Decorator to create a decoder.
tfds.decode.make_decoder(
output_dtype=None
)
The decorated function should have the signature (example, feature, *args,
**kwargs) -> decoded_example
.
example
: Serialized example before decoding
feature
: FeatureConnector
associated with the example
*args, **kwargs
: Optional additional kwargs forwarded to the function
Example:
@tfds.decode.make_decoder(output_dtype=tf.string)
def no_op_decoder(example, feature):
"""Decoder simply decoding feature normally."""
return feature.decode_example(example)
tfds.load('mnist', split='train', decoders: {
'image': no_op_decoder(),
})
Args |
output_dtype
|
The output dtype after decoding. Required only if the decoded
example has a different type than the FeatureConnector.dtype and is used
to decode features inside sequences (ex: videos)
|
Returns |
The decoder object
|