easycv/models/detection3d/detectors/bevformer/bevformer_head.py (3 lines):
	- line 274: if only_bev:  # only use encoder to obtain BEV features, TODO: refine the workaround
	- line 326: # TODO: check the shape of reference
	- line 369: # TODO: check if using sigmoid


easycv/toolkit/torchacc/convert_ops.py (3 lines):
	- line 166: # TODO: add initialize attribute
	- line 339: # TODO: remove it, fix torch.tensor to adapt torch.jit
	- line 349: # TODO: remove it, fix torch.cat to support multiple types of arguments


easycv/core/visualization/open3d_vis.py (3 lines):
	- line 163: # TODO: support score and class info
	- line 235: # TODO: fix problem of current coordinate system
	- line 305: # TODO: support score and class info


easycv/models/segmentation/utils/criterion.py (3 lines):
	- line 50: # TODO make this more general
	- line 57: # TODO make it support different-sized images
	- line 243: # TODO use valid to mask invalid areas due to padding in loss


easycv/core/optimizer/lamb.py (2 lines):
	- line 88: # FIXME it'd be nice to remove explicit tensor conversion of scalars
	- line 152: # FIXME nested where required since logical and/or not


easycv/models/loss/iou_loss.py (2 lines):
	- line 280: # TODO: remove this in the future
	- line 321: # TODO: remove this in the future


easycv/predictors/reid_predictor.py (2 lines):
	- line 109: # TODO: fault tolerance
	- line 134: # TODO: support append to file


easycv/utils/ms_utils.py (2 lines):
	- line 38: # TODO: support multi eval_pipelines
	- line 39: # TODO: support for adding customized required keys to the configuration file


easycv/core/visualization/image.py (2 lines):
	- line 89: # TODO: Unify the font of cv2 and PIL, and auto get font_size according to the font_scale
	- line 177: # TODO: Unify the font of cv2 and PIL, and auto get font_size according to the font_scale


easycv/datasets/detection/pipelines/mm_transforms.py (2 lines):
	- line 871: # TODO: refactor the override option in Resize
	- line 2144: # TODO: add more filter options


easycv/datasets/classification/data_sources/class_list.py (2 lines):
	- line 44: # TODO: support return list, donot save split file
	- line 45: # TODO: support loading list_file that have already been split


easycv/hooks/sync_random_size_hook.py (2 lines):
	- line 27: # TODO need to fix some bugs, to update by 10 iters but when training update by 1 epoch
	- line 61: # TODO some bugs need fix, to update by 10 iters but when training update by 1 epoch


easycv/models/selfsup/dino.py (2 lines):
	- line 277: # TODO: unify the use of init_weight
	- line 383: # TODO: fix extract feature


easycv/predictors/base.py (2 lines):
	- line 418: # TODO: fault tolerance
	- line 444: # TODO: support append to file


easycv/datasets/classification/data_sources/image_list.py (2 lines):
	- line 70: # TODO: support return list, donot save split file
	- line 71: # TODO: support loading list_file that have already been split


easycv/datasets/shared/pipelines/third_transforms_wrapper.py (1 line):
	- line 60: # TODO: find a more pretty way to wrap third transfomrs or import fixed api to warp


easycv/datasets/shared/__init__.py (1 line):
	- line 17: # TODO: merge `DaliImageNetTFRecordDataSet` and `DaliTFRecordMultiViewDataset`


easycv/datasets/classification/raw.py (1 line):
	- line 81: # TODO: support img_metas for torch.jit


easycv/datasets/shared/pipelines/dali_transforms.py (1 line):
	- line 149: # TODO: support random crop_pos by iter


easycv/toolkit/modelscope/trainers/trainer.py (1 line):
	- line 116: # TODO: use ast index to detect whether the hook is in modelscope


easycv/predictors/pose_predictor.py (1 line):
	- line 306: # TODO: Fix when multi people are detected in each sample,


easycv/datasets/detection3d/nuscenes_dataset.py (1 line):
	- line 456: # TODO: check whether this is necessary


easycv/models/backbones/efficientformer.py (1 line):
	- line 487: # TODO: support kd pipeline


easycv/models/loss/set_criterion/set_criterion.py (1 line):
	- line 85: # TODO this should probably be a separate loss, not hacked in this one here


easycv/models/backbones/swin_transformer_dynamic.py (1 line):
	- line 569: # # FIXME look at relaxing size constraints


easycv/datasets/loader/build_loader.py (1 line):
	- line 111: data_source=dataset) if shuffle else None  # TODO: set replace


easycv/models/detection/detectors/fcos/fcos_head.py (1 line):
	- line 489: # TODO: figure out why these two are different


easycv/datasets/selfsup/data_sources/imagenet_feature.py (1 line):
	- line 43: # TODO: multiprocess loading to accelerate


easycv/toolkit/modelscope/pipelines/base.py (1 line):
	- line 86: # TODO: refine config compatibility problems


easycv/utils/dist_utils.py (1 line):
	- line 110: # TODO: May try not to use gloo in the future


easycv/models/backbones/xcit_transformer.py (1 line):
	- line 257: # FIXME: A hack for models pre-trained with layernorm over all the tokens not just the CLS


easycv/predictors/wholebody_keypoints_predictor.py (1 line):
	- line 190: # TODO: Fix when multi people are detected in each sample,


easycv/core/post_processing/merge_augs.py (1 line):
	- line 60: # TODO: use a more elegent way to deal with nms


easycv/models/classification/classification.py (1 line):
	- line 298: # TODO: support Dict[any, any] type of img_metas


easycv/predictors/hand_keypoints_predictor.py (1 line):
	- line 126: # TODO: support multi bboxes for a single sample


easycv/models/utils/x3d_transformer.py (1 line):
	- line 74: # TODO: change the name to `norm`


easycv/models/loss/cross_entropy_loss.py (1 line):
	- line 215: # TODO: handle these two reserved arguments


easycv/file/file_io.py (1 line):
	- line 280: # TODO: 网络不稳时try，其他错误直接抛出


easycv/datasets/pose/data_sources/top_down.py (1 line):
	- line 350: # TODO: optimize fault tolerance for image load


configs/config_templates/yolox_itag.py (1 line):
	- line 19: # TODO: merge `img_size` and `img_scale`, support tuple `image_size` for `DetSourcePAI`


easycv/hooks/optimizer_hook.py (1 line):
	- line 146: # TODO: find a more pretty way to adapt mmdet