46 lines
1.1 KiB
Python
46 lines
1.1 KiB
Python
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from clrnet.utils import Registry, build_from_cfg
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import torch.nn as nn
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BACKBONES = Registry('backbones')
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AGGREGATORS = Registry('aggregators')
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HEADS = Registry('heads')
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NECKS = Registry('necks')
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NETS = Registry('nets')
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def build(cfg, registry, default_args=None):
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if isinstance(cfg, list):
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modules = [
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build_from_cfg(cfg_, registry, default_args) for cfg_ in cfg
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]
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return nn.Sequential(*modules)
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else:
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return build_from_cfg(cfg, registry, default_args)
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def build_backbones(cfg):
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return build(cfg.backbone, BACKBONES, default_args=dict(cfg=cfg))
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def build_necks(cfg):
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return build(cfg.necks, NECKS, default_args=dict(cfg=cfg))
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def build_aggregator(cfg):
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return build(cfg.aggregator, AGGREGATORS, default_args=dict(cfg=cfg))
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def build_heads(cfg):
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return build(cfg.heads, HEADS, default_args=dict(cfg=cfg))
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def build_head(split_cfg, cfg):
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return build(split_cfg, HEADS, default_args=dict(cfg=cfg))
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def build_net(cfg):
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return build(cfg.net, NETS, default_args=dict(cfg=cfg))
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def build_necks(cfg):
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return build(cfg.neck, NECKS, default_args=dict(cfg=cfg))
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