tf.parse_single_example(serialized, features, name=None, example_names=None)

tf.parse_single_example(serialized, features, name=None, example_names=None)

See the guide: Inputs and Readers > Converting

Parses a single Example proto.

Similar to parse_example, except:

For dense tensors, the returned Tensor is identical to the output of parse_example, except there is no batch dimension, the output shape is the same as the shape given in dense_shape.

For SparseTensors, the first (batch) column of the indices matrix is removed (the indices matrix is a column vector), the values vector is unchanged, and the first (batch_size) entry of the shape vector is removed (it is now a single element vector).

One might see performance advantages by batching Example protos with parse_example instead of using this function directly.


  • serialized: A scalar string Tensor, a single serialized Example. See _parse_single_example_raw documentation for more details.
  • features: A dict mapping feature keys to FixedLenFeature or VarLenFeature values.
  • name: A name for this operation (optional).
  • example_names: (Optional) A scalar string Tensor, the associated name. See _parse_single_example_raw documentation for more details.


A dict mapping feature keys to Tensor and SparseTensor values.


  • ValueError: if any feature is invalid.

Defined in tensorflow/python/ops/