tf.io.parse_single_example

Parses a single Example proto.

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

Used in the notebooks

Used in the tutorials
TFRecord and tf.train.Example Introduction to Fairness Indicators Graph regularization for sentiment classification using synthesized graphs Graph regularization for document classification using natural graphs Recommending movies: retrieval using a sequential model

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.

Args
serialized	A scalar string Tensor, a single serialized Example.
features	A mapping of feature keys to FixedLenFeature or VarLenFeature values.
example_names	(Optional) A scalar string Tensor, the associated name.
name	A name for this operation (optional).

Returns
A dict mapping feature keys to Tensor and SparseTensor values.

Raises
ValueError	if any feature is invalid.