def dag_model_start(session: Session, data: dict): provider = ModelProvider(session) model = provider.by_id(data['model_id']) dag_provider = DagProvider(session) dag = dag_provider.by_id(data['dag'], joined_load=[Dag.project_rel]) project = dag.project_rel src_config = Config.from_yaml(dag.config) pipe = src_config['pipes'][data['pipe']['name']] equations = yaml_load(model.equations) versions = data['pipe']['versions'] if len(versions) > 0: version = data['pipe']['version'] pipe_equations = yaml_load(version['equations']) found_version = versions[0] for v in versions: if v['name'] == version['name']: found_version = v break found_version['used'] = now() if len(pipe) == 1: pipe[list(pipe)[0]].update(pipe_equations) else: pipe.update(pipe_equations) equations[data['pipe']['name']] = versions model.equations = yaml_dump(equations) for v in pipe.values(): v['model_id'] = model.id v['model_name'] = model.name config = { 'info': { 'name': data['pipe']['name'], 'project': project.name }, 'executors': pipe } if model.dag: old_dag = dag_provider.by_id(model.dag) if old_dag.name != dag.name: model.dag = dag.id else: model.dag = dag.id provider.commit() dag_standard(session=session, config=config, debug=False, upload_files=False, copy_files_from=data['dag'])
def dag_stop(): data = request_data() provider = DagProvider(_write_session) id = int(data['id']) dag = provider.by_id(id, joined_load=['tasks']) for t in dag.tasks: celery_tasks.stop(logger, _write_session, t, dag) return {'dag': provider.get({'id': id})['data'][0]}
def work(self): project = ProjectProvider(self.session).by_id(self.project) self.info(f'Task = {self.train_task} child_task: {self.child_task}') model = Model( created=now(), name=self.name, project=self.project, equations='', fold=self.fold ) provider = ModelProvider(self.session) if self.train_task: task_provider = TaskProvider(self.session) dag_provider = DagProvider(self.session) task = task_provider.by_id(self.train_task) dag = dag_provider.by_id(task.dag) task_dir = join(TASK_FOLDER, str(self.child_task or task.id)) # get log directory config = yaml_load(dag.config) executor_config = config['executors'][task.executor] catalyst_config_file = executor_config['args']['config'] catalyst_config_file = join(task_dir, catalyst_config_file) catalyst_config = yaml_load(file=catalyst_config_file) catalyst_logdir = catalyst_config['args']['logdir'] model.score_local = task.score src_log = f'{task_dir}/{catalyst_logdir}' models_dir = join(MODEL_FOLDER, project.name) os.makedirs(models_dir, exist_ok=True) model_path_tmp = f'{src_log}/traced.pth' traced = trace_model_from_checkpoint(src_log, self, file=self.file) model_path = f'{models_dir}/{model.name}.pth' model_weight_path = f'{models_dir}/{model.name}_weight.pth' torch.jit.save(traced, model_path_tmp) shutil.copy(model_path_tmp, model_path) file = self.file = 'best_full' shutil.copy(f'{src_log}/checkpoints/{file}.pth', model_weight_path) provider.add(model)
class SegmentationReportBuilder: def __init__(self, session: Session, task: Task, layout: str, part: str = 'valid', name: str = 'img_segment', max_img_size: Tuple[int, int] = None, stack_type: str = 'vertical', main_metric: str = 'dice', plot_count: int = 0, colors: List[Tuple] = None): self.session = session self.task = task self.layout = layout self.part = part self.name = name or 'img_segment' self.max_img_size = max_img_size self.stack_type = stack_type self.main_metric = main_metric self.colors = colors self.plot_count = plot_count self.dag_provider = DagProvider(session) self.report_provider = ReportProvider(session) self.layout_provider = ReportLayoutProvider(session) self.task_provider = TaskProvider(session) self.report_img_provider = ReportImgProvider(session) self.report_task_provider = ReportTasksProvider(session) self.report_series_provider = ReportSeriesProvider(session) self.project = self.task_provider.project(task.id).id self.layout = self.layout_provider.by_name(layout) self.layout_dict = yaml_load(self.layout.content) self.create_base() def create_base(self): report = Report(config=yaml_dump(self.layout_dict), time=now(), layout=self.layout.name, project=self.project, name=self.name) self.report_provider.add(report) self.report_task_provider.add( ReportTasks(report=report.id, task=self.task.id)) self.task.report = report.id self.task_provider.update() def encode_pred(self, mask: np.array): res = np.zeros((*mask.shape[1:], 3), dtype=np.uint8) for i, c in enumerate(mask): c = np.repeat(c[:, :, None], 3, axis=2) color = self.colors[i] if self.colors is not None else (255, 255, 255) res += (c * color).astype(np.uint8) return res def plot_mask(self, img: np.array, mask: np.array): if len(img.shape) == 2: img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) img = img.astype(np.uint8) mask = mask.astype(np.uint8) for i, c in enumerate(mask): contours, _ = cv2.findContours(c, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) color = self.colors[i] if self.colors else (0, 255, 0) for i in range(0, len(contours)): cv2.polylines(img, contours[i], True, color, 2) return img def process_scores(self, scores): for key, item in self.layout_dict['items'].items(): item['name'] = key if item['type'] == 'series' and item['key'] in scores: series = ReportSeries(name=item['name'], value=scores[item['key']], epoch=0, time=now(), task=self.task.id, part='valid', stage='stage1') self.report_series_provider.add(series) def process_pred(self, imgs: np.array, preds: dict, targets: np.array = None, attrs=None, scores=None): for key, item in self.layout_dict['items'].items(): item['name'] = key if item['type'] != 'img_segment': continue report_imgs = [] dag = self.dag_provider.by_id(self.task.dag) for i in range(len(imgs)): if self.plot_count <= 0: break if targets is not None: img = self.plot_mask(imgs[i], targets[i]) else: img = imgs[i] imgs_add = [img] for key, value in preds.items(): imgs_add.append(self.encode_pred(value[i])) for j in range(len(imgs_add)): imgs_add[j] = resize_saving_ratio(imgs_add[j], self.max_img_size) if self.stack_type == 'horizontal': img = np.hstack(imgs_add) else: img = np.vstack(imgs_add) attr = attrs[i] if attrs else {} score = None if targets is not None: score = scores[self.main_metric][i] retval, buffer = cv2.imencode('.jpg', img) report_img = ReportImg(group=item['name'], epoch=0, task=self.task.id, img=buffer, dag=self.task.dag, part=self.part, project=self.project, score=score, **attr) self.plot_count -= 1 report_imgs.append(report_img) dag.img_size += report_img.size self.dag_provider.commit() self.report_img_provider.bulk_save_objects(report_imgs)
def dag_start(): data = request_data() provider = DagProvider(_write_session) task_provider = TaskProvider(_write_session) id = int(data['id']) dag = provider.by_id(id, joined_load=['tasks']) can_start_statuses = [ TaskStatus.Failed.value, TaskStatus.Skipped.value, TaskStatus.Stopped.value ] tasks = list(dag.tasks) def find_resume(task): children = task_provider.children(task.id) children = sorted(children, key=lambda x: x.id, reverse=True) if len(children) > 0: for c in children: if c.parent != task.id: continue info = yaml_load(c.additional_info) if 'distr_info' not in info: continue if info['distr_info']['rank'] == 0: return { 'master_computer': c.computer_assigned, 'master_task_id': c.id, 'load_last': True } raise Exception('Master task not found') else: return { 'master_computer': task.computer_assigned, 'master_task_id': task.id, 'load_last': True } for t in tasks: if t.status not in can_start_statuses: continue if t.parent: continue info = yaml_load(t.additional_info) info['resume'] = find_resume(t) t.additional_info = yaml_dump(info) t.status = TaskStatus.NotRan.value t.pid = None t.started = None t.finished = None t.computer_assigned = None t.celery_id = None t.worker_index = None t.docker_assigned = None provider.commit()
class SupervisorBuilder: def __init__(self): self.session = Session.create_session(key='SupervisorBuilder') self.logger = create_logger(self.session, 'SupervisorBuilder') self.provider = None self.computer_provider = None self.docker_provider = None self.auxiliary_provider = None self.dag_provider = None self.queues = None self.not_ran_tasks = None self.dep_status = None self.computers = None self.auxiliary = {} self.tasks = [] self.tasks_stop = [] self.dags_start = [] self.sent_tasks = 0 def create_base(self): self.session.commit() self.provider = TaskProvider(self.session) self.computer_provider = ComputerProvider(self.session) self.docker_provider = DockerProvider(self.session) self.auxiliary_provider = AuxiliaryProvider(self.session) self.dag_provider = DagProvider(self.session) self.queues = [ f'{d.computer}_{d.name}' for d in self.docker_provider.all() if d.last_activity >= now() - datetime.timedelta(seconds=15) ] self.auxiliary['queues'] = self.queues def load_tasks(self): self.tasks = self.provider.by_status(TaskStatus.NotRan, TaskStatus.InProgress, TaskStatus.Queued) not_ran_tasks = [t for t in self.tasks if t.status == TaskStatus.NotRan.value] self.not_ran_tasks = [task for task in not_ran_tasks if not task.debug] self.not_ran_tasks = sorted( self.not_ran_tasks, key=lambda x: x.gpu or 0, reverse=True) self.logger.debug( f'Found {len(not_ran_tasks)} not ran tasks', ComponentType.Supervisor ) self.dep_status = self.provider.dependency_status(self.not_ran_tasks) self.auxiliary['not_ran_tasks'] = [ { 'id': t.id, 'name': t.name, 'dep_status': [ TaskStatus(s).name for s in self.dep_status.get(t.id, set()) ] } for t in not_ran_tasks[:5] ] def load_computers(self): computers = self.computer_provider.computers() for computer in computers.values(): computer['gpu'] = [0] * computer['gpu'] computer['ports'] = set() computer['cpu_total'] = computer['cpu'] computer['memory_total'] = computer['memory'] computer['gpu_total'] = len(computer['gpu']) computer['can_process_tasks'] = computer['can_process_tasks'] tasks = [ t for t in self.tasks if t.status in [TaskStatus.InProgress.value, TaskStatus.Queued.value] ] for task in tasks: if task.computer_assigned is None: continue assigned = task.computer_assigned comp_assigned = computers[assigned] comp_assigned['cpu'] -= task.cpu if task.gpu_assigned is not None: for g in task.gpu_assigned.split(','): comp_assigned['gpu'][int(g)] = task.id comp_assigned['memory'] -= task.memory * 1024 info = yaml_load(task.additional_info) if 'distr_info' in info: dist_info = info['distr_info'] if dist_info['rank'] == 0: comp_assigned['ports'].add(dist_info['master_port']) self.computers = [ { **value, 'name': name } for name, value in computers.items() ] self.auxiliary['computers'] = self.computers def process_to_celery(self, task: Task, queue: str, computer: dict): r = execute.apply_async((task.id,), queue=queue, retry=False) task.status = TaskStatus.Queued.value task.computer_assigned = computer['name'] task.celery_id = r.id if task.computer_assigned is not None: if task.gpu_assigned: for g in map(int, task.gpu_assigned.split(',')): computer['gpu'][g] = task.id computer['cpu'] -= task.cpu computer['memory'] -= task.memory * 1024 self.logger.info( f'Sent task={task.id} to celery. Queue = {queue} ' f'Task status = {task.status} Celery_id = {r.id}', ComponentType.Supervisor) self.provider.update() def create_service_task( self, task: Task, gpu_assigned=None, distr_info: dict = None, resume: dict = None ): new_task = Task( name=task.name, computer=task.computer, executor=task.executor, status=TaskStatus.NotRan.value, type=TaskType.Service.value, gpu_assigned=gpu_assigned, parent=task.id, report=task.report, dag=task.dag ) new_task.additional_info = task.additional_info if distr_info: additional_info = yaml_load(new_task.additional_info) additional_info['distr_info'] = distr_info new_task.additional_info = yaml_dump(additional_info) if resume: additional_info = yaml_load(new_task.additional_info) additional_info['resume'] = resume new_task.additional_info = yaml_dump(additional_info) return self.provider.add(new_task) def find_port(self, c: dict, docker_name: str): docker = self.docker_provider.get(c['name'], docker_name) ports = list(map(int, docker.ports.split('-'))) for p in range(ports[0], ports[1] + 1): if p not in c['ports']: return p raise Exception(f'All ports in {c["name"]} are taken') def _process_task_valid_computer(self, task: Task, c: dict, single_node: bool): if not c['can_process_tasks']: return 'this computer can not process tasks' if task.computer is not None and task.computer != c['name']: return 'name set in the config!= name of this computer' if task.cpu > c['cpu']: return f'task cpu = {task.cpu} > computer' \ f' free cpu = {c["cpu"]}' if task.memory > c['memory']: return f'task cpu = {task.cpu} > computer ' \ f'free memory = {c["memory"]}' queue = f'{c["name"]}_' \ f'{task.dag_rel.docker_img or "default"}' if queue not in self.queues: return f'required queue = {queue} not in queues' if task.gpu > 0 and not any(g == 0 for g in c['gpu']): return f'task requires gpu, but there is not any free' free_gpu = sum(g == 0 for g in c['gpu']) if single_node and task.gpu > free_gpu: return f'task requires {task.gpu} ' \ f'but there are only {free_gpu} free' def _process_task_get_computers( self, executor: dict, task: Task, auxiliary: dict ): single_node = executor.get('single_node', True) computers = [] for c in self.computers: error = self._process_task_valid_computer(task, c, single_node) auxiliary['computers'].append({'name': c['name'], 'error': error}) if not error: computers.append(c) if task.gpu > 0 and single_node and len(computers) > 0: computers = sorted( computers, key=lambda x: sum(g == 0 for g in c['gpu']), reverse=True )[:1] free_gpu = sum(sum(g == 0 for g in c['gpu']) for c in computers) if task.gpu > free_gpu: auxiliary['not_valid'] = f'gpu required by the ' \ f'task = {task.gpu},' \ f' but there are only {free_gpu} ' \ f'free gpus' return [] return computers def _process_task_to_send( self, executor: dict, task: Task, computers: List[dict] ): distr = executor.get('distr', True) to_send = [] for computer in computers: queue = f'{computer["name"]}_' \ f'{task.dag_rel.docker_img or "default"}' if task.gpu_max > 1 and distr: for index, task_taken_gpu in enumerate(computer['gpu']): if task_taken_gpu: continue to_send.append([computer, queue, index]) if len(to_send) >= task.gpu_max: break if len(to_send) >= task.gpu_max: break elif task.gpu_max > 0: cuda_devices = [] for index, task_taken_gpu in enumerate(computer['gpu']): if task_taken_gpu: continue cuda_devices.append(index) if len(cuda_devices) >= task.gpu_max: break task.gpu_assigned = ','.join(map(str, cuda_devices)) self.process_to_celery(task, queue, computer) else: self.process_to_celery(task, queue, computer) break return to_send def process_task(self, task: Task): auxiliary = self.auxiliary['process_tasks'][-1] auxiliary['computers'] = [] config = yaml_load(task.dag_rel.config) executor = config['executors'][task.executor] computers = self._process_task_get_computers(executor, task, auxiliary) if len(computers) == 0: return to_send = self._process_task_to_send(executor, task, computers) auxiliary['to_send'] = to_send[:5] additional_info = yaml_load(task.additional_info) rank = 0 master_port = None if len(to_send) > 0: master_port = self.find_port( to_send[0][0], to_send[0][1].split('_')[1] ) computer_names = {c['name'] for c, _, __ in to_send} if len(computer_names) == 1: task.computer_assigned = list(computer_names)[0] for computer, queue, gpu_assigned in to_send: main_cmp = to_send[0][0] # noinspection PyTypeChecker ip = 'localhost' if computer['name'] == main_cmp['name'] \ else main_cmp['ip'] distr_info = { 'master_addr': ip, 'rank': rank, 'local_rank': gpu_assigned, 'master_port': master_port, 'world_size': len(to_send), 'master_computer': main_cmp['name'] } service_task = self.create_service_task( task, distr_info=distr_info, gpu_assigned=gpu_assigned, resume=additional_info.get('resume') ) self.process_to_celery(service_task, queue, computer) rank += 1 main_cmp['ports'].add(master_port) if len(to_send) > 0: task.status = TaskStatus.Queued.value self.sent_tasks += len(to_send) def process_tasks(self): self.auxiliary['process_tasks'] = [] for task in self.not_ran_tasks: auxiliary = {'id': task.id, 'name': task.name} self.auxiliary['process_tasks'].append(auxiliary) if task.dag_rel is None: task.dag_rel = self.dag_provider.by_id(task.dag) if TaskStatus.Stopped.value in self.dep_status[task.id] \ or TaskStatus.Failed.value in self.dep_status[task.id] or \ TaskStatus.Skipped.value in self.dep_status[task.id]: auxiliary['not_valid'] = 'stopped or failed in dep_status' self.provider.change_status(task, TaskStatus.Skipped) continue if len(self.dep_status[task.id]) != 0 \ and self.dep_status[task.id] != {TaskStatus.Success.value}: auxiliary['not_valid'] = 'not all dep tasks are finished' continue self.process_task(task) self.auxiliary['process_tasks'] = self.auxiliary['process_tasks'][:5] def _stop_child_tasks(self, task: Task): self.provider.commit() children = self.provider.children(task.id, [Task.dag_rel]) dags = [c.dag_rel for c in children] for c, d in zip(children, dags): celery_tasks.stop(self.logger, self.session, c, d) def process_parent_tasks(self): tasks = self.provider.parent_tasks_stats() was_change = False for task, started, finished, statuses in tasks: status = task.status if statuses[TaskStatus.Failed] > 0: status = TaskStatus.Failed.value elif statuses[TaskStatus.Skipped] > 0: status = TaskStatus.Skipped.value elif statuses[TaskStatus.Queued] > 0: status = TaskStatus.Queued.value elif statuses[TaskStatus.InProgress] > 0: status = TaskStatus.InProgress.value elif statuses[TaskStatus.Success] > 0: status = TaskStatus.Success.value if status != task.status: if status == TaskStatus.InProgress.value: task.started = started elif status >= TaskStatus.Failed.value: task.started = started task.finished = finished self._stop_child_tasks(task) was_change = True task.status = status if was_change: self.provider.commit() self.auxiliary['parent_tasks_stats'] = [ { 'name': task.name, 'id': task.id, 'started': task.started, 'finished': finished, 'statuses': [ { 'name': k.name, 'count': v } for k, v in statuses.items() ], } for task, started, finished, statuses in tasks[:5] ] def write_auxiliary(self): self.auxiliary['duration'] = (now() - self.auxiliary['time']). \ total_seconds() auxiliary = Auxiliary( name='supervisor', data=yaml_dump(self.auxiliary) ) if len(auxiliary.data) > 16000: return self.auxiliary_provider.create_or_update(auxiliary, 'name') def stop_tasks(self, tasks: List[Task]): self.tasks_stop.extend([t.id for t in tasks]) def process_stop_tasks(self): # Stop not running tasks if len(self.tasks_stop) == 0: return tasks = self.provider.by_ids(self.tasks_stop) tasks_not_ran = [t.id for t in tasks if t.status in [TaskStatus.NotRan.value, TaskStatus.Queued.value]] tasks_started = [t for t in tasks if t.status in [TaskStatus.InProgress.value]] tasks_started_ids = [t.id for t in tasks_started] self.provider.change_status_all(tasks=tasks_not_ran, status=TaskStatus.Skipped) pids = [] for task in tasks_started: if task.pid: pids.append((task.computer_assigned, task.pid)) additional_info = yaml_load(task.additional_info) for p in additional_info.get('child_processes', []): pids.append((task.computer_assigned, p)) for computer, queue in self.docker_provider.queues_online(): pids_computer = [p for c, p in pids if c == computer] if len(pids_computer) > 0: celery_tasks.kill_all.apply_async((pids_computer,), queue=queue, retry=False) self.provider.change_status_all(tasks=tasks_started_ids, status=TaskStatus.Stopped) self.tasks_stop = [] def fast_check(self): if self.provider is None or self.computer_provider is None: return False if self.not_ran_tasks is None or self.queues is None: return False if len(self.tasks_stop) > 0: return False if len(self.dags_start) > 0: return False if len(self.auxiliary.get('to_send', [])) > 0: return False queues = set([ f'{d.computer}_{d.name}' for d in self.docker_provider.all() if d.last_activity >= now() - datetime.timedelta(seconds=15) ]) queues_set = set(queues) queues_set2 = set(self.queues) if queues_set != queues_set2: return False tasks = self.provider.by_status(TaskStatus.NotRan, TaskStatus.Queued, TaskStatus.InProgress) tasks_set = {t.id for t in tasks if t.status == TaskStatus.NotRan.value and not t.debug} tasks_set2 = {t.id for t in self.tasks if t.status == TaskStatus.NotRan.value} if tasks_set != tasks_set2: return False tasks_set = {t.id for t in tasks if t.status == TaskStatus.InProgress.value} tasks_set2 = {t.id for t in self.tasks if t.status == TaskStatus.InProgress.value} if tasks_set != tasks_set2: return False tasks_set = {t.id for t in tasks if t.status == TaskStatus.Queued.value} tasks_set2 = {t.id for t in self.tasks if t.status == TaskStatus.Queued.value} if tasks_set != tasks_set2: return False return True def start_dag(self, id: int): self.dags_start.append(id) def process_start_dags(self): if len(self.dags_start) == 0: return for id in self.dags_start: can_start_statuses = [ TaskStatus.Failed.value, TaskStatus.Skipped.value, TaskStatus.Stopped.value ] tasks = self.provider.by_dag(id) children_all = self.provider.children([t.id for t in tasks]) def find_resume(task): children = [c for c in children_all if c.parent == task.id] children = sorted(children, key=lambda x: x.id, reverse=True) if len(children) > 0: for c in children: if c.parent != task.id: continue info = yaml_load(c.additional_info) if 'distr_info' not in info: continue if info['distr_info']['rank'] == 0: return { 'master_computer': c.computer_assigned, 'master_task_id': c.id, 'load_last': True } raise Exception('Master task not found') else: return { 'master_computer': task.computer_assigned, 'master_task_id': task.id, 'load_last': True } for t in tasks: if t.status not in can_start_statuses: continue if t.parent: continue if t.type == TaskType.Train.value: info = yaml_load(t.additional_info) info['resume'] = find_resume(t) t.additional_info = yaml_dump(info) t.status = TaskStatus.NotRan.value t.pid = None t.started = None t.finished = None t.computer_assigned = None t.celery_id = None t.worker_index = None t.docker_assigned = None self.provider.commit() self.dags_start = [] def build(self): try: # if self.fast_check(): # return self.auxiliary = {'time': now()} self.create_base() self.process_stop_tasks() self.process_start_dags() self.process_parent_tasks() self.load_tasks() self.load_computers() self.process_tasks() self.write_auxiliary() except ObjectDeletedError: pass except Exception as e: if Session.sqlalchemy_error(e): Session.cleanup(key='SupervisorBuilder') self.session = Session.create_session(key='SupervisorBuilder') self.logger = create_logger(self.session, 'SupervisorBuilder') self.logger.error(traceback.format_exc(), ComponentType.Supervisor)
class DagCopyBuilder: def __init__(self, session: Session, dag: int, file_changes: str = '', dag_suffix: str = '', logger=None, component: ComponentType = None): self.dag = dag self.file_changes = file_changes self.session = session self.logger = logger self.component = component self.dag_suffix = dag_suffix self.dag_db = None self.dag_provider = None self.task_provider = None self.file_provider = None self.dag_storage_provider = None def log_info(self, message: str): if self.logger: self.logger.info(message, self.component) def create_providers(self): self.log_info('create_providers') self.dag_provider = DagProvider(self.session) self.task_provider = TaskProvider(self.session) self.file_provider = FileProvider(self.session) self.dag_storage_provider = DagStorageProvider(self.session) def create_dag(self): dag = self.dag_provider.by_id(self.dag) name = dag.name if self.dag_suffix: name += ' ' + self.dag_suffix dag_new = Dag(name=name, created=now(), config=dag.config, project=dag.project, docker_img=dag.docker_img, img_size=0, file_size=0, type=dag.type) self.dag_provider.add(dag_new) self.dag_db = dag_new def find_replace(self, changes: dict, path: str): for k, v in changes.items(): if not re.match(k, path): continue return v def create_tasks(self): tasks = self.task_provider.by_dag(self.dag) tasks_new = [] tasks_old = [] for t in tasks: if t.parent: continue task = Task( name=t.name, status=TaskStatus.NotRan.value, computer=t.computer, gpu=t.gpu, gpu_max=t.gpu_max, cpu=t.cpu, executor=t.executor, memory=t.memory, steps=t.steps, dag=self.dag_db.id, debug=t.debug, type=t.type, ) task.additional_info = t.additional_info tasks_new.append(task) tasks_old.append(t) self.task_provider.bulk_save_objects(tasks_new, return_defaults=True) old2new = { t_old.id: t_new.id for t_new, t_old in zip(tasks_new, tasks_old) } dependencies = self.task_provider.get_dependencies(self.dag) dependencies_new = [] for d in dependencies: d_new = TaskDependence(task_id=old2new[d.task_id], depend_id=old2new[d.depend_id]) dependencies_new.append(d_new) self.task_provider.bulk_save_objects(dependencies_new, return_defaults=False) changes = yaml_load(self.file_changes) storages = self.dag_storage_provider.by_dag(self.dag) storages_new = [] for s, f in storages: if not isinstance(changes, dict): continue replace = self.find_replace(changes, s.path) if replace is not None and f: content = f.content.decode('utf-8') if s.path.endswith('.yml'): data = yaml_load(content) data = merge_dicts_smart(data, replace) content = yaml_dump(data) else: for k, v in replace: if k not in content: raise Exception(f'{k} is not in the content') content = content.replace(k, v) content = content.encode('utf-8') md5 = hashlib.md5(content).hexdigest() f = self.file_provider.by_md5(md5) if not f: f = File(content=content, created=now(), project=self.dag_db.project, md5=md5, dag=self.dag_db.id) self.file_provider.add(f) s_new = DagStorage(dag=self.dag_db.id, file=f.id, path=s.path, is_dir=s.is_dir) storages_new.append(s_new) self.dag_storage_provider.bulk_save_objects(storages_new, return_defaults=False) def build(self): self.create_providers() self.create_dag() self.create_tasks()
def file_before_create(mapper, connection, target): provider = DagProvider(_session) dag = provider.by_id(target.dag) dag.file_size += target.size provider.commit()
class ClassificationReportBuilder: def __init__(self, session: Session, task: Task, layout: str, part: str = 'valid', name: str = 'img_classify', max_img_size: Tuple[int, int] = None, main_metric: str = 'accuracy', plot_count: int = 0): self.session = session self.task = task self.layout = layout self.part = part self.name = name or 'img_classify' self.max_img_size = max_img_size self.main_metric = main_metric self.plot_count = plot_count self.dag_provider = DagProvider(session) self.report_provider = ReportProvider(session) self.layout_provider = ReportLayoutProvider(session) self.task_provider = TaskProvider(session) self.report_img_provider = ReportImgProvider(session) self.report_task_provider = ReportTasksProvider(session) self.report_series_provider = ReportSeriesProvider(session) self.project = self.task_provider.project(task.id).id self.layout = self.layout_provider.by_name(layout) self.layout_dict = yaml_load(self.layout.content) def create_base(self): report = Report(config=yaml_dump(self.layout_dict), time=now(), layout=self.layout.name, project=self.project, name=self.name) self.report_provider.add(report) self.report_task_provider.add( ReportTasks(report=report.id, task=self.task.id)) self.task.report = report.id self.task_provider.update() def process_scores(self, scores): for key, item in self.layout_dict['items'].items(): item['name'] = key if item['type'] == 'series' and item['key'] in scores: series = ReportSeries(name=item['name'], value=float(scores[item['key']]), epoch=0, time=now(), task=self.task.id, part='valid', stage='stage1') self.report_series_provider.add(series) def process_pred(self, imgs: np.array, preds: np.array, targets: np.array = None, attrs=None, scores=None): for key, item in self.layout_dict['items'].items(): item['name'] = key if item['type'] != 'img_classify': continue report_imgs = [] dag = self.dag_provider.by_id(self.task.dag) for i in range(len(imgs)): if self.plot_count <= 0: break img = resize_saving_ratio(imgs[i], self.max_img_size) pred = preds[i] attr = attrs[i] if attrs else {} y = None score = None if targets is not None: y = targets[i] score = float(scores[self.main_metric][i]) y_pred = pred.argmax() retval, buffer = cv2.imencode('.jpg', img) report_img = ReportImg(group=item['name'], epoch=0, task=self.task.id, img=buffer, dag=self.task.dag, part=self.part, project=self.project, y_pred=y_pred, y=y, score=score, **attr) report_imgs.append(report_img) dag.img_size += report_img.size self.dag_provider.commit() self.report_img_provider.bulk_save_objects(report_imgs) if targets is not None and item.get('confusion_matrix'): matrix = confusion_matrix(targets, preds.argmax(axis=1), labels=np.arange(preds.shape[1])) matrix = np.array(matrix) c = {'data': matrix} obj = ReportImg(group=item['name'] + '_confusion', epoch=0, task=self.task.id, img=pickle.dumps(c), project=self.project, dag=self.task.dag, part=self.part) self.report_img_provider.add(obj) self.plot_count -= 1