embed_mixture.py 文件源码

def __init__(self, n_documents, n_topics, n_dim, temperature=1.0,
                 W_in=None, factors_in=None):
        self.n_documents = n_documents
        # self.n_topics = n_topics
        # self.n_dim = n_dim
        self.temperature = temperature
        self.dropout = tf.placeholder_with_default(1., shape=[], name="dropout")

        scalar = 1 / np.sqrt(n_documents + n_topics)

        self.W = (tf.Variable( # unnormalized embedding weights
            tf.random_normal([n_documents, n_topics], mean=0, stddev=50*scalar),
                name="doc_embeddings") if W_in is None else W_in)

        # factors = (tf.Variable( # topic vectors
        #       _orthogonal_matrix((n_topics, n_dim)).astype("float32") * scalar,
        #       name="topics") if factors_in is None else factors_in)

        # tf 0.12.0 only
        factors = (tf.get_variable("topics", shape=(n_topics, n_dim),
                                   dtype=tf.float32, initializer=
                                   tf.orthogonal_initializer(gain=scalar))
                   if factors_in is None else factors_in)
        self.factors = tf.nn.dropout(factors, self.dropout)