diff --git a/doc/running_fasnet.md b/doc/running_fasnet.md
index b080ce729b708360b44a642e1d5f4251798af8d6..5e139b6b4c233eb529cf38f08497904cc410c962 100644
--- a/doc/running_fasnet.md
+++ b/doc/running_fasnet.md
@@ -12,8 +12,8 @@ FASNet accepts RGB images only, hence the preprocesing is done first. This can b
 
 .. code-block:: sh
 	./bin/spoof.py \
-	<PATH_TO_CONFIG>/wmca_grandtest_dbconfig.py \
-	<PATH_TO_CONFIG>/wmca_config_pytorch_extractor.py \
+	wmca-color \
+	fasnet \
 	--execute-only preprocessing \
 	--sub-directory <FASNET_PIPELINE_FOLDER> 
 	--grid idiap 
@@ -34,7 +34,7 @@ Once the config file is defined, training the network can be done with the follo
 .. code-block:: sh
 
     ./bin/train_fasnet.py \                   # script used for FASNET training
-    <PATH_TO_TRAINER_CONFIG>/wmca_FASNet.py \  # configuration file defining the FASNET network, database, and training parameters
+    <PATH_TO_TRAINER_CONFIG>/wmca_faset.py \  # configuration file defining the FASNET network, database, and training parameters
     -vv                                      # set verbosity level
 
 People in Idiap can benefit from GPU cluster, running the training as follows:
@@ -46,7 +46,7 @@ People in Idiap can benefit from GPU cluster, running the training as follows:
     --log-dir <FOLDER_TO_SAVE_THE_RESULTS>/logs/ \ # substitute the path to save the logs to (Idiap only)
     --environment="PYTHONUNBUFFERED=1" -- \        #
     ./bin/train_fasnet.py \                        # script used for FASNET training
-    <PATH_TO_TRAINER_CONFIG>/wmca_FASNet.py \      # configuration file defining the FASNET network, database, and training parameters
+    <PATH_TO_TRAINER_CONFIG>/wmca_fasnet.py \      # configuration file defining the FASNET network, database, and training parameters
     --use-gpu \                                    # enable the GPU mode
     -vv                                            # set verbosity level
 
@@ -57,7 +57,7 @@ For a more detailed documentation of functionality available in the training scr
 
     ./bin/train_fasnet.py --help   # note: remove ./bin/ if buildout is not used
 
-Please inspect the corresponding configuration file, ``wmca_FASNet.py`` for example, for more details on how to define the database, network architecture and training parameters.
+Please inspect the corresponding configuration file, ``wmca_faset.py`` for example, for more details on how to define the database, network architecture and training parameters.
 
 The protocols, and channels used in the experiments can be easily configured in the configuration file.
 
@@ -72,10 +72,10 @@ For **grandtest** protocol this can be done as follows.
 .. code-block:: sh
 
 	./bin/spoof.py \
-	<PATH_TO_DATABASE_CONFIG>/wmca_grandtest_dbconfig.py \
-	<PATH_TO_EXTRACTORS>/wmca_config_pytorch_extractor_v1_FASNet.py \
+	wmca-color \
+	fasnet \
 	--protocol grandtest \
-	--sub-directory <FOLDER_TO_SAVE_MCCNN_RESULTS>  -vv  
+	--sub-directory <FOLDER_TO_SAVE_FASNET_RESULTS>  -vv  
 
 
 
@@ -87,8 +87,8 @@ To evaluate the models run the following command.
 .. code-block:: python
 
 	./bin/scoring.py -df \
-	<PATH_TO_SCORES>/scores-dev -ef \
-	<PATH_TO_SCORES>/scores-eval
+	<FOLDER_TO_SAVE_FASNET_RESULTS>/grandtest/scores/scores-dev -ef \
+	<FOLDER_TO_SAVE_FASNET_RESULTS>/grandtest/scores/scores-eval
 
 
 
diff --git a/doc/running_mccn.md b/doc/running_mccn.md
index ad92cee01f0a3e2719d077bf07bada17fba82dd7..47ee3473de3c24bc789c5a5420e4ac3ce66410d4 100644
--- a/doc/running_mccn.md
+++ b/doc/running_mccn.md
@@ -100,8 +100,8 @@ To evaluate the models run the following command.
 .. code-block:: python
 
 	./bin/scoring.py -df \
-	<PATH_TO_SCORES>/scores-dev -ef \
-	<PATH_TO_SCORES>/scores-eval
+	<FOLDER_TO_SAVE_MCCNN_RESULTS>/grandtest/scores/scores-dev -ef \
+	<FOLDER_TO_SAVE_MCCNN_RESULTS>/grandtest/scores/scores-eval
 
 Using pretrained models
 =======================
diff --git a/setup.py b/setup.py
index 0f0f33ed519eb94c7fe37a51be653b718d422b89..9a595fba0a3e6377c54c4e4f5b2f3df91c832c90 100644
--- a/setup.py
+++ b/setup.py
@@ -109,7 +109,7 @@ setup(
         'lbp-lr-infrared = bob.paper.mccnn.tifs2018.config.lbp_lr_infrared',
         'lbp-lr-thermal= bob.paper.mccnn.tifs2018.config.lbp_lr_thermal',
         'lbp-lr-depth= bob.paper.mccnn.tifs2018.config.lbp_lr_depth',
-        'fastnet = bob.paper.mccnn.tifs2018.config.FASNet_config',
+        'fasnet = bob.paper.mccnn.tifs2018.config.FASNet_config',
         'mccnn = bob.paper.mccnn.tifs2018.config.MCCNN_config',
         'iqm-lr = bob.paper.mccnn.tifs2018.config.iqm_lr',
         'haralick-svm = bob.paper.mccnn.tifs2018.config.haralick_svm',],