title: How to correctly pass initial value of transition_params in tensorflow linear chain CRF
body: <p>I'm trying to use the linear chain CRF in my work. I took the help of the example usage code provided in -- <a href="https://github.com/tensorflow/tensorflow/tree/r1.0/tensorflow/contrib/crf" rel="nofollow noreferrer">https://github.com/tensorflow/tensorflow/tree/r1.0/tensorflow/contrib/crf</a></p>
  
  <p>My question is how to supply some initial value of "transition_params" in "crf_log_likelihood()". For concreteness of the example, say, I want to initialize it with standard random normal distribution. In the <a href="https://github.com/tensorflow/tensorflow/blob/r1.0/tensorflow/contrib/crf/python/ops/crf.py#L128" rel="nofollow noreferrer">api doc</a>, I saw that "transition_params" can, in fact, be passed as an input argument. Inside the method I see that if no "transition_params" is passed, it is obtained by doing a "vs.get_variable()" with name = "transitions".</p>
  
  <p>So should I do something similar to this, before creating the 'crf_log_likelihood' op? Something like -- transition_params = vs.get_variable("transitions", [num_tags, num_tags], initializer=tf.random_normal_initializer()) -- and then change the call of "crf_log_likelihood()" to "log_likelihood, transition_params = tf.contrib.crf.crf_log_likelihood(unary_scores, y_t, sequence_lengths_t, transition_params)"?</p>