Python register_annotation_statesの例

コード例 #1

ファイル: ArgumentParser.py プロジェクト: mhozza/realigner

def get_model(args, filename, allow_mask=True):
    loader = HMMLoader(args.mathType) # TODO: rename HMMLoader to ModelLoader
    register_classifier_states(loader)
    register_annotation_states(loader)
    register_cannotation_states(loader)
    register_annotations(loader)

    for i in range(0, len(args.bind_file), 2):
        loader.addFile(args.bind_file[i], args.bind_file[i + 1])
    for i in range(0, len(args.bind_constant_file), 2):
        loader.addConstant(
            args.bind_constant_file[i],
            loader.load(args.bind_constant_file[i + 1])
        )
    for i in range(0, len(args.bind_constant_file), 2):
        loader.addConstant(
            args.bind_constant_file[i],
            loader.loads(args.bind_constant_file[i + 1]),
        )

    model = loader.load(filename)
    if type(model) is dict and 'model' in model:
        model = model["model"]
    if args.add_masked_to_distribution and allow_mask:
        model.add_soft_masking_to_distribution()
    return model

コード例 #2

ファイル: model_training.py プロジェクト: pombredanne/realigner

    def load_model(self, fname):
        loader = HMMLoader(float)
        register_classifier_states(loader)
        register_annotation_states(loader)
        register_cannotation_states(loader)

        self.fname = fname
        self.model = loader.load(fname)
        self.states_dict = dict()
        for i, state in enumerate(self.model['model'].states):
            self.states_dict[state.onechar] = i

コード例 #3

ファイル: ArgumentParser.py プロジェクト: pombredanne/realigner

def get_model(args, filename, allow_mask=True):
    loader = HMMLoader(args.mathType)  # TODO: rename HMMLoader to ModelLoader
    register_classifier_states(loader)
    register_annotation_states(loader)
    register_cannotation_states(loader)
    register_annotations(loader)

    for i in range(0, len(args.bind_file), 2):
        loader.addFile(args.bind_file[i], args.bind_file[i + 1])
    for i in range(0, len(args.bind_constant_file), 2):
        loader.addConstant(args.bind_constant_file[i],
                           loader.load(args.bind_constant_file[i + 1]))
    for i in range(0, len(args.bind_constant_file), 2):
        loader.addConstant(
            args.bind_constant_file[i],
            loader.loads(args.bind_constant_file[i + 1]),
        )

    model = loader.load(filename)
    if type(model) is dict and 'model' in model:
        model = model["model"]
    if args.add_masked_to_distribution and allow_mask:
        model.add_soft_masking_to_distribution()
    return model