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)
