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Fix a few missed model deprecations and one missed pretrained cfg

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This commit is contained in:
Ross Wightman 2023-11-20 12:41:49 -08:00
parent 057fdb570b
commit dfb8658100
2 changed files with 6 additions and 35 deletions
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30
timm/models/efficientnet.py
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@ -1441,12 +1441,6 @@ def mnasnet_100(pretrained=False, **kwargs) -> EfficientNet:
return model return model
@register_model
def mnasnet_b1(pretrained=False, **kwargs) -> EfficientNet:
""" MNASNet B1, depth multiplier of 1.0. """
return mnasnet_100(pretrained, **kwargs)
@register_model @register_model
def mnasnet_140(pretrained=False, **kwargs) -> EfficientNet: def mnasnet_140(pretrained=False, **kwargs) -> EfficientNet:
""" MNASNet B1, depth multiplier of 1.4 """ """ MNASNet B1, depth multiplier of 1.4 """
@ -1475,12 +1469,6 @@ def semnasnet_100(pretrained=False, **kwargs) -> EfficientNet:
return model return model
@register_model
def mnasnet_a1(pretrained=False, **kwargs) -> EfficientNet:
""" MNASNet A1 (w/ SE), depth multiplier of 1.0. """
return semnasnet_100(pretrained, **kwargs)
@register_model @register_model
def semnasnet_140(pretrained=False, **kwargs) -> EfficientNet: def semnasnet_140(pretrained=False, **kwargs) -> EfficientNet:
""" MNASNet A1 (w/ SE), depth multiplier of 1.4. """ """ MNASNet A1 (w/ SE), depth multiplier of 1.4. """
@ -1590,13 +1578,6 @@ def efficientnet_b2(pretrained=False, **kwargs) -> EfficientNet:
return model return model
@register_model
def efficientnet_b2a(pretrained=False, **kwargs) -> EfficientNet:
""" EfficientNet-B2 @ 288x288 w/ 1.0 test crop"""
# WARN this model def is deprecated, different train/test res + test crop handled by default_cfg now
return efficientnet_b2(pretrained=pretrained, **kwargs)
@register_model @register_model
def efficientnet_b3(pretrained=False, **kwargs) -> EfficientNet: def efficientnet_b3(pretrained=False, **kwargs) -> EfficientNet:
""" EfficientNet-B3 """ """ EfficientNet-B3 """
@ -1606,13 +1587,6 @@ def efficientnet_b3(pretrained=False, **kwargs) -> EfficientNet:
return model return model
@register_model
def efficientnet_b3a(pretrained=False, **kwargs) -> EfficientNet:
""" EfficientNet-B3 @ 320x320 w/ 1.0 test crop-pct """
# WARN this model def is deprecated, different train/test res + test crop handled by default_cfg now
return efficientnet_b3(pretrained=pretrained, **kwargs)
@register_model @register_model
def efficientnet_b4(pretrained=False, **kwargs) -> EfficientNet: def efficientnet_b4(pretrained=False, **kwargs) -> EfficientNet:
""" EfficientNet-B4 """ """ EfficientNet-B4 """
@ -2361,4 +2335,8 @@ register_model_deprecations(__name__, {
'tf_efficientnetv2_m_in21k': 'tf_efficientnetv2_m.in21k', 'tf_efficientnetv2_m_in21k': 'tf_efficientnetv2_m.in21k',
'tf_efficientnetv2_l_in21k': 'tf_efficientnetv2_l.in21k', 'tf_efficientnetv2_l_in21k': 'tf_efficientnetv2_l.in21k',
'tf_efficientnetv2_xl_in21k': 'tf_efficientnetv2_xl.in21k', 'tf_efficientnetv2_xl_in21k': 'tf_efficientnetv2_xl.in21k',
'efficientnet_b2a': 'efficientnet_b2',
'efficientnet_b3a': 'efficientnet_b3',
'mnasnet_a1': 'semnasnet_100',
'mnasnet_b1': 'mnasnet_100',
}) })

11
timm/models/resnet.py
View File

@ -1116,6 +1116,7 @@ default_cfgs = generate_default_cfgs({
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnetblur50-84f4748f.pth'), url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnetblur50-84f4748f.pth'),
'resnetblur50d.untrained': _ttcfg(first_conv='conv1.0'), 'resnetblur50d.untrained': _ttcfg(first_conv='conv1.0'),
'resnetblur101d.untrained': _ttcfg(first_conv='conv1.0'), 'resnetblur101d.untrained': _ttcfg(first_conv='conv1.0'),
'resnetaa34d.untrained': _ttcfg(first_conv='conv1.0'),
'resnetaa50.a1h_in1k': _rcfg( 'resnetaa50.a1h_in1k': _rcfg(
hf_hub_id='timm/', hf_hub_id='timm/',
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnetaa50_a1h-4cf422b3.pth'), url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnetaa50_a1h-4cf422b3.pth'),
@ -1730,15 +1731,6 @@ def seresnext26t_32x4d(pretrained: bool = False, **kwargs) -> ResNet:
return _create_resnet('seresnext26t_32x4d', pretrained, **dict(model_args, **kwargs)) return _create_resnet('seresnext26t_32x4d', pretrained, **dict(model_args, **kwargs))
@register_model
def seresnext26tn_32x4d(pretrained: bool = False, **kwargs) -> ResNet:
"""Constructs a SE-ResNeXt-26-T model.
NOTE I deprecated previous 't' model defs and replaced 't' with 'tn', this was the only tn model of note
so keeping this def for backwards compat with any uses out there. Old 't' model is lost.
"""
return seresnext26t_32x4d(pretrained=pretrained, **kwargs)
@register_model @register_model
def seresnext50_32x4d(pretrained: bool = False, **kwargs) -> ResNet: def seresnext50_32x4d(pretrained: bool = False, **kwargs) -> ResNet:
model_args = dict( model_args = dict(
@ -2028,4 +2020,5 @@ register_model_deprecations(__name__, {
'gluon_seresnext101_32x4d': 'seresnext101_32x4d.gluon_in1k', 'gluon_seresnext101_32x4d': 'seresnext101_32x4d.gluon_in1k',
'gluon_seresnext101_64x4d': 'seresnext101_64x4d.gluon_in1k', 'gluon_seresnext101_64x4d': 'seresnext101_64x4d.gluon_in1k',
'gluon_senet154': 'senet154.gluon_in1k', 'gluon_senet154': 'senet154.gluon_in1k',
'seresnext26tn_32x4d': 'seresnext26t_32x4d',
}) })