Upload 122 files

ntu60_xsub/b_1/b_1.py

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+
+modality = 'b'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/b_1'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/b_1/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4bd704f49e2c75cc65f49fc3231c412150197be00eb025d423300146a591f01c
+size 6637515

ntu60_xsub/b_1/best_top1_acc_epoch_150.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0870bbceba1711ec865e3780428d5e91ff11240da65bb8974090e853b72a0587
+size 32948721

ntu60_xsub/b_2/b_2.py

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+modality = 'b'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/b_2'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/b_2/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:19976298b72cca45e66196a2dcc2d7ea29fde877e7d6b70a7aba6e957836da0b
+size 6638245

ntu60_xsub/b_2/best_top1_acc_epoch_147.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ef8476866bf1aa2b047acbd02d27e1eee5da7a05ded6271f2707b8c83a04d2db
+size 32944689

ntu60_xsub/b_3/b_3.py

@@ -0,0 +1,98 @@
+modality = 'b'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/b_3'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['b']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['b']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/b_3/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:65545b3d1d70709d0a7b431d271168343b69b50096256999c34ab4468e9fb3ca
+size 6638553

ntu60_xsub/b_3/best_top1_acc_epoch_150.pth

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+version https://git-lfs.github.com/spec/v1
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+size 32944689

ntu60_xsub/bm/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
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+size 6638802

ntu60_xsub/bm/best_top1_acc_epoch_144.pth

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+version https://git-lfs.github.com/spec/v1
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+size 32944689

ntu60_xsub/bm/bm.py

@@ -0,0 +1,98 @@
+modality = 'bm'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/bm'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+    dict(type='GenSkeFeat', feats=['bm']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['bm']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['bm']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+            dict(type='GenSkeFeat', feats=['bm']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['bm']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['bm']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/j_1/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a8fd9984b0ce5a420e24b6a9297abf340f96f7488f2c54e396ecbbdccdece868
+size 6638847

ntu60_xsub/j_1/best_top1_acc_epoch_148.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8106680babcd4a9831fe58babc9c24db7fa454e548ddabdbd9ef953539ffe16e
+size 32302963

ntu60_xsub/j_1/j_1.py

@@ -0,0 +1,96 @@
+modality = 'j'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/j_1'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 2)

ntu60_xsub/j_2/best_pred.pkl

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+oid sha256:86393749f4195f65c5d1b86af8513d5ed39bac8e67c86583fb7fdda865b41d8a
+size 6637149

ntu60_xsub/j_2/best_top1_acc_epoch_149.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cc521f426ecbf6a7fa2979e44e4fee126b76c06091acefdeff5d37d13a5d0c59
+size 32944689

ntu60_xsub/j_2/j_2.py

@@ -0,0 +1,96 @@
+modality = 'j'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/j_2'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/j_3/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7265074179909a76b167eedb569b65daf914ebaf5fca52b259f65c5d3db1d0c3
+size 6640275

ntu60_xsub/j_3/best_top1_acc_epoch_135.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2090d11d4301eef9ed9f36354fdaaf069b0323a6931ee76dbb646d8bebf6704b
+size 32944689

ntu60_xsub/j_3/j_3.py

@@ -0,0 +1,96 @@
+modality = 'j'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/j_3'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['j']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['j']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/jm/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6cf0f6059cef9957cc9e149181352f8505c1a6d99b19a2d68d4a412e7f90a00a
+size 6636961

ntu60_xsub/jm/best_top1_acc_epoch_141.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6615f8923f98776d08ecbd89fd5630bd1a38071716a633d042a3c403c246d1c0
+size 32944689

ntu60_xsub/jm/jm.py

@@ -0,0 +1,96 @@
+modality = 'jm'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/jm'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='GenSkeFeat', feats=['jm']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['jm']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['jm']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='GenSkeFeat', feats=['jm']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['jm']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['jm']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/k_1/best_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4fe471bb63f4c76c901d82c60f8292141f5a591674d3b7b69f879bb4def4e18a
+size 6637595

ntu60_xsub/k_1/best_top1_acc_epoch_142.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:76d22352971f82a694dde9a3cd4995082f648c178dcc3fdee2c41f9f836ba15e
+size 32944689

ntu60_xsub/k_1/k_1.py

@@ -0,0 +1,98 @@
+modality = 'k'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/k_2'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+    dict(type='GenSkeFeat', feats=['k']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['k']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['k']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+            dict(type='GenSkeFeat', feats=['k']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['k']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['k']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)

ntu60_xsub/k_2/best_pred.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:980441f06551b5ca607b1cd989cea09246dd7f0aeff88efec4adec662b6d74df
+size 6638454

ntu60_xsub/k_2/best_top1_acc_epoch_148.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b02240970c4acef27302ec970f9910e39bf7f95bbf3a4acc59378c3a2a9c8b4f
+size 32944689

ntu60_xsub/k_2/k_2.py

@@ -0,0 +1,98 @@
+modality = 'k'
+graph = 'nturgb+d'
+work_dir = './work_dirs/test_aclnet/ntu60_xsub/k_1'
+model = dict(
+    type='RecognizerGCN',
+    backbone=dict(
+        type='GCN_Module',
+        gcn_ratio=0.125,
+        gcn_ctr='T',
+        gcn_ada='T',
+        tcn_ms_cfg=[(3, 1), (3, 2), (3, 3), (3, 4), ('max', 3), '1x1'],
+        graph_cfg=dict(
+            layout='nturgb+d',
+            mode='random',
+            num_filter=8,
+            init_off=0.04,
+            init_std=0.02)),
+    cls_head=dict(type='SimpleHead', data_cfg='ntu60', num_classes=60, in_channels=384))
+dataset_type = 'PoseDataset'
+ann_file = '/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl'
+train_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='RandomRot', theta=0.2),
+    dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+    dict(type='GenSkeFeat', feats=['k']),
+    dict(type='UniformSampleDecode', clip_len=100),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+val_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['k']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+test_pipeline = [
+    dict(type='PreNormalize3D', align_spine=False),
+    dict(type='GenSkeFeat', feats=['k']),
+    dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+    dict(type='FormatGCNInput'),
+    dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['keypoint'])
+]
+data = dict(
+    videos_per_gpu=16,
+    workers_per_gpu=4,
+    test_dataloader=dict(videos_per_gpu=1),
+    train=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='RandomRot', theta=0.2),
+            dict(type='Spatial_Flip', dataset='nturgb+d', p=0.5),
+            dict(type='GenSkeFeat', feats=['k']),
+            dict(type='UniformSampleDecode', clip_len=100),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_train'),
+    val=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['k']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=1),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'),
+    test=dict(
+        type='PoseDataset',
+        ann_file='/data/lhd/pyskl_data/nturgbd/ntu60_3danno.pkl',
+        pipeline=[
+            dict(type='PreNormalize3D', align_spine=False),
+            dict(type='GenSkeFeat', feats=['k']),
+            dict(type='UniformSampleDecode', clip_len=100, num_clips=10),
+            dict(type='FormatGCNInput'),
+            dict(type='Collect', keys=['keypoint', 'label'], meta_keys=[]),
+            dict(type='ToTensor', keys=['keypoint'])
+        ],
+        split='xsub_val'))
+optimizer = dict(
+    type='SGD', lr=0.025, momentum=0.9, weight_decay=0.0005, nesterov=True)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='CosineAnnealing', min_lr=0, by_epoch=False)
+total_epochs = 150
+checkpoint_config = dict(interval=1)
+evaluation = dict(interval=1, metrics=['top_k_accuracy'])
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+gpu_ids = range(0, 1)