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_base_ = './mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_4.0gf',
backbone=dict(
type='RegNet',
arch='regnetx_4.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch'),
neck=dict(
type='FPN',
in_channels=[80, 240, 560, 1360],
out_channels=256,
num_outs=5))
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