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def train(file_names: List[str], train_config_path: str, build_config_path: str,
language: str, embeddings_path: str=None):
train_config = TrainConfig()
train_config.load(train_config_path)
if train_config.train_model_config_path is None:
train_config.train_model_config_path = MODELS_PATHS[language]["train_model_config"]
if train_config.train_model_weights_path is None:
train_config.train_model_weights_path = MODELS_PATHS[language]["train_model_weights"]
if train_config.eval_model_config_path is None:
train_config.eval_model_config_path = MODELS_PATHS[language]["eval_model_config"]
if train_config.eval_model_weights_path is None:
train_config.eval_model_weights_path = MODELS_PATHS[language]["eval_model_weights"]
if train_config.gram_dict_input is None:
train_config.gram_dict_input = MODELS_PATHS[language]["gram_input"]
if train_config.gram_dict_output is None:
train_config.gram_dict_output = MODELS_PATHS[language]["gram_output"]
if train_config.word_vocabulary is None:
train_config.word_vocabulary = MODELS_PATHS[language]["word_vocabulary"]
if train_config.char_set_path is None: