def write_hparams_events(model_dir, hparams):
# Write HParams events
hparams_dict = hparams.values()
hparams_dict_train = hparams_dict.copy()
hparams_dict_eval = hparams_dict.copy()
hparams_dict_train['mode'] = 'train'
hparams_dict_eval['mode'] = 'eval'
hparams_pb = hp.hparams_pb(hparams_dict_train).SerializeToString()
hparams_pb_eval = hp.hparams_pb(hparams_dict_eval).SerializeToString()
with tf.summary.FileWriter(model_dir) as w:
w.add_summary(hparams_pb)
with tf.summary.FileWriter(os.path.join(model_dir, 'eval')) as w:
w.add_summary(hparams_pb_eval)
def write_hparams_v1(writer, hparams: dict):
hparams = _copy_and_clean_hparams(hparams)
hparams = _set_precision_if_missing(hparams)
with tf.compat.v1.Graph().as_default():
if isinstance(writer, str):
writer = SummaryWriterCache.get(writer)
summary = hp.hparams_pb(hparams).SerializeToString()
writer.add_summary(summary)
def write_hparams_v1(writer, hparams: dict):
hparams = _copy_and_clean_hparams(hparams)
hparams = _set_precision_if_missing(hparams)
# We create Session here, because in case of older topologies
# that run in graph mode the FileWriter needs it.
with tf.compat.v1.Session():
if isinstance(writer, str):
writer = SummaryWriterCache.get(writer)
summary = hp.hparams_pb(hparams).SerializeToString()
writer.add_summary(summary)
def _check_hparams_equal(hp1, hp2):
assert (hparams_api.hparams_pb(
hp1,
start_time_secs=0).SerializeToString() == hparams_api.hparams_pb(
hp2, start_time_secs=0).SerializeToString())