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@ -51,7 +51,7 @@ default_cfgs = {
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/sehalonet33ts_256-87e053f9.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/sehalonet33ts_256-87e053f9.pth',
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input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
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input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
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'halonet50ts': _cfg(
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'halonet50ts': _cfg(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/halonet50ts_256_ra3-f07eab9f.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/halonet50ts_a1h_256-c6d7ff15.pth',
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input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
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input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
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'eca_halonext26ts': _cfg(
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'eca_halonext26ts': _cfg(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/eca_halonext26ts_256-1e55880b.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/eca_halonext26ts_256-1e55880b.pth',
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@ -61,7 +61,7 @@ default_cfgs = {
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26t_c_256-e5a5c857.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26t_c_256-e5a5c857.pth',
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min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=0.94),
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min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=0.94),
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'lambda_resnet50ts': _cfg(
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'lambda_resnet50ts': _cfg(
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url='',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet50ts_a1h_256-b87370f7.pth',
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min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8)),
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min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8)),
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'lambda_resnet26rpt_256': _cfg(
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'lambda_resnet26rpt_256': _cfg(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26rpt_c_256-ab00292d.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26rpt_c_256-ab00292d.pth',
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@ -71,8 +71,12 @@ default_cfgs = {
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/haloregnetz_c_raa_256-c8ad7616.pth',
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/haloregnetz_c_raa_256-c8ad7616.pth',
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mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
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mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
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first_conv='stem.conv', input_size=(3, 224, 224), pool_size=(7, 7), min_input_size=(3, 224, 224), crop_pct=0.94),
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first_conv='stem.conv', input_size=(3, 224, 224), pool_size=(7, 7), min_input_size=(3, 224, 224), crop_pct=0.94),
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'trionet50ts_256': _cfg(
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url='',
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'lamhalobotnet50ts_256': _cfg(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lamhalobotnet_a1h_256-c9bc4e74.pth',
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fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
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'halo2botnet50ts_256': _cfg(
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/halo2botnet50ts_a1h_256-ad9e16fb.pth',
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fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
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fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
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}
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}
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@ -262,7 +266,7 @@ model_cfgs = dict(
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),
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),
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# experimental
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# experimental
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trionet50ts=ByoModelCfg(
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lamhalobotnet50ts=ByoModelCfg(
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blocks=(
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blocks=(
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ByoBlockCfg(type='bottle', d=3, c=256, s=1, gs=0, br=0.25),
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ByoBlockCfg(type='bottle', d=3, c=256, s=1, gs=0, br=0.25),
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interleave_blocks(
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interleave_blocks(
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@ -280,6 +284,24 @@ model_cfgs = dict(
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stem_pool='',
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stem_pool='',
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act_layer='silu',
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act_layer='silu',
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),
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),
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halo2botnet50ts=ByoModelCfg(
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blocks=(
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ByoBlockCfg(type='bottle', d=3, c=256, s=1, gs=0, br=0.25),
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interleave_blocks(
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types=('bottle', 'self_attn'), d=4, c=512, s=2, gs=0, br=0.25,
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self_attn_layer='halo', self_attn_kwargs=dict(halo_size=3)),
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interleave_blocks(
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types=('bottle', 'self_attn'), d=6, c=1024, s=2, gs=0, br=0.25,
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self_attn_layer='halo', self_attn_kwargs=dict(halo_size=3)),
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interleave_blocks(
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types=('bottle', 'self_attn'), d=3, c=2048, s=2, gs=0, br=0.25,
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self_attn_layer='bottleneck', self_attn_kwargs=dict()),
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),
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stem_chs=64,
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stem_type='tiered',
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stem_pool='',
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act_layer='silu',
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),
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)
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)
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@ -382,7 +404,14 @@ def haloregnetz_b(pretrained=False, **kwargs):
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@register_model
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@register_model
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def trionet50ts_256(pretrained=False, **kwargs):
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def lamhalobotnet50ts_256(pretrained=False, **kwargs):
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""" TrioNet
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""" Combo Attention (Lambda + Halo + Bot) Network
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"""
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return _create_byoanet('lamhalobotnet50ts_256', 'lamhalobotnet50ts', pretrained=pretrained, **kwargs)
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@register_model
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def halo2botnet50ts_256(pretrained=False, **kwargs):
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""" Combo Attention (Halo + Halo + Bot) Network
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"""
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"""
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return _create_byoanet('trionet50ts_256', 'trionet50ts', pretrained=pretrained, **kwargs)
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return _create_byoanet('halo2botnet50ts_256', 'halo2botnet50ts', pretrained=pretrained, **kwargs)
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