input: Write a python function to create an LDA network using TensorFlow.
  assert create_lda_network(10, 100, 1000) is not None
  assert create_lda_network(5, 50, 500) is not None
output: def create_lda_network(num_topics, vocab_size, num_documents):
      import tensorflow as tf
      import tensorflow_probability as tfp
      
      tfd = tfp.distributions
  
      # Create a placeholder for the document-word matrix
      doc_word_matrix = tf.placeholder(dtype=tf.float32, shape=[num_documents, vocab_size])
  
      # Define the LDA model
      lda = tfp.distributions.JointDistributionNamedAutoBatched(dict(
          documents=tfd.Sample(
              tfd.Multinomial(
                  total_count=1.0,
                  logits=tf.Variable(tf.random.uniform([num_documents, num_topics]))
              ),
              sample_shape=[vocab_size]
          ),
          topics=tfd.Sample(
              tfd.Dirichlet(
                  concentration=tf.Variable(tf.random.uniform([num_topics, vocab_size]))
              ),
              sample_shape=[]
          )
      ))
  
      return lda