From 054bfce766b0619fd58c376992cf4d017b31df8e Mon Sep 17 00:00:00 2001 From: Vikash Gupta Date: Fri, 24 Jul 2026 07:12:33 +0000 Subject: [PATCH] fix typos in docs: lazy_resampling, modules, whatsnew_1_5 Signed-off-by: Vikash Gupta --- docs/source/lazy_resampling.rst | 4 ++-- docs/source/modules.md | 2 +- docs/source/whatsnew_1_5.md | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/source/lazy_resampling.rst b/docs/source/lazy_resampling.rst index 7b809965f33..9776cd94385 100644 --- a/docs/source/lazy_resampling.rst +++ b/docs/source/lazy_resampling.rst @@ -253,7 +253,7 @@ so the user must set lazy=True on the transforms that they still wish to execute .. figure:: ../images/lazy_resampling_none_example.svg - Figure shwoing the effect of using ``lazy=False`` when ``Compose`` is being executed with ``lazy=None``. Note that + Figure showing the effect of using ``lazy=False`` when ``Compose`` is being executed with ``lazy=None``. Note that the additional resamples that occur due to ``RandRotate90d`` being executed in a non-lazy fashion. @@ -270,4 +270,4 @@ the following transform is a lazy transform, or is configured to execute lazily. .. figure:: ../images/lazy_resampling_apply_pending_example.svg Figure showing the use of :class:`ApplyPendingd` to cause - resampling to occur in the midele of a chain of lazy transforms. + resampling to occur in the middle of a chain of lazy transforms. diff --git a/docs/source/modules.md b/docs/source/modules.md index b2e95658bf7..a0f24b64a88 100644 --- a/docs/source/modules.md +++ b/docs/source/modules.md @@ -205,7 +205,7 @@ The workflow and some of MONAI event handlers are shown as below [[Workflow exam ### EnsembleEvaluator -A typical ensemble procoess is implemented as a ready-to-use workflow [[Cross validation and model ensemble tutorial]](https://github.com/Project-MONAI/tutorials/blob/main/modules/cross_validation_models_ensemble.ipynb): +A typical ensemble process is implemented as a ready-to-use workflow [[Cross validation and model ensemble tutorial]](https://github.com/Project-MONAI/tutorials/blob/main/modules/cross_validation_models_ensemble.ipynb): 1. Split all the training dataset into K folds. 2. Train K models with every K-1 folds data. 3. Execute inference on the test data with all the K models. diff --git a/docs/source/whatsnew_1_5.md b/docs/source/whatsnew_1_5.md index 8b68d716866..5fd7d779234 100644 --- a/docs/source/whatsnew_1_5.md +++ b/docs/source/whatsnew_1_5.md @@ -3,7 +3,7 @@ - Support numpy 2.x and Pytorch 2.6 - MAISI inference accelerate -- Bundles storage changed to huggingface and correspoinding api updated in core +- Bundles storage changed to huggingface and corresponding api updated in core - Ported remaining generative tutorials and bundles - New tutorials: - [2d_regression/image_restoration.ipynb](https://github.com/Project-MONAI/tutorials/blob/main/2d_regression/image_restoration.ipynb)