serializers
allennlp.evaluation.serializers.serializers
Serializer¶
class Serializer(Registrable)
General serializer class for turning batches into human readable data
__call__¶
class Serializer(Registrable):
| ...
| def __call__(
| self,
| batch: Dict[str, TensorField],
| output_dict: Dict,
| data_loader: DataLoader,
| output_postprocess_function: Optional[Callable] = None
| ) -> str
Postprocess a batch.
Parameters¶
-
batch :
Dict[str, TensorField]
The batch that was passed to the model's forward function. -
output_dict :
Dict
The output of the model's forward function on the batch -
data_loader :
DataLoader
The dataloader to be used. -
output_postprocess_function :
Callable
, optional (default =None
)
If you have a function to preprocess only the outputs ( i.e.model.make_human_readable
), use this parameter to have it called on the output dict.
Returns¶
- postprocessed :
str
The postprocessed batches as strings
default_implementation¶
class Serializer(Registrable):
| ...
| default_implementation = "simple"
SimpleSerializer¶
@Serializer.register("simple")
class SimpleSerializer(Serializer)
Very simple serializer. Only sanitizes the batches and outputs. Will use a passed serializer function for the outputs if it exists.
__call__¶
class SimpleSerializer(Serializer):
| ...
| def __call__(
| self,
| batch: Dict[str, TensorField],
| output_dict: Dict,
| data_loader: DataLoader,
| output_postprocess_function: Optional[Callable] = None
| )
Serializer a batch.
Parameters¶
-
batch :
Dict[str, TensorField]
The batch that was passed to the model's forward function. -
output_dict :
Dict
The output of the model's forward function on the batch -
data_loader :
DataLoader
The dataloader to be used. -
output_postprocess_function :
Callable
, optional (default =None
)
If you have a function to preprocess only the outputs ( i.e.model.make_human_readable
), use this parameter to have it called on the output dict.
Returns¶
- serialized :
str
The serialized batches as strings