From 34711422acf246d59e3eeaa8ccbe70727a651bbb Mon Sep 17 00:00:00 2001 From: "limengzhang.vendor" Date: Sun, 12 Jun 2022 09:10:26 +0000 Subject: [PATCH] [Fix] Fix batch size of val_dataloader to 1. --- configs/_base_/datasets/ade20k.py | 2 +- configs/_base_/datasets/ade20k_640x640.py | 2 +- configs/_base_/datasets/chase_db1.py | 2 +- configs/_base_/datasets/cityscapes.py | 2 +- configs/_base_/datasets/coco-stuff10k.py | 2 +- configs/_base_/datasets/coco-stuff164k.py | 2 +- configs/_base_/datasets/drive.py | 2 +- configs/_base_/datasets/hrf.py | 2 +- configs/_base_/datasets/isaid.py | 2 +- configs/_base_/datasets/loveda.py | 2 +- configs/_base_/datasets/pascal_context.py | 2 +- configs/_base_/datasets/pascal_context_59.py | 2 +- configs/_base_/datasets/pascal_voc12.py | 2 +- configs/_base_/datasets/potsdam.py | 2 +- configs/_base_/datasets/stare.py | 2 +- configs/_base_/datasets/vaihingen.py | 2 +- configs/beit/upernet_beit-base_640x640_160k_ade20k_ms.py | 2 +- configs/beit/upernet_beit-base_8x2_640x640_160k_ade20k.py | 2 +- ...senetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py | 2 +- .../bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes.py | 2 +- ...isenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py | 2 +- ...isenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py | 2 +- ...isenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py | 2 +- .../bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes.py | 2 +- ...isenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py | 2 +- .../bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py | 2 +- .../bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py | 2 +- .../bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py | 2 +- configs/cgnet/cgnet_512x1024_60k_cityscapes.py | 2 +- configs/cgnet/cgnet_680x680_60k_cityscapes.py | 2 +- .../upernet_convnext_base_fp16_512x512_160k_ade20k.py | 2 +- .../upernet_convnext_base_fp16_640x640_160k_ade20k.py | 2 +- .../upernet_convnext_large_fp16_640x640_160k_ade20k.py | 2 +- .../upernet_convnext_small_fp16_512x512_160k_ade20k.py | 2 +- .../upernet_convnext_tiny_fp16_512x512_160k_ade20k.py | 2 +- .../upernet_convnext_xlarge_fp16_640x640_160k_ade20k.py | 2 +- configs/dpt/dpt_vit-b16_512x512_160k_ade20k.py | 2 +- configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py | 2 +- .../fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py | 2 +- .../fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py | 2 +- .../fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py | 2 +- configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py | 2 +- .../knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k.py | 2 +- .../knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k.py | 2 +- .../knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k.py | 2 +- .../knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k.py | 2 +- .../knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k.py | 2 +- .../knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py | 2 +- .../knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k.py | 2 +- configs/mae/upernet_mae-base_fp16_512x512_160k_ade20k_ms.py | 2 +- configs/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py | 2 +- .../mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py | 2 +- .../lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py | 2 +- configs/segformer/segformer_mit-b0_512x512_160k_ade20k.py | 2 +- .../segformer_mit-b0_8x1_1024x1024_160k_cityscapes.py | 4 ++-- configs/setr/setr_mla_512x512_160k_b16_ade20k.py | 2 +- configs/setr/setr_naive_512x512_160k_b16_ade20k.py | 2 +- configs/setr/setr_pup_512x512_160k_b16_ade20k.py | 2 +- configs/stdc/stdc1_512x1024_80k_cityscapes.py | 2 +- ..._patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py | 2 +- .../twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py | 2 +- .../twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py | 2 +- configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py | 2 +- configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py | 2 +- configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py | 2 +- configs/vit/upernet_vit-b16_mln_512x512_160k_ade20k.py | 2 +- configs/vit/upernet_vit-b16_mln_512x512_80k_ade20k.py | 2 +- 67 files changed, 68 insertions(+), 68 deletions(-) diff --git a/configs/_base_/datasets/ade20k.py b/configs/_base_/datasets/ade20k.py index 31ac64fdf..8f4ac8ec2 100644 --- a/configs/_base_/datasets/ade20k.py +++ b/configs/_base_/datasets/ade20k.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='images/training', seg_map_path='annotations/training'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/ade20k_640x640.py b/configs/_base_/datasets/ade20k_640x640.py index 47e75fd66..a12189bf5 100644 --- a/configs/_base_/datasets/ade20k_640x640.py +++ b/configs/_base_/datasets/ade20k_640x640.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='images/training', seg_map_path='annotations/training'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/chase_db1.py b/configs/_base_/datasets/chase_db1.py index 9b861861b..ae5509022 100644 --- a/configs/_base_/datasets/chase_db1.py +++ b/configs/_base_/datasets/chase_db1.py @@ -32,7 +32,7 @@ train_dataloader = dict( img_path='images/training', seg_map_path='annotations/training'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/cityscapes.py b/configs/_base_/datasets/cityscapes.py index 5d314aa3f..8553127a7 100644 --- a/configs/_base_/datasets/cityscapes.py +++ b/configs/_base_/datasets/cityscapes.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='leftImg8bit/train', seg_map_path='gtFine/train'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/coco-stuff10k.py b/configs/_base_/datasets/coco-stuff10k.py index d617a7241..9cd062428 100644 --- a/configs/_base_/datasets/coco-stuff10k.py +++ b/configs/_base_/datasets/coco-stuff10k.py @@ -29,7 +29,7 @@ train_dataloader = dict( img_path='images/train2014', seg_map_path='annotations/train2014'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/coco-stuff164k.py b/configs/_base_/datasets/coco-stuff164k.py index 01c55ae8a..099d090a4 100644 --- a/configs/_base_/datasets/coco-stuff164k.py +++ b/configs/_base_/datasets/coco-stuff164k.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='images/train2017', seg_map_path='annotations/val2017'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/drive.py b/configs/_base_/datasets/drive.py index 85ee6accb..81bf858cf 100644 --- a/configs/_base_/datasets/drive.py +++ b/configs/_base_/datasets/drive.py @@ -31,7 +31,7 @@ train_dataloader = dict( img_path='images/training', seg_map_path='annotations/training'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/hrf.py b/configs/_base_/datasets/hrf.py index 1401d8f5a..6e59598c6 100644 --- a/configs/_base_/datasets/hrf.py +++ b/configs/_base_/datasets/hrf.py @@ -31,7 +31,7 @@ train_dataloader = dict( img_path='images/training', seg_map_path='annotations/training'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/isaid.py b/configs/_base_/datasets/isaid.py index 25b01c065..e10e1b303 100644 --- a/configs/_base_/datasets/isaid.py +++ b/configs/_base_/datasets/isaid.py @@ -35,7 +35,7 @@ train_dataloader = dict( img_path='img_dir/train', seg_map_path='ann_dir/train'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/loveda.py b/configs/_base_/datasets/loveda.py index 73b754ea3..3bcf8bddb 100644 --- a/configs/_base_/datasets/loveda.py +++ b/configs/_base_/datasets/loveda.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='img_dir/train', seg_map_path='ann_dir/train'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/pascal_context.py b/configs/_base_/datasets/pascal_context.py index 096e55599..4b8ddc885 100644 --- a/configs/_base_/datasets/pascal_context.py +++ b/configs/_base_/datasets/pascal_context.py @@ -32,7 +32,7 @@ train_dataloader = dict( ann_file='ImageSets/SegmentationContext/train.txt', pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/pascal_context_59.py b/configs/_base_/datasets/pascal_context_59.py index 21d36d0dc..a488b83f4 100644 --- a/configs/_base_/datasets/pascal_context_59.py +++ b/configs/_base_/datasets/pascal_context_59.py @@ -32,7 +32,7 @@ train_dataloader = dict( ann_file='ImageSets/SegmentationContext/train.txt', pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/pascal_voc12.py b/configs/_base_/datasets/pascal_voc12.py index b45d7db75..b423fd18f 100644 --- a/configs/_base_/datasets/pascal_voc12.py +++ b/configs/_base_/datasets/pascal_voc12.py @@ -29,7 +29,7 @@ train_dataloader = dict( ann_file='ImageSets/Segmentation/train.txt', pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/potsdam.py b/configs/_base_/datasets/potsdam.py index 2ff9d02a1..448e03309 100644 --- a/configs/_base_/datasets/potsdam.py +++ b/configs/_base_/datasets/potsdam.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='img_dir/train', seg_map_path='ann_dir/train'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/stare.py b/configs/_base_/datasets/stare.py index 64284d92e..09ab2e87c 100644 --- a/configs/_base_/datasets/stare.py +++ b/configs/_base_/datasets/stare.py @@ -31,7 +31,7 @@ train_dataloader = dict( img_path='images/training', seg_map_path='annotations/training'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/_base_/datasets/vaihingen.py b/configs/_base_/datasets/vaihingen.py index 96874bdda..a1eb9d984 100644 --- a/configs/_base_/datasets/vaihingen.py +++ b/configs/_base_/datasets/vaihingen.py @@ -28,7 +28,7 @@ train_dataloader = dict( img_path='img_dir/train', seg_map_path='ann_dir/train'), pipeline=train_pipeline)) val_dataloader = dict( - batch_size=4, + batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), diff --git a/configs/beit/upernet_beit-base_640x640_160k_ade20k_ms.py b/configs/beit/upernet_beit-base_640x640_160k_ade20k_ms.py index 9acbe9dc2..81db6ac2d 100644 --- a/configs/beit/upernet_beit-base_640x640_160k_ade20k_ms.py +++ b/configs/beit/upernet_beit-base_640x640_160k_ade20k_ms.py @@ -9,5 +9,5 @@ test_pipeline = [ dict(type='Resize', scale=(2560, 640), keep_ratio=True), dict(type='PackSegInputs'), ] -val_dataloader = dict(batch_size=2, dataset=dict(pipeline=test_pipeline)) +val_dataloader = dict(batch_size=1, dataset=dict(pipeline=test_pipeline)) test_dataloader = val_dataloader diff --git a/configs/beit/upernet_beit-base_8x2_640x640_160k_ade20k.py b/configs/beit/upernet_beit-base_8x2_640x640_160k_ade20k.py index 5a26b04b8..9a893ede4 100644 --- a/configs/beit/upernet_beit-base_8x2_640x640_160k_ade20k.py +++ b/configs/beit/upernet_beit-base_8x2_640x640_160k_ade20k.py @@ -37,5 +37,5 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py b/configs/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py index 7152c460d..6e970606c 100644 --- a/configs/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py +++ b/configs/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py @@ -31,5 +31,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.005, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes.py b/configs/bisenetv1/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes.py index 4db959e36..3c354910d 100644 --- a/configs/bisenetv1/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv1/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes.py @@ -20,5 +20,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py b/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py index 4a8ae7c35..047f80106 100644 --- a/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py @@ -25,5 +25,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py b/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py index 9b517405e..d37b3c5d2 100644 --- a/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py @@ -1,4 +1,4 @@ _base_ = './bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py' train_dataloader = dict(batch_size=8, num_workers=4) -val_dataloader = dict(batch_size=8, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py b/configs/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py index 2c408a789..8cc0a0856 100644 --- a/configs/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py +++ b/configs/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py @@ -26,5 +26,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.005, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes.py b/configs/bisenetv1/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes.py index 1e4af495f..23074e5f2 100644 --- a/configs/bisenetv1/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv1/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes.py @@ -51,5 +51,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py b/configs/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py index 92c3e04c7..1d90a2c27 100644 --- a/configs/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py +++ b/configs/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py @@ -31,5 +31,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.005, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py b/configs/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py index 9460f7049..c44792001 100644 --- a/configs/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py @@ -20,5 +20,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py b/configs/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py index 57adf5101..f77b90b5a 100644 --- a/configs/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py @@ -20,5 +20,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=8, num_workers=4) -val_dataloader = dict(batch_size=8, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py b/configs/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py index 4d9395a41..1f0000e11 100644 --- a/configs/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py +++ b/configs/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py @@ -79,5 +79,5 @@ param_scheduler = [ optimizer = dict(type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0005) optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/cgnet/cgnet_512x1024_60k_cityscapes.py b/configs/cgnet/cgnet_512x1024_60k_cityscapes.py index fdb781d38..307545edd 100644 --- a/configs/cgnet/cgnet_512x1024_60k_cityscapes.py +++ b/configs/cgnet/cgnet_512x1024_60k_cityscapes.py @@ -29,5 +29,5 @@ preprocess_cfg = dict(size=crop_size) model = dict(preprocess_cfg=preprocess_cfg) train_dataloader = dict(batch_size=8) -val_dataloader = dict(batch_size=8) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/cgnet/cgnet_680x680_60k_cityscapes.py b/configs/cgnet/cgnet_680x680_60k_cityscapes.py index e2aa3598b..2995c5b09 100644 --- a/configs/cgnet/cgnet_680x680_60k_cityscapes.py +++ b/configs/cgnet/cgnet_680x680_60k_cityscapes.py @@ -43,5 +43,5 @@ test_pipeline = [ train_dataloader = dict( batch_size=8, num_workers=4, dataset=dict(pipeline=train_pipeline)) val_dataloader = dict( - batch_size=8, num_workers=4, dataset=dict(pipeline=test_pipeline)) + batch_size=1, num_workers=4, dataset=dict(pipeline=test_pipeline)) test_dataloader = val_dataloader diff --git a/configs/convnext/upernet_convnext_base_fp16_512x512_160k_ade20k.py b/configs/convnext/upernet_convnext_base_fp16_512x512_160k_ade20k.py index 1c9e48d82..ecb670dbd 100644 --- a/configs/convnext/upernet_convnext_base_fp16_512x512_160k_ade20k.py +++ b/configs/convnext/upernet_convnext_base_fp16_512x512_160k_ade20k.py @@ -43,7 +43,7 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader # fp16 settings default_hooks = dict( diff --git a/configs/convnext/upernet_convnext_base_fp16_640x640_160k_ade20k.py b/configs/convnext/upernet_convnext_base_fp16_640x640_160k_ade20k.py index e625fd367..16814b65a 100644 --- a/configs/convnext/upernet_convnext_base_fp16_640x640_160k_ade20k.py +++ b/configs/convnext/upernet_convnext_base_fp16_640x640_160k_ade20k.py @@ -58,7 +58,7 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader # fp16 settings default_hooks = dict( diff --git a/configs/convnext/upernet_convnext_large_fp16_640x640_160k_ade20k.py b/configs/convnext/upernet_convnext_large_fp16_640x640_160k_ade20k.py index ba729e840..c2a5545cc 100644 --- a/configs/convnext/upernet_convnext_large_fp16_640x640_160k_ade20k.py +++ b/configs/convnext/upernet_convnext_large_fp16_640x640_160k_ade20k.py @@ -58,7 +58,7 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader # fp16 settings default_hooks = dict( diff --git a/configs/convnext/upernet_convnext_small_fp16_512x512_160k_ade20k.py b/configs/convnext/upernet_convnext_small_fp16_512x512_160k_ade20k.py index 555ed74a4..3d4746e10 100644 --- a/configs/convnext/upernet_convnext_small_fp16_512x512_160k_ade20k.py +++ b/configs/convnext/upernet_convnext_small_fp16_512x512_160k_ade20k.py @@ -57,7 +57,7 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader # fp16 settings default_hooks = dict( diff --git a/configs/convnext/upernet_convnext_tiny_fp16_512x512_160k_ade20k.py b/configs/convnext/upernet_convnext_tiny_fp16_512x512_160k_ade20k.py index 24054443a..99f8a6f9d 100644 --- a/configs/convnext/upernet_convnext_tiny_fp16_512x512_160k_ade20k.py +++ b/configs/convnext/upernet_convnext_tiny_fp16_512x512_160k_ade20k.py @@ -57,7 +57,7 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader # fp16 settings default_hooks = dict( diff --git a/configs/convnext/upernet_convnext_xlarge_fp16_640x640_160k_ade20k.py b/configs/convnext/upernet_convnext_xlarge_fp16_640x640_160k_ade20k.py index ac11a956f..59d8cd2a6 100644 --- a/configs/convnext/upernet_convnext_xlarge_fp16_640x640_160k_ade20k.py +++ b/configs/convnext/upernet_convnext_xlarge_fp16_640x640_160k_ade20k.py @@ -58,7 +58,7 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader # fp16 settings default_hooks = dict( diff --git a/configs/dpt/dpt_vit-b16_512x512_160k_ade20k.py b/configs/dpt/dpt_vit-b16_512x512_160k_ade20k.py index 3d83f5a58..3ac29da7e 100644 --- a/configs/dpt/dpt_vit-b16_512x512_160k_ade20k.py +++ b/configs/dpt/dpt_vit-b16_512x512_160k_ade20k.py @@ -39,5 +39,5 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py b/configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py index e95004a4c..0f854a6c0 100644 --- a/configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py +++ b/configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py @@ -6,5 +6,5 @@ crop_size = (512, 1024) preprocess_cfg = dict(size=crop_size) model = dict(preprocess_cfg=preprocess_cfg) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py b/configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py index 6f0452e63..6fbca14ba 100644 --- a/configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py +++ b/configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py @@ -1,5 +1,5 @@ # model settings _base_ = './fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes.py' train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py b/configs/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py index e8ff93957..839d54037 100644 --- a/configs/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py +++ b/configs/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py @@ -1,5 +1,5 @@ # model settings _base_ = './fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes.py' train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/fastfcn/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py b/configs/fastfcn/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py index 55833d11b..5c162c3fb 100644 --- a/configs/fastfcn/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py +++ b/configs/fastfcn/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py @@ -7,5 +7,5 @@ crop_size = (512, 1024) preprocess_cfg = dict(size=crop_size) model = dict(preprocess_cfg=preprocess_cfg) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py b/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py index 3b03dc5b4..397b46d59 100644 --- a/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py +++ b/configs/fastscnn/fast_scnn_lr0.12_8x4_160k_cityscapes.py @@ -7,7 +7,7 @@ preprocess_cfg = dict(size=crop_size) model = dict(preprocess_cfg=preprocess_cfg) # Re-config the data sampler. train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader # Re-config the optimizer. diff --git a/configs/knet/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k.py b/configs/knet/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k.py index 3bd8a1873..fe9baf5d9 100644 --- a/configs/knet/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k.py @@ -102,5 +102,5 @@ param_scheduler = [ ] # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k.py b/configs/knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k.py index 2e2b486a0..d2665f7ab 100644 --- a/configs/knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k.py @@ -102,5 +102,5 @@ param_scheduler = [ ] # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/knet/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k.py b/configs/knet/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k.py index 66e3400c7..311571f20 100644 --- a/configs/knet/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k.py @@ -101,5 +101,5 @@ param_scheduler = [ ] # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/knet/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k.py b/configs/knet/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k.py index 2450af1d6..75129131b 100644 --- a/configs/knet/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k.py @@ -102,5 +102,5 @@ param_scheduler = [ ] # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/knet/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k.py b/configs/knet/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k.py index e525fa5f3..c27f56b74 100644 --- a/configs/knet/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k.py @@ -17,5 +17,5 @@ model = dict( auxiliary_head=dict(in_channels=768)) # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py b/configs/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py index 751da435e..2a52fa296 100644 --- a/configs/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py @@ -39,5 +39,5 @@ val_dataloader = dict(dataset=dict(pipeline=test_pipeline)) test_dataloader = val_dataloader # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/knet/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k.py b/configs/knet/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k.py index fc09e7ff6..7bf81a8e6 100644 --- a/configs/knet/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k.py +++ b/configs/knet/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k.py @@ -68,5 +68,5 @@ param_scheduler = [ ] # In K-Net implementation we use batch size 2 per GPU as default train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/mae/upernet_mae-base_fp16_512x512_160k_ade20k_ms.py b/configs/mae/upernet_mae-base_fp16_512x512_160k_ade20k_ms.py index 30e26a050..b8a9dedaf 100644 --- a/configs/mae/upernet_mae-base_fp16_512x512_160k_ade20k_ms.py +++ b/configs/mae/upernet_mae-base_fp16_512x512_160k_ade20k_ms.py @@ -9,5 +9,5 @@ test_pipeline = [ dict(type='Resize', scale=(2048, 512), keep_ratio=True), dict(type='PackSegInputs') ] -val_dataloader = dict(batch_size=2, dataset=dict(pipeline=test_pipeline)) +val_dataloader = dict(batch_size=1, dataset=dict(pipeline=test_pipeline)) test_dataloader = val_dataloader diff --git a/configs/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py b/configs/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py index c892882db..d8499570e 100644 --- a/configs/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py +++ b/configs/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py @@ -55,5 +55,5 @@ fp16 = dict(loss_scale='dynamic') # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py b/configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py index e869971d5..cbc0abe3e 100644 --- a/configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py +++ b/configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py @@ -10,7 +10,7 @@ model = dict( # Re-config the data sampler. train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader runner = dict(type='IterBasedRunner', max_iters=320000) diff --git a/configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py b/configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py index 239f3c8a6..6cdfd73a6 100644 --- a/configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py +++ b/configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py @@ -7,7 +7,7 @@ preprocess_cfg = dict(size=crop_size) # Re-config the data sampler. model = dict(preprocess_cfg=preprocess_cfg) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader runner = dict(type='IterBasedRunner', max_iters=320000) diff --git a/configs/segformer/segformer_mit-b0_512x512_160k_ade20k.py b/configs/segformer/segformer_mit-b0_512x512_160k_ade20k.py index 32fb75728..40c9f1b17 100644 --- a/configs/segformer/segformer_mit-b0_512x512_160k_ade20k.py +++ b/configs/segformer/segformer_mit-b0_512x512_160k_ade20k.py @@ -40,5 +40,5 @@ param_scheduler = [ ) ] train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/segformer/segformer_mit-b0_8x1_1024x1024_160k_cityscapes.py b/configs/segformer/segformer_mit-b0_8x1_1024x1024_160k_cityscapes.py index ae76a4d19..06072070b 100644 --- a/configs/segformer/segformer_mit-b0_8x1_1024x1024_160k_cityscapes.py +++ b/configs/segformer/segformer_mit-b0_8x1_1024x1024_160k_cityscapes.py @@ -42,6 +42,6 @@ param_scheduler = [ ) ] -train_dataloader = dict(batch_size=1, num_workers=1) -val_dataloader = dict(batch_size=1, num_workers=1) +train_dataloader = dict(batch_size=1, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/setr/setr_mla_512x512_160k_b16_ade20k.py b/configs/setr/setr_mla_512x512_160k_b16_ade20k.py index d2c7ede66..710e1ec36 100644 --- a/configs/setr/setr_mla_512x512_160k_b16_ade20k.py +++ b/configs/setr/setr_mla_512x512_160k_b16_ade20k.py @@ -2,5 +2,5 @@ _base_ = ['./setr_mla_512x512_160k_b8_ade20k.py'] # num_gpus: 8 -> batch_size: 16 train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/setr/setr_naive_512x512_160k_b16_ade20k.py b/configs/setr/setr_naive_512x512_160k_b16_ade20k.py index 9b4cdad81..746f0c4b4 100644 --- a/configs/setr/setr_naive_512x512_160k_b16_ade20k.py +++ b/configs/setr/setr_naive_512x512_160k_b16_ade20k.py @@ -68,5 +68,5 @@ optimizer = dict( # num_gpus: 8 -> batch_size: 16 train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/setr/setr_pup_512x512_160k_b16_ade20k.py b/configs/setr/setr_pup_512x512_160k_b16_ade20k.py index ab0a19db7..95ba3d179 100644 --- a/configs/setr/setr_pup_512x512_160k_b16_ade20k.py +++ b/configs/setr/setr_pup_512x512_160k_b16_ade20k.py @@ -68,5 +68,5 @@ optimizer = dict( # num_gpus: 8 -> batch_size: 16 train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/stdc/stdc1_512x1024_80k_cityscapes.py b/configs/stdc/stdc1_512x1024_80k_cityscapes.py index 30e7909c3..57877173d 100644 --- a/configs/stdc/stdc1_512x1024_80k_cityscapes.py +++ b/configs/stdc/stdc1_512x1024_80k_cityscapes.py @@ -17,5 +17,5 @@ param_scheduler = [ ) ] train_dataloader = dict(batch_size=12, num_workers=4) -val_dataloader = dict(batch_size=12, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py b/configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py index d3ccc69d5..c6a6e3396 100644 --- a/configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py +++ b/configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py @@ -53,5 +53,5 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py b/configs/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py index c13378aca..b9a3d0681 100644 --- a/configs/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py +++ b/configs/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py @@ -9,5 +9,5 @@ model = dict( drop_path_rate=0.3)) train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py b/configs/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py index 29c440008..a3e37ef2a 100644 --- a/configs/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py +++ b/configs/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py @@ -9,5 +9,5 @@ model = dict( drop_path_rate=0.3)) train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py b/configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py index 5a01a2320..717c1b323 100644 --- a/configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py +++ b/configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py @@ -50,5 +50,5 @@ param_scheduler = [ ] train_dataloader = dict(batch_size=2, num_workers=2) -val_dataloader = dict(batch_size=2, num_workers=2) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py b/configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py index 0206abc90..d63166313 100644 --- a/configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py +++ b/configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py @@ -12,5 +12,5 @@ model = dict( train_cfg=dict(), test_cfg=dict(mode='whole')) train_dataloader = dict(batch_size=4, num_workers=4) -val_dataloader = dict(batch_size=4, num_workers=4) +val_dataloader = dict(batch_size=1, num_workers=4) test_dataloader = val_dataloader diff --git a/configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py b/configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py index 1169fc436..4e0863147 100644 --- a/configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py +++ b/configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py @@ -46,5 +46,5 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/vit/upernet_vit-b16_mln_512x512_160k_ade20k.py b/configs/vit/upernet_vit-b16_mln_512x512_160k_ade20k.py index 4abd804a5..fbc430172 100644 --- a/configs/vit/upernet_vit-b16_mln_512x512_160k_ade20k.py +++ b/configs/vit/upernet_vit-b16_mln_512x512_160k_ade20k.py @@ -45,5 +45,5 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader diff --git a/configs/vit/upernet_vit-b16_mln_512x512_80k_ade20k.py b/configs/vit/upernet_vit-b16_mln_512x512_80k_ade20k.py index f937fa8d5..6f9e055b1 100644 --- a/configs/vit/upernet_vit-b16_mln_512x512_80k_ade20k.py +++ b/configs/vit/upernet_vit-b16_mln_512x512_80k_ade20k.py @@ -45,5 +45,5 @@ param_scheduler = [ # By default, models are trained on 8 GPUs with 2 images per GPU train_dataloader = dict(batch_size=2) -val_dataloader = dict(batch_size=2) +val_dataloader = dict(batch_size=1) test_dataloader = val_dataloader