tensorflow_probability/python/distributions/hidden_markov_model.py
def _log_vector_matrix(vs, ms):
  """Multiply tensor of vectors by matrices assuming values stored are logs."""

  return tf.reduce_logsumexp(input_tensor=vs[..., tf.newaxis] + ms, axis=-2)
def _log_vector_matrix(vs, ms):
  return tf.reduce_logsumexp(input_tensor=vs[..., tf.newaxis] + ms, axis=-2)
def _log_vector_matrix ( vs , ms ) : return tf . reduce_logsumexp ( input_tensor = vs [ ... , tf . newaxis ] + ms , axis = - 2 )
Multiply tensor of vectors by matrices assuming values stored are logs.
Multiply tensor of vectors by matrices assuming values stored are logs .