my mmseg version：0.30.0

`base = './cityscapes.py' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) crop_size = (1024, 1024) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations'), dict(type='Resize', img_scale=(1024, 1024), ratio_range=(0.5, 2.0)), dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), dict(type='RandomFlip', prob=0.5), dict(type='PhotoMetricDistortion'), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg']), ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1024, 1024),

img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],

    flip=False,
    transforms=[
        dict(type='Resize', keep_ratio=True),
        dict(type='RandomFlip'),
        dict(type='Normalize', **img_norm_cfg),
        dict(type='Pad', size_divisor=32),
        dict(type='ImageToTensor', keys=['img']),
        dict(type='Collect', keys=['img']),
    ])

] data = dict( train=dict(pipeline=train_pipeline), val=dict(pipeline=test_pipeline), test=dict(pipeline=test_pipeline))` 在transforms里加入pad后：

加入前：

我对模型内加入了上采样，由于图像尺寸的缘故，如果不进行pad，会导致上采样后与下采样前的图片尺寸对不上，所以要怎么正确的在test-pipeline里使用Pad？如果您能解答我的问题我将非常感谢！

open-mmlab / mmsegmentation

Why does using Pad in the test_pipeline lead to a significant decrease in IoU and Acc? #3685

img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],