anticipation/anticipation/configs/long_term_anti/epic/verb_anti_vpretrain/rnn.py [5:26]:
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model = dict(
    type='RNNModel',
    num_classes=num_classes,
    backbone=dict(
        type="mlp1D",
        num_layers=1,
        in_channels=2048,
        h_channels=2048,
        out_channels=2048,
    ),
    lstm=dict(
        type="lstm",
        num_layers=1,
        in_channels=2048,
        out_channels=2048,
        dropout=0.0,
    ),
    fc_indim=2048,
)

data = set_dataset_type(data, 'EpicFutureLabelsI3D')
work_dir = get_workdir(__file__)
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anticipation/anticipation/configs/long_term_anti/gtea/verb_anti_vpretrain/rnn.py [5:26]:
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model = dict(
    type='RNNModel',
    num_classes=num_classes,
    backbone=dict(
        type="mlp1D",
        num_layers=1,
        in_channels=2048,
        h_channels=2048,
        out_channels=2048,
    ),
    lstm=dict(
        type="lstm",
        num_layers=1,
        in_channels=2048,
        out_channels=2048,
        dropout=0.0,
    ),
    fc_indim=2048,
)

data = set_dataset_type(data, 'EpicFutureLabelsI3D')
work_dir = get_workdir(__file__)
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