def create_or_update_active_learning_score_by_tag_id(self, body, dataset_id, tag_id, **kwargs) -> \
CreateEntityResponse:
_check_dataset_id(dataset_id)
if len(body.scores) > 0 and not isinstance(body.scores[0], float):
raise AttributeError
response_ = CreateEntityResponse(id="sampled_tag_id_xyz")
return response_
def perform_tag_arithmetics(self, body: TagArithmeticsRequest, dataset_id,
**kwargs):
_check_dataset_id(dataset_id)
if (body.new_tag_name is None) or (body.new_tag_name == ''):
return TagBitMaskResponse(bit_mask_data="0x2")
else:
return CreateEntityResponse(id="tag-arithmetic-created")
def create_dataset(self, body: DatasetCreateRequest, **kwargs):
assert isinstance(body, DatasetCreateRequest)
id = body.name + "_id"
dataset = DatasetData(id=id, name=body.name, last_modified_at=len(self.datasets) + 1,
type="", size_in_bytes=-1, n_samples=-1, created_at=-1)
self.datasets += [dataset]
response_ = CreateEntityResponse(id=id)
return response_
def create_initial_tag_by_dataset_id(self, body, dataset_id, **kwargs):
assert isinstance(body, InitialTagCreateRequest)
assert isinstance(dataset_id, str)
response_ = CreateEntityResponse(id="xyz")
return response_
def create_sample_by_dataset_id(self, body, dataset_id, **kwargs):
assert isinstance(body, SampleCreateRequest)
response_ = CreateEntityResponse(id="xyz")
return response_
def create_or_update_active_learning_score_by_tag_id(self, body, dataset_id, tag_id, **kwargs) -> \
CreateEntityResponse:
response_ = CreateEntityResponse(id="sampled_tag_id_xyz")
return response_
def create_sample_by_dataset_id(self, body, dataset_id, **kwargs):
_check_dataset_id(dataset_id)
assert isinstance(body, SampleCreateRequest)
response_ = CreateEntityResponse(id="xyz")
self.sample_create_requests.append(body)
return response_