tood_r101_fpn_mstrain_2x_coco.py

_base_ = './tood_r50_fpn_mstrain_2x_coco.py'
model = dict(
    pretrained='torchvision://resnet101',
    backbone=dict(
        type='ResNet',
        depth=101,
        num_stages=4,
        out_indices=(0, 1, 2, 3),
        frozen_stages=1,
        norm_cfg=dict(type='BN', requires_grad=True),
        norm_eval=True,
        style='pytorch'))

data = dict(samples_per_gpu=2,
            workers_per_gpu=2)