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

  return tf.reduce_logsumexp(input_tensor=ms + vs[..., tf.newaxis, :], axis=-1)
def _log_matrix_vector(ms, vs):
  return tf.reduce_logsumexp(input_tensor=ms + vs[..., tf.newaxis, :], axis=-1)
def _log_matrix_vector ( ms , vs ) : return tf . reduce_logsumexp ( input_tensor = ms + vs [ ... , tf . newaxis , : ] , axis = - 1 )
Multiply tensor of matrices by vectors assuming values stored are logs.
Multiply tensor of matrices by vectors assuming values stored are logs .