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_base_ = ['./minkunet18_w32_torchsparse_8xb2-amp-15e_semantickitti.py']
model = dict(
backbone=dict(
base_channels=16,
encoder_channels=[16, 32, 64, 128],
decoder_channels=[128, 64, 48, 48]),
decode_head=dict(channels=48))
# NOTE: Due to TorchSparse backend, the model performance is relatively
# dependent on random seeds, and if random seeds are not specified the
# model performance will be different (± 1.5 mIoU).
randomness = dict(seed=1588147245)
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