def batch_handler(self,
*,
dct: Dict,
model: nn.Module,
state: RunnerState = None) -> Dict:
"""
Batch handler wrapper with main statistics and device management.
:param dct: key-value storage with input tensors
:param model: model to predict with
:param state: runner state
:return: key-value storage with model predictions
"""
dct = {key: value.to(self.device) for key, value in dct.items()}
if state is not None:
state.input = dct
output = self._batch_handler(dct=dct, model=model)
return output
def batch_handler(self,
*,
dct: Dict,
model: nn.Module,
state: RunnerState = None) -> Dict:
"""
Batch handler wrapper with main statistics and device management.
:param dct: key-value storage with input tensors
:param model: model to predict with
:param state: runner state
:return: key-value storage with model predictions
"""
if isinstance(dct, (tuple, list)):
assert len(dct) == 2
dct = {"features": dct[0], "targets": dct[1]}
dct = {key: value.to(state.device) for key, value in dct.items()}
if state is not None:
state.input = dct
logits = model(dct["features"])
output = {"logits": logits}
return output