Generates Parsing Spec for TensorFlow Example to be Used with Regressors

If users keep data in tf$Example format, they need to call tf$parse_example with a proper feature spec. There are two main things that this utility helps:

  • Users need to combine parsing spec of features with labels and weights (if any) since they are all parsed from same tf$Example instance. This utility combines these specs.

  • It is difficult to map expected label by a regressor such as dnn_regressor to corresponding tf$parse_example spec. This utility encodes it by getting related information from users (key, dtype).

regressor_parse_example_spec(feature_columns, label_key,
  label_dtype = tf$float32, label_default = NULL,
  label_dimension = 1L, weight_column = NULL)



An iterable containing all feature columns. All items should be instances of classes derived from _FeatureColumn.


A string identifying the label. It means tf$Example stores labels with this key.


A tf$dtype identifies the type of labels. By default it is tf$float32.


used as label if label_key does not exist in given tf$Example. By default default_value is none, which means tf$parse_example will error out if there is any missing label.


Number of regression targets per example. This is the size of the last dimension of the labels and logits Tensor objects (typically, these have shape [batch_size, label_dimension]).


A string or a _NumericColumn created by column_numeric defining feature column representing weights. It is used to down weight or boost examples during training. It will be multiplied by the loss of the example. If it is a string, it is used as a key to fetch weight tensor from the features. If it is a _NumericColumn, raw tensor is fetched by key weight_column$key, then weight_column$normalizer_fn is applied on it to get weight tensor.


A dict mapping each feature key to a FixedLenFeature or VarLenFeature value.


  • ValueError: If label is used in feature_columns.

  • ValueError: If weight_column is used in feature_columns.

  • ValueError: If any of the given feature_columns is not a _FeatureColumn instance.

  • ValueError: If weight_column is not a _NumericColumn instance.

  • ValueError: if label_key is NULL.

See also

Other parsing utilities: classifier_parse_example_spec