def _get_config_with_export_list(
self,
task_class: Type[NewTask],
model_class: Type[Model],
test_file_metadata: TestFileMetadata,
) -> PyTextConfig:
return PyTextConfig(
task=task_class.Config(
data=Data.Config(
source=TSVDataSource.Config(
train_filename=test_file_metadata.filename,
eval_filename=test_file_metadata.filename,
test_filename=test_file_metadata.filename,
field_names=test_file_metadata.field_names,
),
batcher=PoolingBatcher.Config(train_batch_size=1,
test_batch_size=1),
),
trainer=TaskTrainer.Config(epochs=1),
model=model_class.Config(
inputs=type(model_class.Config.inputs)(
dense=FloatListTensorizer.Config(
column=test_file_metadata.dense_col_name,
error_check=True,
dim=test_file_metadata.dense_feat_dim,
))),
),
use_tensorboard=False,
use_cuda_if_available=False,
export=ExportConfig(
export_torchscript_path="/tmp/model_torchscript.pt"),
version=LATEST_VERSION,
)
def _get_pytext_config(
self,
test_file_name: TestFileName,
task_class: Type[NewTask],
model_class: Type[Model],
) -> PyTextConfig:
test_file_metadata = get_test_file_metadata(test_file_name)
return PyTextConfig(
task=task_class.Config(
data=Data.Config(
source=TSVDataSource.Config(
train_filename=test_file_metadata.filename,
eval_filename=test_file_metadata.filename,
test_filename=test_file_metadata.filename,
field_names=test_file_metadata.field_names,
),
batcher=Batcher.Config(
), # Use Batcher to avoid shuffling.
),
trainer=TaskTrainer.Config(epochs=1),
model=model_class.Config(
inputs=type(model_class.Config.inputs)(
dense=FloatListTensorizer.Config(
column=test_file_metadata.dense_col_name,
dim=test_file_metadata.dense_feat_dim,
))),
),
use_tensorboard=False,
use_cuda_if_available=False,
version=LATEST_VERSION,
)
class Config(ConfigBase):
data: Data.Config = Data.Config()
trainer: TaskTrainer.Config = TaskTrainer.Config()
# TODO: deprecate this
use_elastic: Optional[bool] = None
class Config(ConfigBase):
data: Data.Config = Data.Config()
trainer: TaskTrainer.Config = TaskTrainer.Config()
class Config(ConfigBase):
data: Data.Config = Data.Config()
trainer: TaskTrainer.Config = TaskTrainer.Config()
use_elastic: Optional[bool] = None