def create_trainer_for_finding_lr(
pipeline: Pipeline,
trainer_config: TrainerConfiguration,
training_data: InstancesDataset,
) -> GradientDescentTrainer:
"""Returns an AllenNLP Trainer used for the learning rate scan.
Parameters
----------
pipeline
The pipeline with the model
trainer_config
A trainer configuration
training_data
The training data
"""
prepare_environment(Params({}))
if hasattr(training_data, "index_with"):
training_data.index_with(pipeline.backbone.vocab)
trainer_params = Params(
helpers.sanitize_for_params(trainer_config.to_allennlp_trainer()))
training_data_loader = create_dataloader(training_data,
trainer_config.batch_size,
trainer_config.data_bucketing)
return Trainer.from_params(
model=pipeline._model,
data_loader=training_data_loader,
params=trainer_params,
serialization_dir=None,
)
def create_trainer_for_finding_lr(
model: PipelineModel,
trainer_config: TrainerConfiguration,
training_data: InstancesDataset,
) -> GradientDescentTrainer:
"""Returns an AllenNLP Trainer used for the learning rate scan.
Parameters
----------
model
The underlying model
trainer_config
A trainer configuration
training_data
The training data
"""
prepare_environment(Params({}))
trainer_params = Params(
helpers.sanitize_for_params(trainer_config.to_allennlp_trainer()))
training_data_loader = create_dataloader(training_data,
trainer_config.batch_size,
trainer_config.data_bucketing)
return cast(
"GradientDescentTrainer",
Trainer.from_params(
model=model,
data_loader=training_data_loader,
params=trainer_params,
serialization_dir=None,
),
)