From 6aa007f4c5f5fd7f6885cfe5536ee62eadfbc765 Mon Sep 17 00:00:00 2001 From: liutuo Date: Tue, 3 Jul 2018 19:37:08 +0800 Subject: [PATCH] update basic usage doc --- docs/user_guide/basic_usage.rst | 29 +++++++++++++++-------------- 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/docs/user_guide/basic_usage.rst b/docs/user_guide/basic_usage.rst index b90909dc..e90ef29c 100644 --- a/docs/user_guide/basic_usage.rst +++ b/docs/user_guide/basic_usage.rst @@ -5,7 +5,7 @@ Basic usage Build and run an example model -------------------------------- -Make sure the environment has been set up correctly already.(refer to `installation`) +Make sure the environment has been set up correctly already (refer to `Installation`). Pull the mace model zoo project. @@ -14,7 +14,7 @@ Pull the mace model zoo project. git clone https://github.com/XiaoMi/mace-models.git Here we use the provided mobilenet-v2 model in mace model zoo as an example. -Plug an android phone into your pc and enable Developer Mode of the phone. +Plug an android device into your pc and enable Developer Mode for the device. .. code:: sh @@ -32,7 +32,7 @@ Validate and benchmark the model. .. note:: - 1. If you want to build and run the model on pc, just use the mobilenet-v2-host.yml file instead. + If you want to build and run the model on pc, just use the mobilenet-v2-host.yml file instead for ``--config``. Build your own model @@ -48,11 +48,11 @@ Mace now supports models from tensorflow and caffe. Prepare your tensorflow model.pb file. Use `Graph Transform Tool `__ - to optimize you model for inference. + to optimize your model for inference. This tool will improve the efficiency of inference by making several optimizations like operations - folding, redundant node removal etc. We strongly recommend to use it before building. + folding, redundant node removal etc. We strongly recommend MACE users to use it before building. - The following command shows how to use it for CPU/GPU, + The following command shows how to use the graph transform tool for CPU/GPU, .. code:: bash @@ -75,7 +75,7 @@ Mace now supports models from tensorflow and caffe. - Caffe MACE converter only supports Caffe 1.0+, you need to upgrade - your models with Caffe built-in tool if necessary, + your model by using the Caffe built-in tool if your model is from lower version caffe. .. code:: bash @@ -102,7 +102,7 @@ Modify one of them for your own case. .. literalinclude:: models/demo_app_models_caffe.yml :language: yaml -More details about model deployment file, refer to `advanced_usage`. +More details about model deployment file, refer to `Advanced_usage`. ====================================== @@ -110,9 +110,9 @@ More details about model deployment file, refer to `advanced_usage`. ====================================== MACE provides a python tool (``tools/converter.py``) for -model conversion, compiling, test run, benchmark and correctness validation. +model conversion, compiling, testing, benchmark and validation. -MACE can build either static or shared link library (which is +MACE can build either static or shared library (which is specified by ``linkshared`` in YAML model deployment file). **Commands** @@ -151,8 +151,8 @@ specified by ``linkshared`` in YAML model deployment file). .. warning:: - 1. Plug an android phone into your pc and enable Developer Mode before building. - 2. Please ``build`` your model before ``run`` or ``benchmark`` it. + 1. Plug an android device into your pc and enable Developer Mode before building. + 2. If you want to build the model for pc, set ``target_abis: [host]`` and ``runtime: cpu`` in your deployment YAML file. ============================================ @@ -160,10 +160,10 @@ specified by ``linkshared`` in YAML model deployment file). ============================================ ``build`` command will generate the static/shared library, model files and -header files. All of these files have been packaged into +header files. All of these generated files will be packaged into ``path/to/mace/build/${library_name}/libmace_${library_name}.tar.gz``. -``${library_name}`` is the name you defined in the first line of your demployment yaml file. +``${library_name}`` is the name you defined in the first line of your deployment YAML file. - The generated ``static`` library files are organized as follows, @@ -233,6 +233,7 @@ header files. All of these files have been packaged into Unpack the generated libmace_${library_name}.tar.gz file and copy all of the uncompressed files into your project. + Please refer to \ ``mace/examples/example.cc``\ for full usage. The following lists the key steps. .. code:: cpp -- GitLab