From 9449178cf0ba6274354efc8fa4f4393e209897f6 Mon Sep 17 00:00:00 2001 From: "q.yao" Date: Tue, 6 Dec 2022 14:07:10 +0800 Subject: [PATCH] suppress mmengine scope warning (#1450) --- mmdeploy/codebase/base/mmcodebase.py | 5 ++-- mmdeploy/codebase/base/task.py | 24 +------------------ .../codebase/mmcls/deploy/classification.py | 11 ++------- .../codebase/mmdet/deploy/object_detection.py | 11 +++------ .../mmpose/deploy/pose_detection_model.py | 5 ---- .../mmseg/deploy/segmentation_model.py | 5 ---- 6 files changed, 9 insertions(+), 52 deletions(-) diff --git a/mmdeploy/codebase/base/mmcodebase.py b/mmdeploy/codebase/base/mmcodebase.py index 5130ba37c..04beae313 100644 --- a/mmdeploy/codebase/base/mmcodebase.py +++ b/mmdeploy/codebase/base/mmcodebase.py @@ -47,7 +47,8 @@ class MMCodebase(metaclass=ABCMeta): type=task.value, model_cfg=model_cfg, deploy_cfg=deploy_cfg, - device=device)) + device=device, + _scope_='mmdeploy')) @classmethod def register_deploy_modules(cls): @@ -83,4 +84,4 @@ def get_codebase_class(codebase: Codebase) -> MMCodebase: logger.warn(f'Import mmdeploy.codebase.{codebase.value}.deploy failed' 'Please check whether the module is the custom module.' f'{e}') - return CODEBASE.build({'type': codebase.value}) + return CODEBASE.build({'type': codebase.value, '_scope_': 'mmdeploy'}) diff --git a/mmdeploy/codebase/base/task.py b/mmdeploy/codebase/base/task.py index 87fe21e6f..f5f78a8e5 100644 --- a/mmdeploy/codebase/base/task.py +++ b/mmdeploy/codebase/base/task.py @@ -13,7 +13,6 @@ from torch.utils.data import DataLoader, Dataset from mmdeploy.utils import (get_backend_config, get_codebase, get_codebase_config, get_root_logger) -from mmdeploy.utils.config_utils import get_codebase_external_module from mmdeploy.utils.dataset import is_can_sort_dataset, sort_dataset @@ -24,36 +23,15 @@ class BaseTask(metaclass=ABCMeta): model_cfg (str | Config): Model config file. deploy_cfg (str | Config): Deployment config file. device (str): A string specifying device type. - experiment_name (str, optional): Name of current experiment. - If not specified, timestamp will be used as - ``experiment_name``. Defaults to ``None``. """ - def __init__(self, - model_cfg: Config, - deploy_cfg: Config, - device: str, - experiment_name: str = 'BaseTask'): + def __init__(self, model_cfg: Config, deploy_cfg: Config, device: str): self.model_cfg = model_cfg self.deploy_cfg = deploy_cfg self.device = device self.codebase = get_codebase(deploy_cfg) - self.experiment_name = experiment_name - - # init scope - from .. import import_codebase - custom_module_list = get_codebase_external_module(deploy_cfg) - import_codebase(self.codebase, custom_module_list) - - from mmengine.registry import DefaultScope - if not DefaultScope.check_instance_created(self.experiment_name): - self.scope = DefaultScope.get_instance( - self.experiment_name, - scope_name=self.model_cfg.get('default_scope')) - else: - self.scope = DefaultScope.get_instance(self.experiment_name) # lazy build visualizer self.visualizer = self.model_cfg.get('visualizer', None) diff --git a/mmdeploy/codebase/mmcls/deploy/classification.py b/mmdeploy/codebase/mmcls/deploy/classification.py index 2977a98b8..88c6d4b62 100644 --- a/mmdeploy/codebase/mmcls/deploy/classification.py +++ b/mmdeploy/codebase/mmcls/deploy/classification.py @@ -118,17 +118,10 @@ class Classification(BaseTask): deploy_cfg (Config): Deployment config file or loaded Config object. device (str): A string represents device type. - experiment_name (str, optional): The experiment name used to create - runner. Defaults to 'Classification'. """ - def __init__(self, - model_cfg: Config, - deploy_cfg: Config, - device: str, - experiment_name: str = 'Classification'): - super(Classification, self).__init__(model_cfg, deploy_cfg, device, - experiment_name) + def __init__(self, model_cfg: Config, deploy_cfg: Config, device: str): + super(Classification, self).__init__(model_cfg, deploy_cfg, device) def build_data_preprocessor(self): """Build data preprocessor. diff --git a/mmdeploy/codebase/mmdet/deploy/object_detection.py b/mmdeploy/codebase/mmdet/deploy/object_detection.py index e8a661bd7..1527a01ef 100644 --- a/mmdeploy/codebase/mmdet/deploy/object_detection.py +++ b/mmdeploy/codebase/mmdet/deploy/object_detection.py @@ -122,16 +122,11 @@ class ObjectDetection(BaseTask): model_cfg (Config): The config of the model in mmdet. deploy_cfg (Config): The config of deployment. device (str): Device name. - experiment_name (str, optional): The experiment name used to create - runner. Defaults to 'ObjectDetection'. """ - def __init__(self, - model_cfg: Config, - deploy_cfg: Config, - device: str, - experiment_name: str = 'ObjectDetection') -> None: - super().__init__(model_cfg, deploy_cfg, device, experiment_name) + def __init__(self, model_cfg: Config, deploy_cfg: Config, + device: str) -> None: + super().__init__(model_cfg, deploy_cfg, device) def build_backend_model(self, model_files: Optional[str] = None, diff --git a/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py b/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py index 7704cab74..bb64fced9 100644 --- a/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py +++ b/mmdeploy/codebase/mmpose/deploy/pose_detection_model.py @@ -14,11 +14,6 @@ from mmdeploy.codebase.base import BaseBackendModel from mmdeploy.utils import (Backend, get_backend, get_codebase_config, load_config) - -def __build_backend_model(cls_name: str, registry: Registry, *args, **kwargs): - return registry.module_dict[cls_name](*args, **kwargs) - - __BACKEND_MODEL = Registry('backend_segmentors') diff --git a/mmdeploy/codebase/mmseg/deploy/segmentation_model.py b/mmdeploy/codebase/mmseg/deploy/segmentation_model.py index 5ad1c9657..320c0b4cd 100644 --- a/mmdeploy/codebase/mmseg/deploy/segmentation_model.py +++ b/mmdeploy/codebase/mmseg/deploy/segmentation_model.py @@ -12,11 +12,6 @@ from mmdeploy.codebase.base import BaseBackendModel from mmdeploy.utils import (Backend, get_backend, get_codebase_config, get_root_logger, load_config) - -def __build_backend_model(cls_name: str, registry: Registry, *args, **kwargs): - return registry.module_dict[cls_name](*args, **kwargs) - - __BACKEND_MODEL = Registry('backend_segmentors')