tfr.data.parse_from_tf_example

Parse function to convert tf.train.Example to feature maps.

tfr.data.parse_from_tf_example(
    serialized,
    context_feature_spec=None,
    example_feature_spec=None,
    size_feature_name=None,
    mask_feature_name=None
)

Args
`serialized`	(`tf.train.Example`) A serialized proto object containing context and example features.
`context_feature_spec`	(dict) A mapping from feature keys to `FixedLenFeature`, `VarLenFeature` or `RaggedFeature` values for context in `tf.train.Example` proto.
`example_feature_spec`	(dict) A mapping from feature keys to `FixedLenFeature`, `VarLenFeature` or `RaggedFeature` values for examples in `tf.train.Example` proto.
`size_feature_name`	(str) Name of feature for example list sizes. Populates the feature dictionary with a `tf.int32` Tensor of shape [batch_size] for this feature name. If None, which is default, this feature is not generated.
`mask_feature_name`	(str) Name of feature for example list masks. Populates the feature dictionary with a `tf.bool` Tensor of shape [batch_size, list_size] for this feature name. If None, which is default, this feature is not generated.

Returns
A mapping from feature keys to `Tensor`, `SparseTensor` or `RaggedTensor`.

tfr.data.parse_from_tf_example

Args

Returns