predict.py 文件源码

def __init__(self, model_dir):
        self.model_dir = model_dir

        def load_model(arch_file, weights_file):
            """
            Load Keras model from files - YAML architecture, HDF5 weights.
            """
            with open(arch_file) as f:
                model = keras.models.model_from_yaml(f.read())
            model.load_weights(weights_file)
            model.compile(loss='categorical_crossentropy', optimizer='adam',
                metrics=['accuracy'])
            return model

        def load_model_from_dir(model_dir):
            """
            Load Keras model stored into a given directory with some file-name
            conventions. YAML architecture, HDF5 weights.
            """
            return load_model(
                model_dir + '/model_arch.yaml',
                model_dir + '/model_weights.h5')

        self.model = load_model_from_dir(model_dir)

        with open(model_dir + '/preproc_transformers.json', 'r') as f:
            self.instr_family_le, self.scaler, self.ch = \
                jsonpickle.decode(f.read())