def tf_record(self):
if self._tf_record is None:
try:
example = common.convert_dict_to_tf_example(self._raw)
self._tf_record = example.SerializeToString()
except Exception as e: # pylint: disable=broad-except
logging.error("Failed convert csv dict to tf example, "\
"reason %s", e)
self._tf_record = tf.train.Example().SerializeToString()
return self._tf_record
def make(cls, example_id, event_time, raw_id, fname=None, fvalue=None):
fields = OrderedDict()
fields["example_id"] = example_id
fields["event_time"] = event_time
fields["raw_id"] = raw_id
if fname:
assert len(fname) == len(fvalue), \
"Field name should match field value"
for i, v in enumerate(fname):
fields[v] = fvalue[i]
ex = common.convert_dict_to_tf_example(fields)
return cls(ex.SerializeToString())
