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_