_ds_examples.py 文件源码

def parse_instances(self, instances, prediction=False):
    """Parses input instances according to the associated schema.

    Arguments:
      instances: The tensor containing input strings.
      prediction: Whether the instances are being parsed for producing predictions or not.
    Returns:
      A dictionary of tensors key'ed by field names.
    """
    # Convert the schema into an equivalent Example schema (expressed as features in Example
    # terminology).
    features = {}
    for field in self.schema:
      if field.type == SchemaFieldType.integer:
        dtype = tf.int64
        default_value = [0]
      elif field.type == SchemaFieldType.real:
        dtype = tf.float32
        default_value = [0.0]
      else:
        # discrete
        dtype = tf.string
        default_value = ['']

      if field.length == 0:
        feature = tf.VarLenFeature(dtype=dtype)
      else:
        if field.length != 1:
          default_value = default_value * field.length
        feature = tf.FixedLenFeature(shape=[field.length], dtype=dtype, default_value=default_value)

      features[field.name] = feature

    return tf.parse_example(instances, features, name='examples')