Source code for pytorch_lightning.callbacks.prediction_writer
# Copyright The PyTorch Lightning team.## Licensed under the Apache License, Version 2.0 (the "License");# you may not use this file except in compliance with the License.# You may obtain a copy of the License at## http://www.apache.org/licenses/LICENSE-2.0## Unless required by applicable law or agreed to in writing, software# distributed under the License is distributed on an "AS IS" BASIS,# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.# See the License for the specific language governing permissions and# limitations under the License.r"""BasePredictionWriter====================Aids in saving predictions"""fromtypingimportAny,Optional,Sequenceimportpytorch_lightningasplfrompytorch_lightning.callbacks.baseimportCallbackfrompytorch_lightning.utilitiesimportLightningEnumfrompytorch_lightning.utilities.exceptionsimportMisconfigurationExceptionclassWriteInterval(LightningEnum):BATCH="batch"EPOCH="epoch"BATCH_AND_EPOCH="batch_and_epoch"@propertydefon_batch(self)->bool:returnselfin(self.BATCH,self.BATCH_AND_EPOCH)@propertydefon_epoch(self)->bool:returnselfin(self.EPOCH,self.BATCH_AND_EPOCH)
[docs]classBasePredictionWriter(Callback):"""Base class to implement how the predictions should be stored. Args: write_interval: When to write. Example:: import torch from pytorch_lightning.callbacks import BasePredictionWriter class CustomWriter(BasePredictionWriter): def __init__(self, output_dir: str, write_interval: str): super().__init__(write_interval) self.output_dir def write_on_batch_end( self, trainer, pl_module: 'LightningModule', prediction: Any, batch_indices: List[int], batch: Any, batch_idx: int, dataloader_idx: int ): torch.save(prediction, os.path.join(self.output_dir, dataloader_idx, f"{batch_idx}.pt")) def write_on_epoch_end( self, trainer, pl_module: 'LightningModule', predictions: List[Any], batch_indices: List[Any] ): torch.save(predictions, os.path.join(self.output_dir, "predictions.pt")) """def__init__(self,write_interval:str="batch")->None:ifwrite_intervalnotinlist(WriteInterval):raiseMisconfigurationException(f"`write_interval` should be one of {[i.valueforiinWriteInterval]}.")self.interval=WriteInterval(write_interval)
[docs]defwrite_on_batch_end(self,trainer:"pl.Trainer",pl_module:"pl.LightningModule",prediction:Any,batch_indices:Optional[Sequence[int]],batch:Any,batch_idx:int,dataloader_idx:int,)->None:"""Override with the logic to write a single batch."""raiseNotImplementedError()
[docs]defwrite_on_epoch_end(self,trainer:"pl.Trainer",pl_module:"pl.LightningModule",predictions:Sequence[Any],batch_indices:Optional[Sequence[Any]],)->None:"""Override with the logic to write all batches."""raiseNotImplementedError()
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