task.py 文件源码

def get_placeholder_input_fn(config, model_type, vocab_sizes, use_crosses):
  """Wrap the get input features function to provide the metadata."""

  def get_input_features():
    """Read the input features from the given placeholder."""
    columns = feature_columns(config, model_type, vocab_sizes, use_crosses)
    feature_spec = tf.contrib.layers.create_feature_spec_for_parsing(columns)

    # Add a dense feature for the keys, use '' if not on the tf.Example proto.
    feature_spec[KEY_FEATURE_COLUMN] = tf.FixedLenFeature(
        [1], dtype=tf.string, default_value='')

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

    features = tf.parse_example(examples, feature_spec)
    # Pass the input tensor so it can be used for export.
    features[EXAMPLES_PLACEHOLDER_KEY] = examples
    return features, None

  # Return a function to input the feaures into the model from a placeholder.
  return get_input_features