From 6a5627a1de8d74f0dd66b63cf31d26a8c94e107d Mon Sep 17 00:00:00 2001 From: Anthony Barbier Date: Tue, 26 Sep 2017 14:42:02 +0100 Subject: COMPMID-417 Update changelog before release Change-Id: Ia37515fb8238a03699d75751b877d5aaff5ba1a0 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/89174 Reviewed-by: Moritz Pflanzer Tested-by: Anthony Barbier --- docs/03_scripts.dox | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'docs/03_scripts.dox') diff --git a/docs/03_scripts.dox b/docs/03_scripts.dox index 2fd3907978..5601428ac2 100644 --- a/docs/03_scripts.dox +++ b/docs/03_scripts.dox @@ -13,7 +13,7 @@ extract the parameter values from a trained model. @note complex networks might require altering the script to properly work. -@subsection how_to How to use the script +@subsection caffe_how_to How to use the script Install caffe following caffe's document. Make sure the pycaffe has been added into the PYTHONPATH. @@ -30,7 +30,7 @@ For example, to extract the data from pre-trained caffe Alex model to binary fil The script has been tested under Python2.7. -@subsection result What is the expected output from the script +@subsection caffe_result What is the expected output from the script 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. @@ -60,7 +60,7 @@ when dealing with binary files with version < 0.11, pass the whole file name {mo specified otherwise by the user. Thus should a user alter this default behavior and/or want to extract parameters from other collections, tf.GraphKeys.TRAINABLE_VARIABLES should be replaced accordingly. -@subsection how_to How to use the script +@subsection tensorflow_how_to How to use the script Install tensorflow and numpy. @@ -82,7 +82,7 @@ Or for binary checkpoint files before Tensorflow 0.11: The script has been tested with Tensorflow 1.2, 1.3 on Python 2.7.6 and Python 3.4.3. -@subsection result What is the expected output from the script +@subsection tensorflow_result What is the expected output from the script 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. -- cgit v1.2.1