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())