From eb5ea47d9cb8cee98cdf2d5b37c027b6a1206ef7 Mon Sep 17 00:00:00 2001 From: Jinhee Lee <39753595+lee-jinhee@users.noreply.github.com> Date: Tue, 1 Nov 2022 20:14:36 +0900 Subject: [PATCH] Update customize_datasets.md (#2249) --- docs/en/tutorials/customize_datasets.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/en/tutorials/customize_datasets.md b/docs/en/tutorials/customize_datasets.md index 666466fe3..31df5bb06 100644 --- a/docs/en/tutorials/customize_datasets.md +++ b/docs/en/tutorials/customize_datasets.md @@ -34,7 +34,7 @@ data = dict( using [`build and registry`](https://github.com/open-mmlab/mmcv/blob/master/docs/en/understand_mmcv/registry.md) mechanism. - `samples_per_gpu`: How many samples per batch and per gpu to load during model training, and the `batch_size` of training is equal to `samples_per_gpu` times gpu number, e.g. when using 8 gpus for distributed data parallel training and `samples_per_gpu=4`, the `batch_size` is `8*4=32`. - If you would like to define `batch_size` for testing and validation, please use `test_dataloaser` and + If you would like to define `batch_size` for testing and validation, please use `test_dataloader` and `val_dataloader` with mmseg >=0.24.1. - `workers_per_gpu`: How many subprocesses per gpu to use for data loading. `0` means that the data will be loaded in the main process. @@ -43,7 +43,7 @@ data = dict( **Note:** before v0.24.1, except `train`, `val` `test`, `samples_per_gpu` and `workers_per_gpu`, the other keys in `data` must be the input keyword arguments for `dataloader` in pytorch, and the dataloaders used for model training, validation and testing have the same input arguments. -In v0.24.1, mmseg supports to use `train_dataloader`, `test_dataloaser` and `val_dataloader` to specify different keyword arguments, and still supports the overall arguments definition but the specific dataloader setting has a higher priority. +In v0.24.1, mmseg supports to use `train_dataloader`, `test_dataloader` and `val_dataloader` to specify different keyword arguments, and still supports the overall arguments definition but the specific dataloader setting has a higher priority. Here is an example for specific dataloader: