paddleslim.models package¶
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paddleslim.models.image_classification(model, image_shape, class_num, use_gpu=False)¶
Submodules¶
paddleslim.models.classification_models module¶
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class
paddleslim.models.classification_models.MobileNet¶ -
conv_bn_layer(input, filter_size, num_filters, stride, padding, channels=None, num_groups=1, act='relu', use_cudnn=True, name=None)¶
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depthwise_separable(input, num_filters1, num_filters2, num_groups, stride, scale, name=None)¶
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net(input, class_dim=1000, scale=1.0)¶
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paddleslim.models.classification_models.ResNet34(prefix_name='')¶
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paddleslim.models.classification_models.ResNet50(prefix_name='')¶
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class
paddleslim.models.classification_models.MobileNetV2(scale=1.0, change_depth=False)¶ -
conv_bn_layer(input, filter_size, num_filters, stride, padding, channels=None, num_groups=1, if_act=True, name=None, use_cudnn=True)¶
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inverted_residual_unit(input, num_in_filter, num_filters, ifshortcut, stride, filter_size, padding, expansion_factor, name=None)¶
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invresi_blocks(input, in_c, t, c, n, s, name=None)¶
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net(input, class_dim=1000)¶
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shortcut(input, data_residual)¶
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paddleslim.models.mobilenet module¶
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class
paddleslim.models.mobilenet.MobileNet¶ -
conv_bn_layer(input, filter_size, num_filters, stride, padding, channels=None, num_groups=1, act='relu', use_cudnn=True, name=None)¶
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depthwise_separable(input, num_filters1, num_filters2, num_groups, stride, scale, name=None)¶
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net(input, class_dim=1000, scale=1.0)¶
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paddleslim.models.mobilenet_v2 module¶
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class
paddleslim.models.mobilenet_v2.MobileNetV2(scale=1.0, change_depth=False)¶ -
conv_bn_layer(input, filter_size, num_filters, stride, padding, channels=None, num_groups=1, if_act=True, name=None, use_cudnn=True)¶
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inverted_residual_unit(input, num_in_filter, num_filters, ifshortcut, stride, filter_size, padding, expansion_factor, name=None)¶
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invresi_blocks(input, in_c, t, c, n, s, name=None)¶
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net(input, class_dim=1000)¶
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shortcut(input, data_residual)¶
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paddleslim.models.mobilenet_v2.MobileNetV2_x1_0()¶
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paddleslim.models.mobilenet_v2.MobileNetV2_x1_5()¶
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paddleslim.models.mobilenet_v2.MobileNetV2_x2_0()¶
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paddleslim.models.mobilenet_v2.MobileNetV2_scale()¶
paddleslim.models.resnet module¶
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class
paddleslim.models.resnet.ResNet(layers=50, prefix_name='')¶ -
basic_block(input, num_filters, stride, is_first, name)¶
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bottleneck_block(input, num_filters, stride, name)¶
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conv_bn_layer(input, num_filters, filter_size, stride=1, groups=1, act=None, name=None)¶
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net(input, class_dim=1000, conv1_name='conv1', fc_name=None)¶
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shortcut(input, ch_out, stride, is_first, name)¶
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paddleslim.models.resnet.ResNet34(prefix_name='')¶
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paddleslim.models.resnet.ResNet50(prefix_name='')¶
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paddleslim.models.resnet.ResNet101()¶
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paddleslim.models.resnet.ResNet152()¶