diff --git a/hubconf.py b/hubconf.py index eb114bc20d0b7954ec5b8fd3206cfffe5ef0407b..b7f76745ae0654ea41c0cdc2ac2087e4797eb241 100644 --- a/hubconf.py +++ b/hubconf.py @@ -41,10 +41,15 @@ class _SysPathG(object): self.path) -with _SysPathG( - os.path.join( - os.path.dirname(os.path.abspath(__file__)), 'ppcls', 'arch')): - import backbone +with _SysPathG(os.path.dirname(os.path.abspath(__file__)), ): + import ppcls + import ppcls.arch.backbone as backbone + + def ppclas_init(): + if ppcls.utils.logger._logger is None: + ppcls.utils.logger.init_logger() + + ppclas_init() def _load_pretrained_parameters(model, name): url = 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/{}_pretrained.pdparams'.format( @@ -63,9 +68,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `AlexNet` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.AlexNet(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'AlexNet') return model @@ -80,9 +84,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `VGG11` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.VGG11(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'VGG11') return model @@ -97,9 +100,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `VGG13` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.VGG13(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'VGG13') return model @@ -114,9 +116,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `VGG16` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.VGG16(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'VGG16') return model @@ -131,9 +132,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `VGG19` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.VGG19(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'VGG19') return model @@ -149,9 +149,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNet18` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNet18(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNet18') return model @@ -167,9 +166,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNet34` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNet34(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNet34') return model @@ -185,9 +183,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNet50` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNet50(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNet50') return model @@ -203,9 +200,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNet101` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNet101(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNet101') return model @@ -221,9 +217,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNet152` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNet152(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNet152') return model @@ -237,9 +232,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `SqueezeNet1_0` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.SqueezeNet1_0(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'SqueezeNet1_0') return model @@ -253,9 +247,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `SqueezeNet1_1` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.SqueezeNet1_1(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'SqueezeNet1_1') return model @@ -271,9 +264,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `DenseNet121` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.DenseNet121(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'DenseNet121') return model @@ -289,9 +281,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `DenseNet161` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.DenseNet161(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'DenseNet161') return model @@ -307,9 +298,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `DenseNet169` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.DenseNet169(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'DenseNet169') return model @@ -325,9 +315,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `DenseNet201` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.DenseNet201(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'DenseNet201') return model @@ -343,9 +332,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `DenseNet264` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.DenseNet264(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'DenseNet264') return model @@ -359,9 +347,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `InceptionV3` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.InceptionV3(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'InceptionV3') return model @@ -375,9 +362,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `InceptionV4` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.InceptionV4(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'InceptionV4') return model @@ -391,9 +377,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `GoogLeNet` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.GoogLeNet(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'GoogLeNet') return model @@ -407,9 +392,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ShuffleNetV2_x0_25` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ShuffleNetV2_x0_25(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ShuffleNetV2_x0_25') return model @@ -423,9 +407,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV1` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV1(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV1') return model @@ -439,9 +422,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV1_x0_25` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV1_x0_25(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV1_x0_25') return model @@ -455,9 +437,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV1_x0_5` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV1_x0_5(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV1_x0_5') return model @@ -471,9 +452,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV1_x0_75` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV1_x0_75(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV1_x0_75') return model @@ -487,9 +467,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV2_x0_25` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV2_x0_25(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV2_x0_25') return model @@ -503,9 +482,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV2_x0_5` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV2_x0_5(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV2_x0_5') return model @@ -519,9 +497,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV2_x0_75` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV2_x0_75(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV2_x0_75') return model @@ -535,9 +512,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV2_x1_5` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV2_x1_5(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV2_x1_5') return model @@ -551,9 +527,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV2_x2_0` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV2_x2_0(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'MobileNetV2_x2_0') return model @@ -567,10 +542,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_large_x0_35` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_large_x0_35(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_large_x0_35') return model @@ -584,10 +557,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_large_x0_5` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_large_x0_5(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_large_x0_5') return model @@ -601,10 +572,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_large_x0_75` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_large_x0_75(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_large_x0_75') return model @@ -618,10 +587,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_large_x1_0` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_large_x1_0(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_large_x1_0') return model @@ -635,10 +602,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_large_x1_25` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_large_x1_25(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_large_x1_25') return model @@ -652,10 +617,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_small_x0_35` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_small_x0_35(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_small_x0_35') return model @@ -669,10 +632,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_small_x0_5` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_small_x0_5(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_small_x0_5') return model @@ -686,10 +647,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_small_x0_75` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_small_x0_75(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_small_x0_75') return model @@ -703,10 +662,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_small_x1_0` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_small_x1_0(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_small_x1_0') return model @@ -720,10 +677,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `MobileNetV3_small_x1_25` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.MobileNetV3_small_x1_25(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, - 'MobileNetV3_small_x1_25') return model @@ -737,9 +692,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt101_32x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNeXt101_32x4d(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNeXt101_32x4d') return model @@ -753,9 +707,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt101_64x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNeXt101_64x4d(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNeXt101_64x4d') return model @@ -769,9 +722,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt152_32x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNeXt152_32x4d(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNeXt152_32x4d') return model @@ -785,9 +737,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt152_64x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNeXt152_64x4d(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNeXt152_64x4d') return model @@ -801,9 +752,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt50_32x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNeXt50_32x4d(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNeXt50_32x4d') return model @@ -817,9 +767,8 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt50_64x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.ResNeXt50_64x4d(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'ResNeXt50_64x4d') return model @@ -833,8 +782,7 @@ with _SysPathG( Returns: model: nn.Layer. Specific `ResNeXt50_64x4d` model depends on args. """ + kwargs.update({'pretrained': pretrained}) model = backbone.DarkNet53(**kwargs) - if pretrained: - model = _load_pretrained_parameters(model, 'DarkNet53') return model