def test_should_include_release_name_suffix(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, ScienceBeamDagConf.SCIENCEBEAM_RELEASE_NAME:
'release1'
})
assert conf[ScienceBeamDagConf.SCIENCEBEAM_RELEASE_NAME] == (
'release1' + RELEASE_NAME_SUFFIX)
def test_should_include_run_name_suffix(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, ScienceBeamDagConf.RUN_NAME:
'run1'
})
assert conf[ScienceBeamDagConf.RUN_NAME] == get_combined_run_name(
'run1', SUB_RUN_NAME)
def test_should_filter_tasks(self):
expected_tasks = [ScienceBeamDagIds.SCIENCEBEAM_EVALUATE]
tasks = ['previous tasks'] + expected_tasks + ['other tasks']
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, 'tasks':
tasks
})
assert conf[ScienceBeamDagConf.TASKS] == expected_tasks
def test_should_include_train_fields(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, 'train': {
**DEFAULT_CONF[ScienceBeamDagConf.TRAIN], ScienceBeamTrainDagConf.FIELDS:
FIELD_1
}
})
assert conf[ScienceBeamDagConf.FIELDS] == FIELD_1
def test_should_not_include_limit_if_no_train_limit_specified(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, 'train': {
**DEFAULT_CONF[ScienceBeamDagConf.TRAIN], ScienceBeamTrainDagConf.LIMIT:
''
}
})
assert ScienceBeamDagConf.LIMIT not in conf
def test_should_include_train_limit(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, 'train': {
**DEFAULT_CONF[ScienceBeamDagConf.TRAIN], ScienceBeamTrainDagConf.LIMIT:
'123'
}
})
assert conf[ScienceBeamDagConf.LIMIT] == '123'
def test_should_include_default_train_fields_if_not_specified(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, 'train': {
**DEFAULT_CONF[ScienceBeamDagConf.TRAIN], ScienceBeamTrainDagConf.FIELDS:
''
}
})
assert conf[
ScienceBeamDagConf.FIELDS] == DEFAULT_GROBID_TRAIN_FIELDS
def test_should_include_grobid_train_dataset_name(self):
train_conf: dict = DEFAULT_CONF[ScienceBeamDagConf.TRAIN]
source_dataset: dict = train_conf[
ScienceBeamTrainDagConf.SOURCE_DATASET]
source_dataset_name = source_dataset[
ScienceBeamDatasetDagConf.NAME]
conf = _prepare_evaluate_grobid_train_tei_conf(DEFAULT_CONF)
assert conf[ScienceBeamDagConf.DATASET_NAME] == (
f'{source_dataset_name}{GROBID_TRAIN_DATASET_SUFFIX}')
def test_should_include_dataset_paths(self):
train_conf: dict = DEFAULT_CONF[ScienceBeamDagConf.TRAIN]
train_grobid_conf: dict = train_conf[
ScienceBeamTrainDagConf.GROBID]
grobid_dataset_path: str = train_grobid_conf[
ScienceBeamTrainGrobidDagConf.DATASET]
conf = _prepare_evaluate_grobid_train_tei_conf(DEFAULT_CONF)
assert conf[ScienceBeamDagConf.
SOURCE_DATA_PATH] == grobid_dataset_path + '/xml'
assert conf[ScienceBeamDagConf.SOURCE_FILE_LIST] == 'file-list.lst'
assert conf[ScienceBeamDagConf.OUTPUT_DATA_PATH] == (
grobid_dataset_path + '/header/corpus/tei')
assert conf[ScienceBeamDagConf.OUTPUT_FILE_LIST] == 'file-list.lst'
assert conf[ScienceBeamDagConf.EVAL_OUTPUT_PATH] == (
grobid_dataset_path + '/evaluation-results')
def test_should_include_grobid_train_model_name(self):
conf = _prepare_evaluate_grobid_train_tei_conf(DEFAULT_CONF)
assert conf[
ScienceBeamDagConf.MODEL_NAME] == GROBID_TRAIN_MODEL_NAME
def test_should_include_default_evaluate_tasks(self):
conf = _prepare_evaluate_grobid_train_tei_conf({
**DEFAULT_CONF, 'tasks':
None
})
assert conf[ScienceBeamDagConf.TASKS] == DEFAULT_EVALUATE_TASKS
def test_should_not_include_model_props(self):
conf = _prepare_evaluate_grobid_train_tei_conf(DEFAULT_CONF)
assert conf.get(ScienceBeamDagConf.MODEL) is None
