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update function name to lower case

pull/701/head
lyuwenyu 2021-04-26 12:30:25 +08:00
parent c31931eb0e
commit 2d874f4b16
1 changed files with 93 additions and 106 deletions
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hubconf.py
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@ -15,20 +15,7 @@
dependencies = ['paddle', 'numpy'] dependencies = ['paddle', 'numpy']
import paddle import paddle
from ppcls.modeling import architectures
from ppcls.modeling.architectures import alexnet as _alexnet
from ppcls.modeling.architectures import vgg as _vgg
from ppcls.modeling.architectures import resnet as _resnet
from ppcls.modeling.architectures import squeezenet as _squeezenet
from ppcls.modeling.architectures import densenet as _densenet
from ppcls.modeling.architectures import inception_v3 as _inception_v3
from ppcls.modeling.architectures import inception_v4 as _inception_v4
from ppcls.modeling.architectures import googlenet as _googlenet
from ppcls.modeling.architectures import shufflenet_v2 as _shufflenet_v2
from ppcls.modeling.architectures import mobilenet_v1 as _mobilenet_v1
from ppcls.modeling.architectures import mobilenet_v2 as _mobilenet_v2
from ppcls.modeling.architectures import mobilenet_v3 as _mobilenet_v3
from ppcls.modeling.architectures import resnext as _resnext
def _load_pretrained_parameters(model, name): def _load_pretrained_parameters(model, name):
@ -39,7 +26,7 @@ def _load_pretrained_parameters(model, name):
return model return model
def AlexNet(pretrained=False, **kwargs): def alexnet(pretrained=False, **kwargs):
""" """
AlexNet AlexNet
Args: Args:
@ -49,14 +36,14 @@ def AlexNet(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `AlexNet` model depends on args. model: nn.Layer. Specific `AlexNet` model depends on args.
""" """
model = _alexnet.AlexNet(**kwargs) model = architectures.AlexNet(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'AlexNet') model = _load_pretrained_parameters(model, 'AlexNet')
return model return model
def VGG11(pretrained=False, **kwargs): def vgg11(pretrained=False, **kwargs):
""" """
VGG11 VGG11
Args: Args:
@ -67,14 +54,14 @@ def VGG11(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `VGG11` model depends on args. model: nn.Layer. Specific `VGG11` model depends on args.
""" """
model = _vgg.VGG11(**kwargs) model = architectures.VGG11(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'VGG11') model = _load_pretrained_parameters(model, 'VGG11')
return model return model
def VGG13(pretrained=False, **kwargs): def vgg13(pretrained=False, **kwargs):
""" """
VGG13 VGG13
Args: Args:
@ -85,14 +72,14 @@ def VGG13(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `VGG13` model depends on args. model: nn.Layer. Specific `VGG13` model depends on args.
""" """
model = _vgg.VGG13(**kwargs) model = architectures.VGG13(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'VGG13') model = _load_pretrained_parameters(model, 'VGG13')
return model return model
def VGG16(pretrained=False, **kwargs): def vgg16(pretrained=False, **kwargs):
""" """
VGG16 VGG16
Args: Args:
@ -103,14 +90,14 @@ def VGG16(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `VGG16` model depends on args. model: nn.Layer. Specific `VGG16` model depends on args.
""" """
model = _vgg.VGG16(**kwargs) model = architectures.VGG16(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'VGG16') model = _load_pretrained_parameters(model, 'VGG16')
return model return model
def VGG19(pretrained=False, **kwargs): def vgg19(pretrained=False, **kwargs):
""" """
VGG19 VGG19
Args: Args:
@ -121,14 +108,14 @@ def VGG19(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `VGG19` model depends on args. model: nn.Layer. Specific `VGG19` model depends on args.
""" """
model = _vgg.VGG19(**kwargs) model = architectures.VGG19(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'VGG19') model = _load_pretrained_parameters(model, 'VGG19')
return model return model
def ResNet18(pretrained=False, **kwargs): def resnet18(pretrained=False, **kwargs):
""" """
ResNet18 ResNet18
Args: Args:
@ -140,14 +127,14 @@ def ResNet18(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNet18` model depends on args. model: nn.Layer. Specific `ResNet18` model depends on args.
""" """
model = _resnet.ResNet18(**kwargs) model = architectures.ResNet18(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNet18') model = _load_pretrained_parameters(model, 'ResNet18')
return model return model
def ResNet34(pretrained=False, **kwargs): def resnet34(pretrained=False, **kwargs):
""" """
ResNet34 ResNet34
Args: Args:
@ -159,14 +146,14 @@ def ResNet34(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNet34` model depends on args. model: nn.Layer. Specific `ResNet34` model depends on args.
""" """
model = _resnet.ResNet34(**kwargs) model = architectures.ResNet34(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNet34') model = _load_pretrained_parameters(model, 'ResNet34')
return model return model
def ResNet50(pretrained=False, **kwargs): def resnet50(pretrained=False, **kwargs):
""" """
ResNet50 ResNet50
Args: Args:
@ -178,14 +165,14 @@ def ResNet50(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNet50` model depends on args. model: nn.Layer. Specific `ResNet50` model depends on args.
""" """
model = _resnet.ResNet50(**kwargs) model = architectures.ResNet50(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNet50') model = _load_pretrained_parameters(model, 'ResNet50')
return model return model
def ResNet101(pretrained=False, **kwargs): def resnet101(pretrained=False, **kwargs):
""" """
ResNet101 ResNet101
Args: Args:
@ -197,14 +184,14 @@ def ResNet101(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNet101` model depends on args. model: nn.Layer. Specific `ResNet101` model depends on args.
""" """
model = _resnet.ResNet101(**kwargs) model = architectures.ResNet101(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNet101') model = _load_pretrained_parameters(model, 'ResNet101')
return model return model
def ResNet152(pretrained=False, **kwargs): def resnet152(pretrained=False, **kwargs):
""" """
ResNet152 ResNet152
Args: Args:
@ -216,14 +203,14 @@ def ResNet152(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNet152` model depends on args. model: nn.Layer. Specific `ResNet152` model depends on args.
""" """
model = _resnet.ResNet152(**kwargs) model = architectures.ResNet152(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNet152') model = _load_pretrained_parameters(model, 'ResNet152')
return model return model
def SqueezeNet1_0(pretrained=False, **kwargs): def squeezenet1_0(pretrained=False, **kwargs):
""" """
SqueezeNet1_0 SqueezeNet1_0
Args: Args:
@ -233,14 +220,14 @@ def SqueezeNet1_0(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `SqueezeNet1_0` model depends on args. model: nn.Layer. Specific `SqueezeNet1_0` model depends on args.
""" """
model = _squeezenet.SqueezeNet1_0(**kwargs) model = architectures.SqueezeNet1_0(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'SqueezeNet1_0') model = _load_pretrained_parameters(model, 'SqueezeNet1_0')
return model return model
def SqueezeNet1_1(pretrained=False, **kwargs): def squeezenet1_1(pretrained=False, **kwargs):
""" """
SqueezeNet1_1 SqueezeNet1_1
Args: Args:
@ -250,14 +237,14 @@ def SqueezeNet1_1(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `SqueezeNet1_1` model depends on args. model: nn.Layer. Specific `SqueezeNet1_1` model depends on args.
""" """
model = _squeezenet.SqueezeNet1_1(**kwargs) model = architectures.SqueezeNet1_1(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'SqueezeNet1_1') model = _load_pretrained_parameters(model, 'SqueezeNet1_1')
return model return model
def DenseNet121(pretrained=False, **kwargs): def densenet121(pretrained=False, **kwargs):
""" """
DenseNet121 DenseNet121
Args: Args:
@ -269,14 +256,14 @@ def DenseNet121(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `DenseNet121` model depends on args. model: nn.Layer. Specific `DenseNet121` model depends on args.
""" """
model = _densenet.DenseNet121(**kwargs) model = architectures.DenseNet121(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'DenseNet121') model = _load_pretrained_parameters(model, 'DenseNet121')
return model return model
def DenseNet161(pretrained=False, **kwargs): def densenet161(pretrained=False, **kwargs):
""" """
DenseNet161 DenseNet161
Args: Args:
@ -288,14 +275,14 @@ def DenseNet161(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `DenseNet161` model depends on args. model: nn.Layer. Specific `DenseNet161` model depends on args.
""" """
model = _densenet.DenseNet161(**kwargs) model = architectures.DenseNet161(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'DenseNet161') model = _load_pretrained_parameters(model, 'DenseNet161')
return model return model
def DenseNet169(pretrained=False, **kwargs): def densenet169(pretrained=False, **kwargs):
""" """
DenseNet169 DenseNet169
Args: Args:
@ -307,14 +294,14 @@ def DenseNet169(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `DenseNet169` model depends on args. model: nn.Layer. Specific `DenseNet169` model depends on args.
""" """
model = _densenet.DenseNet169(**kwargs) model = architectures.DenseNet169(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'DenseNet169') model = _load_pretrained_parameters(model, 'DenseNet169')
return model return model
def DenseNet201(pretrained=False, **kwargs): def densenet201(pretrained=False, **kwargs):
""" """
DenseNet201 DenseNet201
Args: Args:
@ -326,14 +313,14 @@ def DenseNet201(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `DenseNet201` model depends on args. model: nn.Layer. Specific `DenseNet201` model depends on args.
""" """
model = _densenet.DenseNet201(**kwargs) model = architectures.DenseNet201(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'DenseNet201') model = _load_pretrained_parameters(model, 'DenseNet201')
return model return model
def DenseNet264(pretrained=False, **kwargs): def densenet264(pretrained=False, **kwargs):
""" """
DenseNet264 DenseNet264
Args: Args:
@ -345,14 +332,14 @@ def DenseNet264(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `DenseNet264` model depends on args. model: nn.Layer. Specific `DenseNet264` model depends on args.
""" """
model = _densenet.DenseNet264(**kwargs) model = architectures.DenseNet264(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'DenseNet264') model = _load_pretrained_parameters(model, 'DenseNet264')
return model return model
def InceptionV3(pretrained=False, **kwargs): def inceptionv3(pretrained=False, **kwargs):
""" """
InceptionV3 InceptionV3
Args: Args:
@ -362,14 +349,14 @@ def InceptionV3(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `InceptionV3` model depends on args. model: nn.Layer. Specific `InceptionV3` model depends on args.
""" """
model = _inception_v3.InceptionV3(**kwargs) model = architectures.InceptionV3(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'InceptionV3') model = _load_pretrained_parameters(model, 'InceptionV3')
return model return model
def InceptionV4(pretrained=False, **kwargs): def inceptionv4(pretrained=False, **kwargs):
""" """
InceptionV4 InceptionV4
Args: Args:
@ -379,14 +366,14 @@ def InceptionV4(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `InceptionV4` model depends on args. model: nn.Layer. Specific `InceptionV4` model depends on args.
""" """
model = _inception_v4.InceptionV4(**kwargs) model = architectures.InceptionV4(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'InceptionV4') model = _load_pretrained_parameters(model, 'InceptionV4')
return model return model
def GoogLeNet(pretrained=False, **kwargs): def googlenet(pretrained=False, **kwargs):
""" """
GoogLeNet GoogLeNet
Args: Args:
@ -396,14 +383,14 @@ def GoogLeNet(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `GoogLeNet` model depends on args. model: nn.Layer. Specific `GoogLeNet` model depends on args.
""" """
model = _googlenet.GoogLeNet(**kwargs) model = architectures.GoogLeNet(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'GoogLeNet') model = _load_pretrained_parameters(model, 'GoogLeNet')
return model return model
def ShuffleNetV2_x0_25(pretrained=False, **kwargs): def shufflenetv2_x0_25(pretrained=False, **kwargs):
""" """
ShuffleNetV2_x0_25 ShuffleNetV2_x0_25
Args: Args:
@ -413,14 +400,14 @@ def ShuffleNetV2_x0_25(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ShuffleNetV2_x0_25` model depends on args. model: nn.Layer. Specific `ShuffleNetV2_x0_25` model depends on args.
""" """
model = _shufflenet_v2.ShuffleNetV2_x0_25(**kwargs) model = architectures.ShuffleNetV2_x0_25(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ShuffleNetV2_x0_25') model = _load_pretrained_parameters(model, 'ShuffleNetV2_x0_25')
return model return model
def MobileNetV1(pretrained=False, **kwargs): def mobilenetv1(pretrained=False, **kwargs):
""" """
MobileNetV1 MobileNetV1
Args: Args:
@ -430,14 +417,14 @@ def MobileNetV1(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV1` model depends on args. model: nn.Layer. Specific `MobileNetV1` model depends on args.
""" """
model = _mobilenet_v1.MobileNetV1(**kwargs) model = architectures.MobileNetV1(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV1') model = _load_pretrained_parameters(model, 'MobileNetV1')
return model return model
def MobileNetV1_x0_25(pretrained=False, **kwargs): def mobilenetv1_x0_25(pretrained=False, **kwargs):
""" """
MobileNetV1_x0_25 MobileNetV1_x0_25
Args: Args:
@ -447,14 +434,14 @@ def MobileNetV1_x0_25(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV1_x0_25` model depends on args. model: nn.Layer. Specific `MobileNetV1_x0_25` model depends on args.
""" """
model = _mobilenet_v1.MobileNetV1_x0_25(**kwargs) model = architectures.MobileNetV1_x0_25(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV1_x0_25') model = _load_pretrained_parameters(model, 'MobileNetV1_x0_25')
return model return model
def MobileNetV1_x0_5(pretrained=False, **kwargs): def mobilenetv1_x0_5(pretrained=False, **kwargs):
""" """
MobileNetV1_x0_5 MobileNetV1_x0_5
Args: Args:
@ -464,14 +451,14 @@ def MobileNetV1_x0_5(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV1_x0_5` model depends on args. model: nn.Layer. Specific `MobileNetV1_x0_5` model depends on args.
""" """
model = _mobilenet_v1.MobileNetV1_x0_5(**kwargs) model = architectures.MobileNetV1_x0_5(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV1_x0_5') model = _load_pretrained_parameters(model, 'MobileNetV1_x0_5')
return model return model
def MobileNetV1_x0_75(pretrained=False, **kwargs): def mobilenetv1_x0_75(pretrained=False, **kwargs):
""" """
MobileNetV1_x0_75 MobileNetV1_x0_75
Args: Args:
@ -481,14 +468,14 @@ def MobileNetV1_x0_75(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV1_x0_75` model depends on args. model: nn.Layer. Specific `MobileNetV1_x0_75` model depends on args.
""" """
model = _mobilenet_v1.MobileNetV1_x0_75(**kwargs) model = architectures.MobileNetV1_x0_75(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV1_x0_75') model = _load_pretrained_parameters(model, 'MobileNetV1_x0_75')
return model return model
def MobileNetV2_x0_25(pretrained=False, **kwargs): def mobilenetv2_x0_25(pretrained=False, **kwargs):
""" """
MobileNetV2_x0_25 MobileNetV2_x0_25
Args: Args:
@ -498,14 +485,14 @@ def MobileNetV2_x0_25(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV2_x0_25` model depends on args. model: nn.Layer. Specific `MobileNetV2_x0_25` model depends on args.
""" """
model = _mobilenet_v2.MobileNetV2_x0_25(**kwargs) model = architectures.MobileNetV2_x0_25(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV2_x0_25') model = _load_pretrained_parameters(model, 'MobileNetV2_x0_25')
return model return model
def MobileNetV2_x0_5(pretrained=False, **kwargs): def mobilenetv2_x0_5(pretrained=False, **kwargs):
""" """
MobileNetV2_x0_5 MobileNetV2_x0_5
Args: Args:
@ -515,14 +502,14 @@ def MobileNetV2_x0_5(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV2_x0_5` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV2_x0_5') model = _load_pretrained_parameters(model, 'MobileNetV2_x0_5')
return model return model
def MobileNetV2_x0_75(pretrained=False, **kwargs): def mobilenetv2_x0_75(pretrained=False, **kwargs):
""" """
MobileNetV2_x0_75 MobileNetV2_x0_75
Args: Args:
@ -532,14 +519,14 @@ def MobileNetV2_x0_75(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV2_x0_75` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV2_x0_75') model = _load_pretrained_parameters(model, 'MobileNetV2_x0_75')
return model return model
def MobileNetV2_x1_5(pretrained=False, **kwargs): def mobilenetv2_x1_5(pretrained=False, **kwargs):
""" """
MobileNetV2_x1_5 MobileNetV2_x1_5
Args: Args:
@ -549,14 +536,14 @@ def MobileNetV2_x1_5(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV2_x1_5` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV2_x1_5') model = _load_pretrained_parameters(model, 'MobileNetV2_x1_5')
return model return model
def MobileNetV2_x2_0(pretrained=False, **kwargs): def mobilenetv2_x2_0(pretrained=False, **kwargs):
""" """
MobileNetV2_x2_0 MobileNetV2_x2_0
Args: Args:
@ -566,14 +553,14 @@ def MobileNetV2_x2_0(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV2_x2_0` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV2_x2_0') model = _load_pretrained_parameters(model, 'MobileNetV2_x2_0')
return model return model
def MobileNetV3_large_x0_35(pretrained=False, **kwargs): def mobilenetv3_large_x0_35(pretrained=False, **kwargs):
""" """
MobileNetV3_large_x0_35 MobileNetV3_large_x0_35
Args: Args:
@ -583,14 +570,14 @@ def MobileNetV3_large_x0_35(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_large_x0_35` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_35') model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_35')
return model return model
def MobileNetV3_large_x0_5(pretrained=False, **kwargs): def mobilenetv3_large_x0_5(pretrained=False, **kwargs):
""" """
MobileNetV3_large_x0_5 MobileNetV3_large_x0_5
Args: Args:
@ -600,14 +587,14 @@ def MobileNetV3_large_x0_5(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_large_x0_5` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_5') model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_5')
return model return model
def MobileNetV3_large_x0_75(pretrained=False, **kwargs): def mobilenetv3_large_x0_75(pretrained=False, **kwargs):
""" """
MobileNetV3_large_x0_75 MobileNetV3_large_x0_75
Args: Args:
@ -617,14 +604,14 @@ def MobileNetV3_large_x0_75(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_large_x0_75` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_75') model = _load_pretrained_parameters(model, 'MobileNetV3_large_x0_75')
return model return model
def MobileNetV3_large_x1_0(pretrained=False, **kwargs): def mobilenetv3_large_x1_0(pretrained=False, **kwargs):
""" """
MobileNetV3_large_x1_0 MobileNetV3_large_x1_0
Args: Args:
@ -634,14 +621,14 @@ def MobileNetV3_large_x1_0(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_large_x1_0` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x1_0') model = _load_pretrained_parameters(model, 'MobileNetV3_large_x1_0')
return model return model
def MobileNetV3_large_x1_25(pretrained=False, **kwargs): def mobilenetv3_large_x1_25(pretrained=False, **kwargs):
""" """
MobileNetV3_large_x1_25 MobileNetV3_large_x1_25
Args: Args:
@ -651,14 +638,14 @@ def MobileNetV3_large_x1_25(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_large_x1_25` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_large_x1_25') model = _load_pretrained_parameters(model, 'MobileNetV3_large_x1_25')
return model return model
def MobileNetV3_small_x0_35(pretrained=False, **kwargs): def mobilenetv3_small_x0_35(pretrained=False, **kwargs):
""" """
MobileNetV3_small_x0_35 MobileNetV3_small_x0_35
Args: Args:
@ -668,14 +655,14 @@ def MobileNetV3_small_x0_35(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_small_x0_35` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_35') model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_35')
return model return model
def MobileNetV3_small_x0_5(pretrained=False, **kwargs): def mobilenetv3_small_x0_5(pretrained=False, **kwargs):
""" """
MobileNetV3_small_x0_5 MobileNetV3_small_x0_5
Args: Args:
@ -685,14 +672,14 @@ def MobileNetV3_small_x0_5(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_small_x0_5` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_5') model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_5')
return model return model
def MobileNetV3_small_x0_75(pretrained=False, **kwargs): def mobilenetv3_small_x0_75(pretrained=False, **kwargs):
""" """
MobileNetV3_small_x0_75 MobileNetV3_small_x0_75
Args: Args:
@ -702,14 +689,14 @@ def MobileNetV3_small_x0_75(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_small_x0_75` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_75') model = _load_pretrained_parameters(model, 'MobileNetV3_small_x0_75')
return model return model
def MobileNetV3_small_x1_0(pretrained=False, **kwargs): def mobilenetv3_small_x1_0(pretrained=False, **kwargs):
""" """
MobileNetV3_small_x1_0 MobileNetV3_small_x1_0
Args: Args:
@ -719,14 +706,14 @@ def MobileNetV3_small_x1_0(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_small_x1_0` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x1_0') model = _load_pretrained_parameters(model, 'MobileNetV3_small_x1_0')
return model return model
def MobileNetV3_small_x1_25(pretrained=False, **kwargs): def mobilenetv3_small_x1_25(pretrained=False, **kwargs):
""" """
MobileNetV3_small_x1_25 MobileNetV3_small_x1_25
Args: Args:
@ -736,14 +723,14 @@ def MobileNetV3_small_x1_25(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `MobileNetV3_small_x1_25` model depends on args. 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: if pretrained:
model = _load_pretrained_parameters(model, 'MobileNetV3_small_x1_25') model = _load_pretrained_parameters(model, 'MobileNetV3_small_x1_25')
return model return model
def ResNeXt101_32x4d(pretrained=False, **kwargs): def resnext101_32x4d(pretrained=False, **kwargs):
""" """
ResNeXt101_32x4d ResNeXt101_32x4d
Args: Args:
@ -753,14 +740,14 @@ def ResNeXt101_32x4d(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNeXt101_32x4d` model depends on args. model: nn.Layer. Specific `ResNeXt101_32x4d` model depends on args.
""" """
model = _resnext.ResNeXt101_32x4d(**kwargs) model = architectures.ResNeXt101_32x4d(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNeXt101_32x4d') model = _load_pretrained_parameters(model, 'ResNeXt101_32x4d')
return model return model
def ResNeXt101_64x4d(pretrained=False, **kwargs): def resnext101_64x4d(pretrained=False, **kwargs):
""" """
ResNeXt101_64x4d ResNeXt101_64x4d
Args: Args:
@ -770,14 +757,14 @@ def ResNeXt101_64x4d(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNeXt101_64x4d` model depends on args. model: nn.Layer. Specific `ResNeXt101_64x4d` model depends on args.
""" """
model = _resnext.ResNeXt101_64x4d(**kwargs) model = architectures.ResNeXt101_64x4d(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNeXt101_64x4d') model = _load_pretrained_parameters(model, 'ResNeXt101_64x4d')
return model return model
def ResNeXt152_32x4d(pretrained=False, **kwargs): def resnext152_32x4d(pretrained=False, **kwargs):
""" """
ResNeXt152_32x4d ResNeXt152_32x4d
Args: Args:
@ -787,14 +774,14 @@ def ResNeXt152_32x4d(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNeXt152_32x4d` model depends on args. model: nn.Layer. Specific `ResNeXt152_32x4d` model depends on args.
""" """
model = _resnext.ResNeXt152_32x4d(**kwargs) model = architectures.ResNeXt152_32x4d(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNeXt152_32x4d') model = _load_pretrained_parameters(model, 'ResNeXt152_32x4d')
return model return model
def ResNeXt152_64x4d(pretrained=False, **kwargs): def resnext152_64x4d(pretrained=False, **kwargs):
""" """
ResNeXt152_64x4d ResNeXt152_64x4d
Args: Args:
@ -804,14 +791,14 @@ def ResNeXt152_64x4d(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNeXt152_64x4d` model depends on args. model: nn.Layer. Specific `ResNeXt152_64x4d` model depends on args.
""" """
model = _resnext.ResNeXt152_64x4d(**kwargs) model = architectures.ResNeXt152_64x4d(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNeXt152_64x4d') model = _load_pretrained_parameters(model, 'ResNeXt152_64x4d')
return model return model
def ResNeXt50_32x4d(pretrained=False, **kwargs): def resnext50_32x4d(pretrained=False, **kwargs):
""" """
ResNeXt50_32x4d ResNeXt50_32x4d
Args: Args:
@ -821,14 +808,14 @@ def ResNeXt50_32x4d(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNeXt50_32x4d` model depends on args. model: nn.Layer. Specific `ResNeXt50_32x4d` model depends on args.
""" """
model = _resnext.ResNeXt50_32x4d(**kwargs) model = architectures.ResNeXt50_32x4d(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNeXt50_32x4d') model = _load_pretrained_parameters(model, 'ResNeXt50_32x4d')
return model return model
def ResNeXt50_64x4d(pretrained=False, **kwargs): def resnext50_64x4d(pretrained=False, **kwargs):
""" """
ResNeXt50_64x4d ResNeXt50_64x4d
Args: Args:
@ -838,7 +825,7 @@ def ResNeXt50_64x4d(pretrained=False, **kwargs):
Returns: Returns:
model: nn.Layer. Specific `ResNeXt50_64x4d` model depends on args. model: nn.Layer. Specific `ResNeXt50_64x4d` model depends on args.
""" """
model = _resnext.ResNeXt50_64x4d(**kwargs) model = architectures.ResNeXt50_64x4d(**kwargs)
if pretrained: if pretrained:
model = _load_pretrained_parameters(model, 'ResNeXt50_64x4d') model = _load_pretrained_parameters(model, 'ResNeXt50_64x4d')