Fix some half removed resnet model defs, pooling for ecaresnet269d

pull/413/head
Ross Wightman 4 years ago
parent 2a8c4dc63b
commit 3b57490a63

@ -217,7 +217,7 @@ default_cfgs = {
interpolation='bicubic', first_conv='conv1.0', input_size=(3, 256, 256), crop_pct=0.94, pool_size=(8, 8)), interpolation='bicubic', first_conv='conv1.0', input_size=(3, 256, 256), crop_pct=0.94, pool_size=(8, 8)),
'ecaresnet269d': _cfg( 'ecaresnet269d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ecaresnet269d_320_ra2-7baa55cb.pth', url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ecaresnet269d_320_ra2-7baa55cb.pth',
interpolation='bicubic', first_conv='conv1.0', input_size=(3, 320, 320), pool_size=(8, 8), interpolation='bicubic', first_conv='conv1.0', input_size=(3, 320, 320), pool_size=(10, 10),
crop_pct=1.0, test_input_size=(3, 352, 352)), crop_pct=1.0, test_input_size=(3, 352, 352)),
# Efficient Channel Attention ResNeXts # Efficient Channel Attention ResNeXts
@ -1029,14 +1029,6 @@ def swsl_resnext101_32x16d(pretrained=True, **kwargs):
return _create_resnet('swsl_resnext101_32x16d', pretrained, **model_args) return _create_resnet('swsl_resnext101_32x16d', pretrained, **model_args)
@register_model
def ecaresnet18(pretrained=False, **kwargs):
""" Constructs an ECA-ResNet-18 model.
"""
model_args = dict(block=BasicBlock, layers=[2, 2, 2, 2], block_args=dict(attn_layer='eca'), **kwargs)
return _create_resnet('ecaresnet18', pretrained, **model_args)
@register_model @register_model
def ecaresnet26t(pretrained=False, **kwargs): def ecaresnet26t(pretrained=False, **kwargs):
"""Constructs an ECA-ResNeXt-26-T model. """Constructs an ECA-ResNeXt-26-T model.
@ -1049,14 +1041,6 @@ def ecaresnet26t(pretrained=False, **kwargs):
return _create_resnet('ecaresnet26t', pretrained, **model_args) return _create_resnet('ecaresnet26t', pretrained, **model_args)
@register_model
def ecaresnet50(pretrained=False, **kwargs):
"""Constructs an ECA-ResNet-50 model.
"""
model_args = dict(block=Bottleneck, layers=[3, 4, 6, 3], block_args=dict(attn_layer='eca'), **kwargs)
return _create_resnet('ecaresnet50', pretrained, **model_args)
@register_model @register_model
def ecaresnet50d(pretrained=False, **kwargs): def ecaresnet50d(pretrained=False, **kwargs):
"""Constructs a ResNet-50-D model with eca. """Constructs a ResNet-50-D model with eca.

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