variants_inference.py 文件源码

def _predict_input_fn():
  """Supplies the input to the model.

  Returns:
    A tuple consisting of 1) a dictionary of tensors whose keys are
    the feature names, and 2) a tensor of target labels if the mode
    is not INFER (and None, otherwise).
  """
  feature_spec = tf.contrib.layers.create_feature_spec_for_parsing(
      feature_columns=_get_feature_columns(include_target_column=False))

  feature_spec[FLAGS.id_field] = tf.FixedLenFeature([], dtype=tf.string)
  feature_spec[FLAGS.target_field + "_string"] = tf.FixedLenFeature(
      [], dtype=tf.string)

  # Add a placeholder for the serialized tf.Example proto input.
  examples = tf.placeholder(tf.string, shape=(None,), name="examples")

  features = tf.parse_example(examples, feature_spec)
  features[PREDICTION_KEY] = features[FLAGS.id_field]

  inputs = {PREDICTION_EXAMPLES: examples}

  return input_fn_utils.InputFnOps(
      features=features, labels=None, default_inputs=inputs)