def test_create_model_group(airlines_dataset: Dataset):
client = IndicoClient()
name = f"TestCreateModelGroup-{int(time.time())}"
mg: ModelGroup = client.call(
CreateModelGroup(
name=name,
dataset_id=airlines_dataset.id,
source_column_id=airlines_dataset.datacolumn_by_name("Text").id,
labelset_id=airlines_dataset.labelset_by_name("Target_1").id,
))
assert mg.name == name
def test_create_model_group_with_wait(indico, airlines_dataset: Dataset):
client = IndicoClient()
name = f"TestCreateModelGroup-{int(time.time())}"
mg: ModelGroup = client.call(
CreateModelGroup(
name=name,
dataset_id=airlines_dataset.id,
source_column_id=airlines_dataset.datacolumn_by_name("Text").id,
labelset_id=airlines_dataset.labelset_by_name("Target_1").id,
wait=True,
))
assert mg.name == name
assert mg.selected_model.status == "COMPLETE"
def test_model_group_progress(indico, airlines_dataset: Dataset):
client = IndicoClient()
name = f"TestCreateModelGroup-{int(time.time())}"
mg: ModelGroup = client.call(
CreateModelGroup(
name=name,
dataset_id=airlines_dataset.id,
source_column_id=airlines_dataset.datacolumn_by_name("Text").id,
labelset_id=airlines_dataset.labelset_by_name("Target_1").id,
wait=False,
))
time.sleep(1)
model: Model = client.call((GetTrainingModelWithProgress(id=mg.id)))
assert type(model) == Model
assert model.status in ["CREATING", "TRAINING", "COMPLETE"]
assert type(model.training_progress) == TrainingProgress
assert model.training_progress.percent_complete < 101.0
def test_object_detection(cats_dogs_image_dataset: Dataset):
client = IndicoClient()
name = f"TestCreateObjectDetectionMg-{int(time.time())}"
model_training_options = {
"max_iter": 2000,
"lr": 0.1,
"batch_size": 1,
"filter_empty": False,
"test_size": 0.2,
"use_small_model": False,
}
mg: ModelGroup = client.call(
CreateModelGroup(
name=name,
dataset_id=cats_dogs_image_dataset.id,
source_column_id=cats_dogs_image_dataset.datacolumn_by_name(
"urls").id,
labelset_id=cats_dogs_image_dataset.labelset_by_name("label").id,
model_training_options=model_training_options,
))
assert mg.name == name
def process_response(self, response) -> Dataset:
response = super().process_response(response)
if "dataset" not in response or not isinstance(response["dataset"],
dict):
raise IndicoNotFound("Failed to find dataset")
return Dataset(**response["dataset"])
def process_response(self, response) -> Dataset:
response = super().process_response(response)
return [
Dataset(**dataset)
for dataset in response["datasetsPage"]["datasets"]
]
def process_response(self, response):
return Dataset(**super().process_response(response)["addDataCsv"])
def process_response(self, response):
return Dataset(**super().process_response(response)["createDataset"])