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_base_ = '../gcnet/mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py'
# model settings
model = dict(
roi_head=dict(
bbox_roi_extractor=dict(
type='GenericRoIExtractor',
aggregation='sum',
roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=2),
out_channels=256,
featmap_strides=[4, 8, 16, 32],
pre_cfg=dict(
type='ConvModule',
in_channels=256,
out_channels=256,
kernel_size=5,
padding=2,
inplace=False,
),
post_cfg=dict(
type='GeneralizedAttention',
in_channels=256,
spatial_range=-1,
num_heads=6,
attention_type='0100',
kv_stride=2)),
mask_roi_extractor=dict(
type='GenericRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=2),
out_channels=256,
featmap_strides=[4, 8, 16, 32],
pre_cfg=dict(
type='ConvModule',
in_channels=256,
out_channels=256,
kernel_size=5,
padding=2,
inplace=False,
),
post_cfg=dict(
type='GeneralizedAttention',
in_channels=256,
spatial_range=-1,
num_heads=6,
attention_type='0100',
kv_stride=2))))
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