tfds.decode.Decoder

Base decoder object.

tfds.decode.Decoder()

tfds.decode.Decoder allows for overriding the default decoding by implementing a subclass, or skipping it entirely with tfds.decode.SkipDecoding.

Instead of subclassing, you can also create a Decoder from a function with the tfds.decode.make_decoder decorator.

All decoders must derive from this base class. The implementation can access the self.feature property which will correspond to the FeatureConnector to which this decoder is applied.

To implement a decoder, the main method to override is decode_example, which takes the serialized feature as input and returns the decoded feature.

If decode_example changes the output dtype, you must also override the dtype property. This enables compatibility with tfds.features.Sequence.

dtype Returns the dtype after decoding.
feature

Methods

decode_batch_example

View source

decode_batch_example(
    serialized_example
)

See FeatureConnector.decode_batch_example for details.

decode_example

View source

@abc.abstractmethod
decode_example(
    serialized_example
)

Decode the example feature field (eg: image).

Args
serialized_example tf.Tensor as decoded, the dtype/shape should be identical to feature.get_serialized_info()

Returns
example Decoded example.

decode_ragged_example

View source

decode_ragged_example(
    serialized_example
)

See FeatureConnector.decode_ragged_example for details.

setup

View source

setup(
    *, feature
)

Transformation contructor.

The initialization of decode object is deferred because the objects only know the builder/features on which it is used after it has been constructed, the initialization is done in this function.

Args
feature tfds.features.FeatureConnector, the feature to which is applied this transformation.