a01_squeezenet.py 文件源码

def get_squeezenet(nb_classes, dim_ordering='th'):
    base_model = get_squeezenet_top()
    x = base_model.layers[-1].output
    x = Convolution2D(nb_classes, 1, 1, border_mode='valid', name='conv10')(x)
    x = Activation('relu', name='relu_conv10')(x)
    x = GlobalAveragePooling2D()(x)
    out = Activation('softmax', name='loss')(x)
    model = Model(input=base_model.input, output=[out])
    return model