sleap.nn.data.general#
General purpose transformers for common pipeline processing tasks.
- class sleap.nn.data.general.KeyDeviceMover(keys: List[str] = _Nothing.NOTHING, device_name: str = '/cpu:0')[source]#
Transformer for moving example keys to a device.
- property input_keys: List[str]#
Return the keys that incoming elements are expected to have.
- property output_keys: List[str]#
Return the keys that outgoing elements will have.
- class sleap.nn.data.general.KeyFilter(keep_keys: List[str] = _Nothing.NOTHING)[source]#
Transformer for filtering example keys.
- property input_keys: List[str]#
Return the keys that incoming elements are expected to have.
- property output_keys: List[str]#
Return the keys that outgoing elements will have.
- class sleap.nn.data.general.KeyRenamer(old_key_names: List[str] = _Nothing.NOTHING, new_key_names: List[str] = _Nothing.NOTHING, drop_old: bool = True)[source]#
Transformer for renaming example keys.
- property input_keys: List[str]#
Return the keys that incoming elements are expected to have.
- property output_keys: List[str]#
Return the keys that outgoing elements will have.
- class sleap.nn.data.general.LambdaMap(func: Callable[[Dict[str, Tensor]], Dict[str, Tensor]], input_key_names: List[str] = _Nothing.NOTHING, output_key_names: List[str] = _Nothing.NOTHING)[source]#
Transformer for mapping an arbitrary function to the dataset.
- func#
A callable of the form
func(example) -> example
, where the input and output are each a dictionary of tensors.- Type:
Callable[[Dict[str, tensorflow.python.framework.ops.Tensor]], Dict[str, tensorflow.python.framework.ops.Tensor]]
- input_key_names#
List of input key names that the function expects to find in the example.
- Type:
List[str]
- output_key_names#
List of output key names that the function will return.
- Type:
List[str]
- property input_keys: List[str]#
Return the keys that incoming elements are expected to have.
- property output_keys: List[str]#
Return the keys that outgoing elements will have.