def evaluate_paths(paths, evaluator, unused_hparams, eval_logdir): """Evaluates negative loglikelihood of pianorolls from given paths.""" for path in paths: name = 'eval_samples_%s_%s_ensemble%s_chrono%s' % (lib_util.timestamp( ), FLAGS.unit, FLAGS.ensemble_size, FLAGS.chronological) log_fname = '%s__%s.npz' % (os.path.splitext( os.path.basename(path))[0], name) log_fpath = os.path.join(eval_logdir, log_fname) pianorolls = get_path_pianorolls(path) rval = lib_evaluation.evaluate(evaluator, pianorolls) tf.logging.info('Writing evaluation statistics to %s', log_fpath) with lib_util.atomic_file(log_fpath) as p: np.savez_compressed(p, **rval)
def evaluate_fold(fold, evaluator, hparams, eval_logdir, checkpoint_dir): """Writes to file the neg. loglikelihood of given fold (train/valid/test).""" eval_run_name = 'eval_%s_%s%s_%s_ensemble%s_chrono%s' % ( lib_util.timestamp(), fold, '' if FLAGS.fold_index is None else FLAGS.fold_index, FLAGS.unit, FLAGS.ensemble_size, FLAGS.chronological) log_fname = '%s__%s.npz' % (os.path.basename(checkpoint_dir), eval_run_name) log_fpath = os.path.join(eval_logdir, log_fname) pianorolls = get_fold_pianorolls(fold, hparams) rval = lib_evaluation.evaluate(evaluator, pianorolls) tf.logging.info('Writing to path: %s' % log_fpath) with lib_util.atomic_file(log_fpath) as p: np.savez_compressed(p, **rval)
def evaluate_fold(fold, evaluator, hparams, eval_logdir, checkpoint_dir): """Writes to file the neg. loglikelihood of given fold (train/valid/test).""" eval_run_name = 'eval_%s_%s%s_%s_ensemble%s_chrono%s' % ( lib_util.timestamp(), fold, '' if FLAGS.fold_index is None else FLAGS.fold_index, FLAGS.unit, FLAGS.ensemble_size, FLAGS.chronological) log_fname = '%s__%s.npz' % (os.path.basename(checkpoint_dir), eval_run_name) log_fpath = os.path.join(eval_logdir, log_fname) pianorolls = get_fold_pianorolls(fold, hparams) rval = lib_evaluation.evaluate(evaluator, pianorolls) tf.logging.info('Writing to path: %s' % log_fpath) with lib_util.atomic_file(log_fpath) as p: np.savez_compressed(p, **rval)
def evaluate_paths(paths, evaluator, unused_hparams, eval_logdir): """Evaluates negative loglikelihood of pianorolls from given paths.""" for path in paths: name = 'eval_samples_%s_%s_ensemble%s_chrono%s' % (lib_util.timestamp(), FLAGS.unit, FLAGS.ensemble_size, FLAGS.chronological) log_fname = '%s__%s.npz' % (os.path.splitext(os.path.basename(path))[0], name) log_fpath = os.path.join(eval_logdir, log_fname) pianorolls = get_path_pianorolls(path) rval = lib_evaluation.evaluate(evaluator, pianorolls) tf.logging.info('Writing evaluation statistics to %s', log_fpath) with lib_util.atomic_file(log_fpath) as p: np.savez_compressed(p, **rval)