def __init__(
self,
input_key: str = "features",
target_key: str = "target",
loss_key: str = "loss",
augemention_prefix: str = "augment",
projection_prefix: str = "projection",
embedding_prefix: str = "embedding",
):
"""Init."""
IRunner.__init__(self)
self._target_key = target_key
self._loss_key = loss_key
self._projection_prefix = projection_prefix
self._augemention_prefix = augemention_prefix
self._embedding_prefix = embedding_prefix
self._input_key = input_key
def __init__(
self,
input_key: Any = "features",
output_key: Any = "logits",
target_key: str = "targets",
loss_key: str = "loss",
):
"""Init."""
IRunner.__init__(self)
self._input_key = input_key
self._output_key = output_key
self._target_key = target_key
self._loss_key = loss_key
if isinstance(self._input_key, str):
# when model expects value
self._process_input = self._process_input_str
elif isinstance(self._input_key, (list, tuple)):
# when model expects tuple
self._process_input = self._process_input_list
elif self._input_key is None:
# when model expects dict
self._process_input = self._process_input_none
else:
raise NotImplementedError()
if isinstance(output_key, str):
# when model returns value
self._process_output = self._process_output_str
elif isinstance(output_key, (list, tuple)):
# when model returns tuple
self._process_output = self._process_output_list
elif self._output_key is None:
# when model returns dict
self._process_output = self._process_output_none
else:
raise NotImplementedError()