update function name to lower case
parent
c31931eb0e
commit
2d874f4b16
199
hubconf.py
199
hubconf.py
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@ -15,20 +15,7 @@
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dependencies = ['paddle', 'numpy']
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import paddle
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from ppcls.modeling.architectures import alexnet as _alexnet
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from ppcls.modeling.architectures import vgg as _vgg
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from ppcls.modeling.architectures import resnet as _resnet
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from ppcls.modeling.architectures import squeezenet as _squeezenet
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from ppcls.modeling.architectures import densenet as _densenet
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from ppcls.modeling.architectures import inception_v3 as _inception_v3
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from ppcls.modeling.architectures import inception_v4 as _inception_v4
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from ppcls.modeling.architectures import googlenet as _googlenet
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from ppcls.modeling.architectures import shufflenet_v2 as _shufflenet_v2
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from ppcls.modeling.architectures import mobilenet_v1 as _mobilenet_v1
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from ppcls.modeling.architectures import mobilenet_v2 as _mobilenet_v2
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from ppcls.modeling.architectures import mobilenet_v3 as _mobilenet_v3
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from ppcls.modeling.architectures import resnext as _resnext
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from ppcls.modeling import architectures
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def _load_pretrained_parameters(model, name):
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@ -39,7 +26,7 @@ def _load_pretrained_parameters(model, name):
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return model
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def AlexNet(pretrained=False, **kwargs):
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def alexnet(pretrained=False, **kwargs):
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"""
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AlexNet
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Args:
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@ -49,14 +36,14 @@ def AlexNet(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `AlexNet` model depends on args.
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"""
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model = _alexnet.AlexNet(**kwargs)
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model = architectures.AlexNet(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'AlexNet')
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return model
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def VGG11(pretrained=False, **kwargs):
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def vgg11(pretrained=False, **kwargs):
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"""
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VGG11
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Args:
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@ -67,14 +54,14 @@ def VGG11(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `VGG11` model depends on args.
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"""
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model = _vgg.VGG11(**kwargs)
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model = architectures.VGG11(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'VGG11')
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return model
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def VGG13(pretrained=False, **kwargs):
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def vgg13(pretrained=False, **kwargs):
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"""
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VGG13
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Args:
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@ -85,14 +72,14 @@ def VGG13(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `VGG13` model depends on args.
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"""
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model = _vgg.VGG13(**kwargs)
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model = architectures.VGG13(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'VGG13')
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return model
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def VGG16(pretrained=False, **kwargs):
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def vgg16(pretrained=False, **kwargs):
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"""
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VGG16
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Args:
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@ -103,14 +90,14 @@ def VGG16(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `VGG16` model depends on args.
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"""
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model = _vgg.VGG16(**kwargs)
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model = architectures.VGG16(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'VGG16')
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return model
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def VGG19(pretrained=False, **kwargs):
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def vgg19(pretrained=False, **kwargs):
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"""
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VGG19
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Args:
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@ -121,14 +108,14 @@ def VGG19(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `VGG19` model depends on args.
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"""
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model = _vgg.VGG19(**kwargs)
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model = architectures.VGG19(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'VGG19')
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return model
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def ResNet18(pretrained=False, **kwargs):
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def resnet18(pretrained=False, **kwargs):
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"""
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ResNet18
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Args:
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@ -140,14 +127,14 @@ def ResNet18(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `ResNet18` model depends on args.
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"""
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model = _resnet.ResNet18(**kwargs)
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model = architectures.ResNet18(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'ResNet18')
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return model
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def ResNet34(pretrained=False, **kwargs):
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def resnet34(pretrained=False, **kwargs):
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"""
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ResNet34
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Args:
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@ -159,14 +146,14 @@ def ResNet34(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `ResNet34` model depends on args.
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"""
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model = _resnet.ResNet34(**kwargs)
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model = architectures.ResNet34(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'ResNet34')
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return model
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def ResNet50(pretrained=False, **kwargs):
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def resnet50(pretrained=False, **kwargs):
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"""
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ResNet50
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Args:
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@ -178,14 +165,14 @@ def ResNet50(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `ResNet50` model depends on args.
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"""
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model = _resnet.ResNet50(**kwargs)
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model = architectures.ResNet50(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'ResNet50')
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return model
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def ResNet101(pretrained=False, **kwargs):
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def resnet101(pretrained=False, **kwargs):
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"""
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ResNet101
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Args:
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@ -197,14 +184,14 @@ def ResNet101(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `ResNet101` model depends on args.
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"""
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model = _resnet.ResNet101(**kwargs)
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model = architectures.ResNet101(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'ResNet101')
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return model
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def ResNet152(pretrained=False, **kwargs):
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def resnet152(pretrained=False, **kwargs):
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"""
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ResNet152
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Args:
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@ -216,14 +203,14 @@ def ResNet152(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `ResNet152` model depends on args.
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"""
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model = _resnet.ResNet152(**kwargs)
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model = architectures.ResNet152(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'ResNet152')
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return model
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def SqueezeNet1_0(pretrained=False, **kwargs):
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def squeezenet1_0(pretrained=False, **kwargs):
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"""
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SqueezeNet1_0
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Args:
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@ -233,14 +220,14 @@ def SqueezeNet1_0(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `SqueezeNet1_0` model depends on args.
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"""
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model = _squeezenet.SqueezeNet1_0(**kwargs)
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model = architectures.SqueezeNet1_0(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'SqueezeNet1_0')
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return model
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def SqueezeNet1_1(pretrained=False, **kwargs):
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def squeezenet1_1(pretrained=False, **kwargs):
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"""
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SqueezeNet1_1
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Args:
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@ -250,14 +237,14 @@ def SqueezeNet1_1(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `SqueezeNet1_1` model depends on args.
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"""
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model = _squeezenet.SqueezeNet1_1(**kwargs)
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model = architectures.SqueezeNet1_1(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'SqueezeNet1_1')
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return model
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def DenseNet121(pretrained=False, **kwargs):
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def densenet121(pretrained=False, **kwargs):
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"""
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DenseNet121
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Args:
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@ -269,14 +256,14 @@ def DenseNet121(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `DenseNet121` model depends on args.
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"""
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model = _densenet.DenseNet121(**kwargs)
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model = architectures.DenseNet121(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'DenseNet121')
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return model
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def DenseNet161(pretrained=False, **kwargs):
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def densenet161(pretrained=False, **kwargs):
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"""
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DenseNet161
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Args:
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@ -288,14 +275,14 @@ def DenseNet161(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `DenseNet161` model depends on args.
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"""
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model = _densenet.DenseNet161(**kwargs)
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model = architectures.DenseNet161(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'DenseNet161')
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return model
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def DenseNet169(pretrained=False, **kwargs):
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def densenet169(pretrained=False, **kwargs):
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"""
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DenseNet169
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Args:
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@ -307,14 +294,14 @@ def DenseNet169(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `DenseNet169` model depends on args.
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"""
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model = _densenet.DenseNet169(**kwargs)
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model = architectures.DenseNet169(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'DenseNet169')
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return model
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def DenseNet201(pretrained=False, **kwargs):
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def densenet201(pretrained=False, **kwargs):
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"""
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DenseNet201
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Args:
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@ -326,14 +313,14 @@ def DenseNet201(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `DenseNet201` model depends on args.
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"""
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model = _densenet.DenseNet201(**kwargs)
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model = architectures.DenseNet201(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'DenseNet201')
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return model
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def DenseNet264(pretrained=False, **kwargs):
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def densenet264(pretrained=False, **kwargs):
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"""
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DenseNet264
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Args:
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@ -345,14 +332,14 @@ def DenseNet264(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `DenseNet264` model depends on args.
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"""
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model = _densenet.DenseNet264(**kwargs)
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model = architectures.DenseNet264(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'DenseNet264')
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return model
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def InceptionV3(pretrained=False, **kwargs):
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def inceptionv3(pretrained=False, **kwargs):
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"""
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InceptionV3
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Args:
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@ -362,14 +349,14 @@ def InceptionV3(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `InceptionV3` model depends on args.
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"""
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model = _inception_v3.InceptionV3(**kwargs)
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model = architectures.InceptionV3(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'InceptionV3')
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return model
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def InceptionV4(pretrained=False, **kwargs):
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def inceptionv4(pretrained=False, **kwargs):
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"""
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InceptionV4
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Args:
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@ -379,14 +366,14 @@ def InceptionV4(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `InceptionV4` model depends on args.
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"""
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model = _inception_v4.InceptionV4(**kwargs)
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model = architectures.InceptionV4(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'InceptionV4')
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return model
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def GoogLeNet(pretrained=False, **kwargs):
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def googlenet(pretrained=False, **kwargs):
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"""
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GoogLeNet
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Args:
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@ -396,14 +383,14 @@ def GoogLeNet(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `GoogLeNet` model depends on args.
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"""
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model = _googlenet.GoogLeNet(**kwargs)
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model = architectures.GoogLeNet(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'GoogLeNet')
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return model
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def ShuffleNetV2_x0_25(pretrained=False, **kwargs):
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def shufflenetv2_x0_25(pretrained=False, **kwargs):
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"""
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ShuffleNetV2_x0_25
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Args:
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@ -413,14 +400,14 @@ def ShuffleNetV2_x0_25(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `ShuffleNetV2_x0_25` model depends on args.
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"""
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model = _shufflenet_v2.ShuffleNetV2_x0_25(**kwargs)
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model = architectures.ShuffleNetV2_x0_25(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'ShuffleNetV2_x0_25')
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return model
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def MobileNetV1(pretrained=False, **kwargs):
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def mobilenetv1(pretrained=False, **kwargs):
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"""
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MobileNetV1
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Args:
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@ -430,14 +417,14 @@ def MobileNetV1(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `MobileNetV1` model depends on args.
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"""
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model = _mobilenet_v1.MobileNetV1(**kwargs)
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model = architectures.MobileNetV1(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'MobileNetV1')
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return model
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def MobileNetV1_x0_25(pretrained=False, **kwargs):
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def mobilenetv1_x0_25(pretrained=False, **kwargs):
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"""
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MobileNetV1_x0_25
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Args:
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@ -447,14 +434,14 @@ def MobileNetV1_x0_25(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `MobileNetV1_x0_25` model depends on args.
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"""
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model = _mobilenet_v1.MobileNetV1_x0_25(**kwargs)
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model = architectures.MobileNetV1_x0_25(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'MobileNetV1_x0_25')
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return model
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def MobileNetV1_x0_5(pretrained=False, **kwargs):
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def mobilenetv1_x0_5(pretrained=False, **kwargs):
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"""
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MobileNetV1_x0_5
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Args:
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@ -464,14 +451,14 @@ def MobileNetV1_x0_5(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `MobileNetV1_x0_5` model depends on args.
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"""
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model = _mobilenet_v1.MobileNetV1_x0_5(**kwargs)
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model = architectures.MobileNetV1_x0_5(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'MobileNetV1_x0_5')
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return model
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def MobileNetV1_x0_75(pretrained=False, **kwargs):
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def mobilenetv1_x0_75(pretrained=False, **kwargs):
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"""
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MobileNetV1_x0_75
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Args:
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@ -481,14 +468,14 @@ def MobileNetV1_x0_75(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `MobileNetV1_x0_75` model depends on args.
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"""
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model = _mobilenet_v1.MobileNetV1_x0_75(**kwargs)
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model = architectures.MobileNetV1_x0_75(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'MobileNetV1_x0_75')
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return model
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def MobileNetV2_x0_25(pretrained=False, **kwargs):
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def mobilenetv2_x0_25(pretrained=False, **kwargs):
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"""
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MobileNetV2_x0_25
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Args:
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@ -498,14 +485,14 @@ def MobileNetV2_x0_25(pretrained=False, **kwargs):
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Returns:
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model: nn.Layer. Specific `MobileNetV2_x0_25` model depends on args.
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"""
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model = _mobilenet_v2.MobileNetV2_x0_25(**kwargs)
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model = architectures.MobileNetV2_x0_25(**kwargs)
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if pretrained:
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model = _load_pretrained_parameters(model, 'MobileNetV2_x0_25')
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return model
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def MobileNetV2_x0_5(pretrained=False, **kwargs):
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def mobilenetv2_x0_5(pretrained=False, **kwargs):
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"""
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MobileNetV2_x0_5
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Args:
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@ -515,14 +502,14 @@ def MobileNetV2_x0_5(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV2_x0_5` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v2.MobileNetV2_x0_5(**kwargs)
|
||||
model = architectures.MobileNetV2_x0_5(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV2_x0_5')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV2_x0_75(pretrained=False, **kwargs):
|
||||
def mobilenetv2_x0_75(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV2_x0_75
|
||||
Args:
|
||||
|
@ -532,14 +519,14 @@ def MobileNetV2_x0_75(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV2_x0_75` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v2.MobileNetV2_x0_75(**kwargs)
|
||||
model = architectures.MobileNetV2_x0_75(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV2_x0_75')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV2_x1_5(pretrained=False, **kwargs):
|
||||
def mobilenetv2_x1_5(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV2_x1_5
|
||||
Args:
|
||||
|
@ -549,14 +536,14 @@ def MobileNetV2_x1_5(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV2_x1_5` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v2.MobileNetV2_x1_5(**kwargs)
|
||||
model = architectures.MobileNetV2_x1_5(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV2_x1_5')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV2_x2_0(pretrained=False, **kwargs):
|
||||
def mobilenetv2_x2_0(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV2_x2_0
|
||||
Args:
|
||||
|
@ -566,14 +553,14 @@ def MobileNetV2_x2_0(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV2_x2_0` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v2.MobileNetV2_x2_0(**kwargs)
|
||||
model = architectures.MobileNetV2_x2_0(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV2_x2_0')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_large_x0_35(pretrained=False, **kwargs):
|
||||
def mobilenetv3_large_x0_35(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_large_x0_35
|
||||
Args:
|
||||
|
@ -583,14 +570,14 @@ def MobileNetV3_large_x0_35(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_large_x0_35` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_large_x0_35(**kwargs)
|
||||
model = architectures.MobileNetV3_large_x0_35(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_35')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_large_x0_5(pretrained=False, **kwargs):
|
||||
def mobilenetv3_large_x0_5(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_large_x0_5
|
||||
Args:
|
||||
|
@ -600,14 +587,14 @@ def MobileNetV3_large_x0_5(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_large_x0_5` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_large_x0_5(**kwargs)
|
||||
model = architectures.MobileNetV3_large_x0_5(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_5')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_large_x0_75(pretrained=False, **kwargs):
|
||||
def mobilenetv3_large_x0_75(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_large_x0_75
|
||||
Args:
|
||||
|
@ -617,14 +604,14 @@ def MobileNetV3_large_x0_75(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_large_x0_75` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_large_x0_75(**kwargs)
|
||||
model = architectures.MobileNetV3_large_x0_75(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_75')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_large_x1_0(pretrained=False, **kwargs):
|
||||
def mobilenetv3_large_x1_0(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_large_x1_0
|
||||
Args:
|
||||
|
@ -634,14 +621,14 @@ def MobileNetV3_large_x1_0(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_large_x1_0` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_large_x1_0(**kwargs)
|
||||
model = architectures.MobileNetV3_large_x1_0(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x1_0')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_large_x1_25(pretrained=False, **kwargs):
|
||||
def mobilenetv3_large_x1_25(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_large_x1_25
|
||||
Args:
|
||||
|
@ -651,14 +638,14 @@ def MobileNetV3_large_x1_25(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_large_x1_25` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_large_x1_25(**kwargs)
|
||||
model = architectures.MobileNetV3_large_x1_25(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x1_25')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_small_x0_35(pretrained=False, **kwargs):
|
||||
def mobilenetv3_small_x0_35(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_small_x0_35
|
||||
Args:
|
||||
|
@ -668,14 +655,14 @@ def MobileNetV3_small_x0_35(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_small_x0_35` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_small_x0_35(**kwargs)
|
||||
model = architectures.MobileNetV3_small_x0_35(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_35')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_small_x0_5(pretrained=False, **kwargs):
|
||||
def mobilenetv3_small_x0_5(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_small_x0_5
|
||||
Args:
|
||||
|
@ -685,14 +672,14 @@ def MobileNetV3_small_x0_5(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_small_x0_5` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_small_x0_5(**kwargs)
|
||||
model = architectures.MobileNetV3_small_x0_5(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_5')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_small_x0_75(pretrained=False, **kwargs):
|
||||
def mobilenetv3_small_x0_75(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_small_x0_75
|
||||
Args:
|
||||
|
@ -702,14 +689,14 @@ def MobileNetV3_small_x0_75(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_small_x0_75` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_small_x0_75(**kwargs)
|
||||
model = architectures.MobileNetV3_small_x0_75(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_75')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_small_x1_0(pretrained=False, **kwargs):
|
||||
def mobilenetv3_small_x1_0(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_small_x1_0
|
||||
Args:
|
||||
|
@ -719,14 +706,14 @@ def MobileNetV3_small_x1_0(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_small_x1_0` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_small_x1_0(**kwargs)
|
||||
model = architectures.MobileNetV3_small_x1_0(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x1_0')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def MobileNetV3_small_x1_25(pretrained=False, **kwargs):
|
||||
def mobilenetv3_small_x1_25(pretrained=False, **kwargs):
|
||||
"""
|
||||
MobileNetV3_small_x1_25
|
||||
Args:
|
||||
|
@ -736,14 +723,14 @@ def MobileNetV3_small_x1_25(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `MobileNetV3_small_x1_25` model depends on args.
|
||||
"""
|
||||
model = _mobilenet_v3.MobileNetV3_small_x1_25(**kwargs)
|
||||
model = architectures.MobileNetV3_small_x1_25(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x1_25')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def ResNeXt101_32x4d(pretrained=False, **kwargs):
|
||||
def resnext101_32x4d(pretrained=False, **kwargs):
|
||||
"""
|
||||
ResNeXt101_32x4d
|
||||
Args:
|
||||
|
@ -753,14 +740,14 @@ def ResNeXt101_32x4d(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `ResNeXt101_32x4d` model depends on args.
|
||||
"""
|
||||
model = _resnext.ResNeXt101_32x4d(**kwargs)
|
||||
model = architectures.ResNeXt101_32x4d(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'ResNeXt101_32x4d')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def ResNeXt101_64x4d(pretrained=False, **kwargs):
|
||||
def resnext101_64x4d(pretrained=False, **kwargs):
|
||||
"""
|
||||
ResNeXt101_64x4d
|
||||
Args:
|
||||
|
@ -770,14 +757,14 @@ def ResNeXt101_64x4d(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `ResNeXt101_64x4d` model depends on args.
|
||||
"""
|
||||
model = _resnext.ResNeXt101_64x4d(**kwargs)
|
||||
model = architectures.ResNeXt101_64x4d(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'ResNeXt101_64x4d')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def ResNeXt152_32x4d(pretrained=False, **kwargs):
|
||||
def resnext152_32x4d(pretrained=False, **kwargs):
|
||||
"""
|
||||
ResNeXt152_32x4d
|
||||
Args:
|
||||
|
@ -787,14 +774,14 @@ def ResNeXt152_32x4d(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `ResNeXt152_32x4d` model depends on args.
|
||||
"""
|
||||
model = _resnext.ResNeXt152_32x4d(**kwargs)
|
||||
model = architectures.ResNeXt152_32x4d(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'ResNeXt152_32x4d')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def ResNeXt152_64x4d(pretrained=False, **kwargs):
|
||||
def resnext152_64x4d(pretrained=False, **kwargs):
|
||||
"""
|
||||
ResNeXt152_64x4d
|
||||
Args:
|
||||
|
@ -804,14 +791,14 @@ def ResNeXt152_64x4d(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `ResNeXt152_64x4d` model depends on args.
|
||||
"""
|
||||
model = _resnext.ResNeXt152_64x4d(**kwargs)
|
||||
model = architectures.ResNeXt152_64x4d(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'ResNeXt152_64x4d')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def ResNeXt50_32x4d(pretrained=False, **kwargs):
|
||||
def resnext50_32x4d(pretrained=False, **kwargs):
|
||||
"""
|
||||
ResNeXt50_32x4d
|
||||
Args:
|
||||
|
@ -821,14 +808,14 @@ def ResNeXt50_32x4d(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `ResNeXt50_32x4d` model depends on args.
|
||||
"""
|
||||
model = _resnext.ResNeXt50_32x4d(**kwargs)
|
||||
model = architectures.ResNeXt50_32x4d(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'ResNeXt50_32x4d')
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def ResNeXt50_64x4d(pretrained=False, **kwargs):
|
||||
def resnext50_64x4d(pretrained=False, **kwargs):
|
||||
"""
|
||||
ResNeXt50_64x4d
|
||||
Args:
|
||||
|
@ -838,7 +825,7 @@ def ResNeXt50_64x4d(pretrained=False, **kwargs):
|
|||
Returns:
|
||||
model: nn.Layer. Specific `ResNeXt50_64x4d` model depends on args.
|
||||
"""
|
||||
model = _resnext.ResNeXt50_64x4d(**kwargs)
|
||||
model = architectures.ResNeXt50_64x4d(**kwargs)
|
||||
if pretrained:
|
||||
model = _load_pretrained_parameters(model, 'ResNeXt50_64x4d')
|
||||
|
||||
|
|
Loading…
Reference in New Issue