From 6d02b5a4e2a7eae14361cde9599bbf4ccde2cd37 Mon Sep 17 00:00:00 2001 From: Fabian Isensee Date: Tue, 12 Apr 2022 11:58:36 +0200 Subject: [PATCH] typos --- documentation/common_questions.md | 2 +- .../experiment_planner_baseline_3DUNet_v21_noResampling.py | 4 ++-- .../experiment_planning/experiment_planner_baseline_2DUNet.py | 2 +- .../experiment_planning/experiment_planner_baseline_3DUNet.py | 2 +- nnunet/training/network_training/nnUNetTrainerV2.py | 2 +- .../nnUNetTrainerV2_softDeepSupervision.py | 2 +- tests/test_steps_for_sliding_window_prediction.py | 2 +- 7 files changed, 8 insertions(+), 8 deletions(-) diff --git a/documentation/common_questions.md b/documentation/common_questions.md index 23d9ee6ca..45d963098 100644 --- a/documentation/common_questions.md +++ b/documentation/common_questions.md @@ -149,7 +149,7 @@ iterations each (250000 iterations). The training time thus scales approximately know what you are doing! Again, training times will be increased if you do this! 3) is a better way of increasing the patch size. -3) Run `nnUNet_plan_and_preprocess` with a larger GPU memory budget. This will make nnU-Net plan for larger batch sizes +3) Run `nnUNet_plan_and_preprocess` with a larger GPU memory budget. This will make nnU-Net plan for larger patch sizes during experiment planning. Doing this can change the patch size, network topology, the batch size as well as the presence of the U-Net cascade. To run with a different memory budget, you need to specify a different experiment planner, for example `nnUNet_plan_and_preprocess -t TASK_ID -pl2d None -pl3d ExperimentPlanner3D_v21_32GB` (note that `-pl2d None` will diff --git a/nnunet/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_v21_noResampling.py b/nnunet/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_v21_noResampling.py index 2e3d4fe8d..3810cc780 100644 --- a/nnunet/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_v21_noResampling.py +++ b/nnunet/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_v21_noResampling.py @@ -34,7 +34,7 @@ def plan_experiment(self): :return: """ use_nonzero_mask_for_normalization = self.determine_whether_to_use_mask_for_norm() - print("Are we using the nonzero mask for normalizaion?", use_nonzero_mask_for_normalization) + print("Are we using the nonzero mask for normalization?", use_nonzero_mask_for_normalization) spacings = self.dataset_properties['all_spacings'] sizes = self.dataset_properties['all_sizes'] @@ -132,7 +132,7 @@ def plan_experiment(self): :return: """ use_nonzero_mask_for_normalization = self.determine_whether_to_use_mask_for_norm() - print("Are we using the nonzero mask for normalizaion?", use_nonzero_mask_for_normalization) + print("Are we using the nonzero mask for normalization?", use_nonzero_mask_for_normalization) spacings = self.dataset_properties['all_spacings'] sizes = self.dataset_properties['all_sizes'] diff --git a/nnunet/experiment_planning/experiment_planner_baseline_2DUNet.py b/nnunet/experiment_planning/experiment_planner_baseline_2DUNet.py index 4a6882b83..3eaa05208 100644 --- a/nnunet/experiment_planning/experiment_planner_baseline_2DUNet.py +++ b/nnunet/experiment_planning/experiment_planner_baseline_2DUNet.py @@ -89,7 +89,7 @@ def get_properties_for_stage(self, current_spacing, original_spacing, original_s def plan_experiment(self): use_nonzero_mask_for_normalization = self.determine_whether_to_use_mask_for_norm() - print("Are we using the nonzero mask for normalizaion?", use_nonzero_mask_for_normalization) + print("Are we using the nonzero mask for normalization?", use_nonzero_mask_for_normalization) spacings = self.dataset_properties['all_spacings'] sizes = self.dataset_properties['all_sizes'] diff --git a/nnunet/experiment_planning/experiment_planner_baseline_3DUNet.py b/nnunet/experiment_planning/experiment_planner_baseline_3DUNet.py index 694056535..1a8b65dc3 100644 --- a/nnunet/experiment_planning/experiment_planner_baseline_3DUNet.py +++ b/nnunet/experiment_planning/experiment_planner_baseline_3DUNet.py @@ -246,7 +246,7 @@ def get_properties_for_stage(self, current_spacing, original_spacing, original_s def plan_experiment(self): use_nonzero_mask_for_normalization = self.determine_whether_to_use_mask_for_norm() - print("Are we using the nonzero mask for normalizaion?", use_nonzero_mask_for_normalization) + print("Are we using the nonzero mask for normalization?", use_nonzero_mask_for_normalization) spacings = self.dataset_properties['all_spacings'] sizes = self.dataset_properties['all_sizes'] diff --git a/nnunet/training/network_training/nnUNetTrainerV2.py b/nnunet/training/network_training/nnUNetTrainerV2.py index eec575726..e5e77e265 100644 --- a/nnunet/training/network_training/nnUNetTrainerV2.py +++ b/nnunet/training/network_training/nnUNetTrainerV2.py @@ -170,7 +170,7 @@ def initialize_optimizer_and_scheduler(self): def run_online_evaluation(self, output, target): """ due to deep supervision the return value and the reference are now lists of tensors. We only need the full - resolution output because this is what we are interested in the end. The others are ignored + resolution output because this is what we are interested in in the end. The others are ignored :param output: :param target: :return: diff --git a/nnunet/training/network_training/nnUNet_variants/architectural_variants/nnUNetTrainerV2_softDeepSupervision.py b/nnunet/training/network_training/nnUNet_variants/architectural_variants/nnUNetTrainerV2_softDeepSupervision.py index 6060213ca..62f974a0e 100644 --- a/nnunet/training/network_training/nnUNet_variants/architectural_variants/nnUNetTrainerV2_softDeepSupervision.py +++ b/nnunet/training/network_training/nnUNet_variants/architectural_variants/nnUNetTrainerV2_softDeepSupervision.py @@ -116,7 +116,7 @@ def initialize(self, training=True, force_load_plans=False): def run_online_evaluation(self, output, target): """ due to deep supervision the return value and the reference are now lists of tensors. We only need the full - resolution output because this is what we are interested in the end. The others are ignored + resolution output because this is what we are interested in in the end. The others are ignored :param output: :param target: :return: diff --git a/tests/test_steps_for_sliding_window_prediction.py b/tests/test_steps_for_sliding_window_prediction.py index 33ab8b532..08f8faf48 100644 --- a/tests/test_steps_for_sliding_window_prediction.py +++ b/tests/test_steps_for_sliding_window_prediction.py @@ -28,7 +28,7 @@ def _verify_steps(self, steps, patch_size, image_size, step_size): str(patch_size), step_size) target_step_sizes_in_voxels = [i * step_size for i in patch_size] - # this code is copied from the current implementation. Not ideal, but I don't know hoe else to the the + # this code is copied from the current implementation. Not ideal, but I don't know how else to compute the # expected num_steps num_steps = [int(np.ceil((i - k) / j)) + 1 for i, j, k in zip(image_size, target_step_sizes_in_voxels, patch_size)]