efficientnet-b2-test.py

_base_ = [
    'configs/_base_/models/tiny_efficientnet_b2.py',
    'configs/_base_/datasets/tiny_imagenet_bs32.py',
    'configs/_base_/schedules/imagenet_bs256.py',
    'configs/_base_/default_runtime.py',
]

# dataset settings
train_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(type='EfficientNetRandomCrop', scale=260),
    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
    dict(type='PackInputs'),
]

test_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(type='EfficientNetCenterCrop', crop_size=260),
    dict(type='PackInputs'),
]

train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
test_dataloader = dict(dataset=dict(pipeline=test_pipeline))