_base_ = '2s-agcn_8xb16-joint-u100-80e_ntu60-xsub-keypoint-2d.py'

dataset_type = 'PoseDataset'
ann_file = 'data/skeleton/ntu60_2d.pkl'
train_pipeline = [
    dict(type='PreNormalize2D'),
    dict(type='GenSkeFeat', dataset='coco', feats=['jm']),
    dict(type='UniformSampleFrames', clip_len=100),
    dict(type='PoseDecode'),
    dict(type='FormatGCNInput', num_person=2),
    dict(type='PackActionInputs')
]
val_pipeline = [
    dict(type='PreNormalize2D'),
    dict(type='GenSkeFeat', dataset='coco', feats=['jm']),
    dict(
        type='UniformSampleFrames', clip_len=100, num_clips=1, test_mode=True),
    dict(type='PoseDecode'),
    dict(type='FormatGCNInput', num_person=2),
    dict(type='PackActionInputs')
]
test_pipeline = [
    dict(type='PreNormalize2D'),
    dict(type='GenSkeFeat', dataset='coco', feats=['jm']),
    dict(
        type='UniformSampleFrames', clip_len=100, num_clips=10,
        test_mode=True),
    dict(type='PoseDecode'),
    dict(type='FormatGCNInput', num_person=2),
    dict(type='PackActionInputs')
]

train_dataloader = dict(
    batch_size=16,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=True),
    dataset=dict(
        type='RepeatDataset',
        times=5,
        dataset=dict(
            type=dataset_type,
            ann_file=ann_file,
            pipeline=train_pipeline,
            split='xsub_train')))
val_dataloader = dict(
    batch_size=16,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type=dataset_type,
        ann_file=ann_file,
        pipeline=val_pipeline,
        split='xsub_val',
        test_mode=True))
test_dataloader = dict(
    batch_size=1,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type=dataset_type,
        ann_file=ann_file,
        pipeline=test_pipeline,
        split='xsub_val',
        test_mode=True))