From 5ba3c92bdac22220ae25b585684b28c1089889cc Mon Sep 17 00:00:00 2001 From: hakuryuu96 Date: Tue, 7 Nov 2023 14:05:59 +0000 Subject: [PATCH 1/2] Changed key for SegKDLoss, added + sign to instructions for overriding dataset_params --- src/super_gradients/recipes/cityscapes_kd_base.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/super_gradients/recipes/cityscapes_kd_base.yaml b/src/super_gradients/recipes/cityscapes_kd_base.yaml index 40d0d6e2b4..b7a2c17721 100644 --- a/src/super_gradients/recipes/cityscapes_kd_base.yaml +++ b/src/super_gradients/recipes/cityscapes_kd_base.yaml @@ -1,7 +1,7 @@ # Distillation for semantic segmentation on Cityscapes dataset. # # Instructions: -# 0. Make sure that the data is stored in dataset_params.dataset_dir or add "dataset_params.data_dir=" at the end of the command below (feel free to check ReadMe) +# 0. Make sure that the data is stored in dataset_params.dataset_dir or add "+dataset_params.data_dir=" at the end of the command below (feel free to check ReadMe) # 1. Move to the project root (where you will find the ReadMe and src folder) # 2. Run the command: # DDRNet23: python -m super_gradients.train_from_kd_recipe --config-name=cityscapes_kd_base student_architecture=ddrnet_23 @@ -55,7 +55,7 @@ training_hyperparams: weights: [ 1. ] kd_loss_weights: [1., 6.] - KDLogitsLoss: + kd_loss: _target_: super_gradients.training.losses.cwd_loss.ChannelWiseKnowledgeDistillationLoss temperature: 3. normalization_mode: channel_wise From 2a1a18883ee7933e6262e927e8e1c4b03681daf5 Mon Sep 17 00:00:00 2001 From: hakuryuu96 Date: Thu, 9 Nov 2023 16:43:01 +0000 Subject: [PATCH 2/2] Updated instructions for cityscapes_kd_base --- src/super_gradients/recipes/cityscapes_kd_base.yaml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/super_gradients/recipes/cityscapes_kd_base.yaml b/src/super_gradients/recipes/cityscapes_kd_base.yaml index b7a2c17721..b6592f5948 100644 --- a/src/super_gradients/recipes/cityscapes_kd_base.yaml +++ b/src/super_gradients/recipes/cityscapes_kd_base.yaml @@ -1,7 +1,9 @@ # Distillation for semantic segmentation on Cityscapes dataset. # # Instructions: -# 0. Make sure that the data is stored in dataset_params.dataset_dir or add "+dataset_params.data_dir=" at the end of the command below (feel free to check ReadMe) +# 0. Make sure that the data is stored in dataset_params.[train/val]_dataset_params.root_dir or +# add "dataset_params.[train/val]_dataset_params.root_dir=" at the end of the +# command below (feel free to check ReadMe) # 1. Move to the project root (where you will find the ReadMe and src folder) # 2. Run the command: # DDRNet23: python -m super_gradients.train_from_kd_recipe --config-name=cityscapes_kd_base student_architecture=ddrnet_23