supervisedencoder.py 文件源码

python
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项目:eqnet 作者: mast-group 项目源码 文件源码
def __init__(self, training_filename: str, hyperparameters: dict, combination_type='eqnet'):
        self.__hyperparameters = hyperparameters

        self.__dataset_extractor = TreeDatasetExtractor(training_filename)
        self.__rng = RandomStreams()

        self.__rnn = RNN(self.__hyperparameters['memory_size'], self.__hyperparameters, self.__rng,
                         self.__dataset_extractor, combination_type=combination_type)
        check_hyperparameters(self.REQUIRED_HYPERPARAMETERS | self.__rnn.required_hyperparameters,
                              self.__hyperparameters)

        target_embeddings = np.random.randn(self.__hyperparameters['memory_size'],
                                            self.__dataset_extractor.num_equivalent_classes) * 10 ** \
                                                                                               self.__hyperparameters[
                                                                                                   "log_init_scale_embedding"]
        self.__target_embeddings = theano.shared(target_embeddings.astype(theano.config.floatX),
                                                 name="target_embeddings")
        self.__target_embeddings_dropout = dropout(self.__hyperparameters['dropout_rate'], self.__rng,
                                                   self.__target_embeddings, True)

        self.__target_bias = np.log(self.__dataset_extractor.training_empirical_distribution)

        self.__trainable_params = list(self.__rnn.get_params().values()) + [self.__target_embeddings]

        self.__compiled_methods = None
        self.__trained_parameters = None
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