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_base_ = [
'../_base_/models/pointpillars_hv_fpn_lyft.py',
'../_base_/datasets/lyft-3d.py',
'../_base_/schedules/schedule-2x.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
pts_neck=dict(
_delete_=True,
type='SECONDFPN',
norm_cfg=dict(type='naiveSyncBN2d', eps=1e-3, momentum=0.01),
in_channels=[64, 128, 256],
upsample_strides=[1, 2, 4],
out_channels=[128, 128, 128]),
pts_bbox_head=dict(
in_channels=384,
feat_channels=384,
anchor_generator=dict(
_delete_=True,
type='AlignedAnchor3DRangeGenerator',
ranges=[[-80, -80, -1.0715024, 80, 80, -1.0715024],
[-80, -80, -0.3033737, 80, 80, -0.3033737],
[-80, -80, -0.3519405, 80, 80, -0.3519405],
[-80, -80, -0.8871424, 80, 80, -0.8871424],
[-80, -80, -0.6276341, 80, 80, -0.6276341],
[-80, -80, -1.3220503, 80, 80, -1.3220503],
[-80, -80, -1.0709302, 80, 80, -1.0709302],
[-80, -80, -0.9122268, 80, 80, -0.9122268],
[-80, -80, -1.8012227, 80, 80, -1.8012227]],
sizes=[
[4.75, 1.92, 1.71], # car
[10.24, 2.84, 3.44], # truck
[12.70, 2.92, 3.42], # bus
[6.52, 2.42, 2.34], # emergency vehicle
[8.17, 2.75, 3.20], # other vehicle
[2.35, 0.96, 1.59], # motorcycle
[1.76, 0.63, 1.44], # bicycle
[0.80, 0.76, 1.76], # pedestrian
[0.73, 0.35, 0.50] # animal
],
rotations=[0, 1.57],
reshape_out=True)))
# Default setting for scaling LR automatically
# - `enable` means enable scaling LR automatically
# or not by default.
# - `base_batch_size` = (8 GPUs) x (2 samples per GPU).
auto_scale_lr = dict(enable=False, base_batch_size=16)
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