`. Users could open `<workspace-path>/configs/*.yaml` and edit the content to change configuration. 

docs/builder/prepare_backend.md

@@ -34,7 +34,9 @@ Follow [Android Guide](https://developer.android.com/studio) to install adb on y
 The easiest way is to directly download Android Studio from [this page](https://developer.android.com/studio). After installing it, you will find adb at path `$HOME/Android/Sdk/platform-tools/`.
 
 #### 2. Get TFLite Benchmark Model
-The `benchmark_model` is a tool provided by [TensorFlow Lite](https://www.tensorflow.org/lite/), which can run a model and output its latency. Because nn-Meter needs to parse the text output of `benchmark_model`, a fixed version is required. For the convenience of users, we have released two modified version of `benchmark_model` based on `tensorflow==2.1` and `tensorflow==2.7`, respectively. Users could download our modified version of `benchmark_model` from [here](https://github.com/microsoft/nn-Meter/releases/tag/v2.0-data).
+The `benchmark_model` is a tool provided by [TensorFlow Lite](https://www.tensorflow.org/lite/), which can run a model and output its latency. Because nn-Meter needs to parse the text output of `benchmark_model`, a fixed version is required. For the convenience of users, we have released two modified version of `benchmark_model` based on `tensorflow==2.1` and `tensorflow==2.7`, respectively. Users could download our complied version of `benchmark_model` from [here](https://github.com/microsoft/nn-Meter/releases/tag/v2.0-data).
+
+NOTE: In our tf21 version, we have not specified to use `Aarch64` for benchmark model compiling, which is an optional argument at that moment, and become a default setting with no need to specify by now. As a result, our benchmark model shows larger profiling latency than newly compiled benchmark tool. Users should apply our `benchmark_model_cpu_v2.1` and `benchmark_model_gpu_v2.1` to reproduce the consistent latency with our paper.
 
 NOTE: On a same hardware, the different versions of `benchmark_model` can result in different inference latency for a same model. We recommend users compile and build the `benchmark_model` for latest version. Users could follow [Official Guidance](https://www.tensorflow.org/lite/performance/measurement) to build benchmark tool with new version `TensorFlow Lite`. Meanwhile, the class of `LatencyParser` may need to be refined. We are working to release the source code of this modified version.
 
@@ -177,7 +179,7 @@ class MyParser(BaseParser): ...
 
 ### Step 1: Create a Package for the Customized Backend
 
-After preparing the backend class, users should also prepare a default config file in yaml format if there is any modifiable configs. This config file will be copied to workspace when running `nn-meter create --customized-workspace`. Users can refer to [the Configuration of TFLite and OpenVINO](#prepare-configuration-file) as a reference. nn-Meter suggests users to gather all code of backend and default config files in a package with a predefined location. The folder should contain all relevant classes, such as `Parser` and `Profiler`. A folder will be treated as a package with a `__init__.py` file added. Here is a demo of folder structure:
+After preparing the backend class, users should also prepare a default config file in yaml format if there is any modifiable configs. This config file will be copied to workspace when running `nn-meter create --customized-workspace <path/to/place/workspace/> --backend <backend-name>`. Users can refer to [the Configuration of TFLite and OpenVINO](#prepare-configuration-file) as a reference. nn-Meter suggests users to gather all code of backend and default config files in a package with a predefined location. The folder should contain all relevant classes, such as `Parser` and `Profiler`. A folder will be treated as a package with a `__init__.py` file added. Here is a demo of folder structure:
 
 ``` text
 ./customized_backend/

examples/nn-meter_builder_examples/test_fusion_rule.ipynb

@@ -34,7 +34,7 @@
     "nn-meter create --openvino-workspace <path/to/place/workspace/>\n",
     "\n",
     "# for customized platform\n",
-    "nn-meter create --customized-workspace <backend-name> <path/to/place/workspace/>\n",
+    "nn-meter create --customized-workspace <path/to/place/workspace/> --backend <backend-name>\n",
     "```\n",
     "\n",
     "After running the command, a workspace folder will be created and two yaml files named `backend_config.yaml`, `ruletest_config.yaml`, and `predictorbuild_config.yaml`, i.e., configuration file for backend, fusion_rule_tester, and predictor builder respectively, will be placed in `<workspace-path>/configs/`. Users could edit the content to change configuration. The config will take effect after the the config file is saved and closed.\n",
@@ -296,11 +296,9 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "e8b26d4e88bfd67f05264bddcd3043513b547d3c68498482ebbb5473451a395f"
-  },
   "kernelspec": {
-   "display_name": "Python 3.6.10 64-bit ('py36-Jiahang': conda)",
+   "display_name": "Python 3.8.13 ('trans')",
+   "language": "python",
    "name": "python3"
   },
   "language_info": {
@@ -313,9 +311,14 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.8.13"
   },
-  "orig_nbformat": 4
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "3e4490da19e6167cb6c7f36fb42a54586b5824152c7fa58ab9eba6ba33512076"
+   }
+  }
  },
  "nbformat": 4,
  "nbformat_minor": 2