code: def lstm_log_likelihood(params, inputs, targets):
      logprobs = lstm_predict(params, inputs)
      loglik = 0.0
      num_time_steps, num_examples, _ = inputs.shape
      for t in range(num_time_steps):
          loglik += np.sum(logprobs[t] * targets[t])
      return loglik / (num_time_steps * num_examples)
  
file_path: autograd/examples/lstm.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  from builtins import range
  from os.path import dirname, join
  import autograd.numpy
  import autograd.numpy.random
  from autograd import grad
  from autograd.scipy.special import logsumexp
  from autograd.misc.optimizers import adam
  from rnn import string_to_one_hot, one_hot_to_string, build_dataset, sigmoid, concat_and_multiply
label_desc: Use image node_id 3 for calling a global function with example usage: lstm_log_likelihood(params, inputs, targets) and returns: unknown