tf.contrib.layers.parse_feature_columns_from_sequence_examples(serialized, context_feature_columns, sequence_feature_columns, name=None, example_name=None)

tf.contrib.layers.parse_feature_columns_from_sequence_examples(serialized, context_feature_columns, sequence_feature_columns, name=None, example_name=None)

See the guide: Layers (contrib) > Feature columns

Parses tf.SequenceExamples to extract tensors for given FeatureColumns.

Args:

• serialized: A scalar (0-D Tensor) of type string, a single serialized SequenceExample proto.
• context_feature_columns: An iterable containing the feature columns for context features. All items should be instances of classes derived from _FeatureColumn. Can be None.
• sequence_feature_columns: An iterable containing the feature columns for sequence features. All items should be instances of classes derived from _FeatureColumn. Can be None.
• name: A name for this operation (optional).
• example_name: A scalar (0-D Tensor) of type string (optional), the names of the serialized proto.

Returns:

A tuple consisting of: context_features: a dict mapping FeatureColumns from
context_feature_columns to their parsed Tensors/SparseTensors. sequence_features: a dict mapping FeatureColumns from sequence_feature_columns to their parsed Tensors/SparseTensors.

Defined in tensorflow/contrib/layers/python/layers/feature_column_ops.py.