diff options
Diffstat (limited to 'docs/03_scripts.dox')
| -rw-r--r-- | docs/03_scripts.dox | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/docs/03_scripts.dox b/docs/03_scripts.dox index 5601428ac2..eede8b5d1c 100644 --- a/docs/03_scripts.dox +++ b/docs/03_scripts.dox @@ -8,7 +8,7 @@ One can find caffe <a href="https://github.com/BVLC/caffe/wiki/Model-Zoo">pre-trained models</a> on caffe's official github repository. -The caffe_data_extractor.py provided in the @ref scripts folder is an example script that shows how to +The caffe_data_extractor.py provided in the scripts folder is an example script that shows how to extract the parameter values from a trained model. @note complex networks might require altering the script to properly work. @@ -35,7 +35,7 @@ The script has been tested under Python2.7. If the script runs successfully, it prints the names and shapes of each layer onto the standard output and generates *.npy files containing the weights and biases of each layer. -The @ref arm_compute::utils::load_trained_data shows how one could load +The arm_compute::utils::load_trained_data shows how one could load the weights and biases into tensor from the .npy file by the help of Accessor. @section tensorflow_data_extractor Extract data from pre-trained tensorflow model @@ -87,6 +87,6 @@ The script has been tested with Tensorflow 1.2, 1.3 on Python 2.7.6 and Python 3 If the script runs successfully, it prints the names and shapes of each parameter onto the standard output and generates *.npy files containing the weights and biases of each layer. -The @ref arm_compute::utils::load_trained_data shows how one could load +The arm_compute::utils::load_trained_data shows how one could load the weights and biases into tensor from the .npy file by the help of Accessor. */ |