109 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (43:153, 38%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (27:138, 89%) 63 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (78:142, 23%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (73:138, 51%) 63 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (94:159, 26%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (73:138, 51%) 56 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (73:129, 23%) - configs/detection/vitdet/vitdet_mask_rcnn.py (67:123, 38%) 51 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:198, 18%) - configs/detection/vitdet/lsj_coco_instance.py (1:55, 47%) 47 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (58:106, 30%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (80:127, 28%) 47 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (58:106, 30%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12aug.py (78:125, 29%) 44 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (199:245, 16%) - configs/detection/vitdet/lsj_coco_instance.py (57:103, 40%) 35 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (78:113, 12%) - configs/detection/vitdet/vitdet_mask_rcnn.py (88:123, 24%) 35 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (89:124, 12%) - configs/detection/vitdet/vitdet_mask_rcnn.py (88:123, 24%) 34 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (195:230, 14%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (140:176, 15%) 30 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:177, 11%) - configs/detection/vitdet/lsj_coco_detection.py (1:34, 28%) 29 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (85:113, 10%) - configs/detection/vitdet/vitdet_faster_rcnn.py (81:109, 22%) 29 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (101:129, 12%) - configs/detection/vitdet/vitdet_faster_rcnn.py (81:109, 22%) 29 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (96:124, 10%) - configs/detection/vitdet/vitdet_faster_rcnn.py (81:109, 22%) 29 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (86:115, 12%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (124:153, 12%) 28 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (73:104, 22%) - configs/classification/imagenet/timm/timm_config.py (55:86, 29%) 28 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (28:56, 10%) - configs/detection/vitdet/vitdet_faster_rcnn.py (39:66, 21%) 28 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (28:56, 10%) - configs/detection/vitdet/vitdet_mask_rcnn.py (39:66, 19%) 27 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (201:228, 9%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (150:179, 10%) 27 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (45:71, 11%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (26:52, 22%) 27 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (68:96, 17%) - configs/segmentation/segformer/segformer_b0_coco.py (127:155, 11%) 26 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (68:94, 16%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e127_semantic.py (151:177, 11%) 24 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:104, 19%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (64:90, 25%) 24 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (183:208, 10%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (153:179, 9%) 23 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (131:154, 9%) - configs/detection/vitdet/vitdet_mask_rcnn.py (125:148, 15%) 23 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (221:245, 8%) - configs/detection/vitdet/lsj_coco_detection.py (79:103, 21%) 23 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (126:149, 8%) - configs/detection/vitdet/vitdet_mask_rcnn.py (125:148, 15%) 23 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:101, 18%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_192.py (39:62, 38%) 23 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:101, 18%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_224.py (38:61, 39%) 23 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:101, 18%) - configs/classification/imagenet/deit/randaug_imagenet_classification.py (47:70, 29%) 23 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (115:138, 8%) - configs/detection/vitdet/vitdet_mask_rcnn.py (125:148, 15%) 22 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (216:237, 7%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (140:163, 10%) 21 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (52:72, 8%) - configs/detection/vitdet/vitdet_faster_rcnn.py (45:65, 16%) 21 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (89:110, 7%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (132:153, 9%) 21 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (52:72, 8%) - configs/detection/vitdet/vitdet_mask_rcnn.py (45:65, 14%) 21 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:201, 8%) - configs/detection/fcos/fcos_r50_caffe_1x_coco.py (20:40, 47%) 21 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (78:99, 7%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (132:153, 9%) 21 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (81:102, 13%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (99:119, 15%) 21 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (81:102, 13%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12.py (97:117, 15%) 20 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (49:68, 7%) - configs/detection/vitdet/vitdet_mask_rcnn.py (45:64, 13%) 20 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (199:219, 7%) - configs/detection/vitdet/lsj_coco_detection.py (57:77, 18%) 20 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (35:54, 7%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (33:52, 16%) 20 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (29:51, 13%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12aug.py (37:59, 12%) 20 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:107, 15%) - configs/classification/imagenet/swint/imagenet_swin_tiny_patch4_window7_224_jpg_torchacc.py (82:101, 16%) 20 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:98, 14%) - configs/classification/imagenet/swint/imagenet_swin_tiny_patch4_window7_224_jpg_torchacc.py (82:101, 16%) 20 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (49:68, 7%) - configs/detection/vitdet/vitdet_faster_rcnn.py (45:64, 15%) 20 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (29:51, 13%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12.py (37:59, 14%) 19 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (56:75, 15%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (41:60, 20%) 19 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (56:75, 13%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (41:60, 20%) 19 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (58:76, 7%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (54:72, 15%) 19 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (58:76, 7%) - configs/detection/vitdet/vitdet_mask_rcnn.py (68:86, 13%) 19 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (70:88, 6%) - configs/detection/vitdet/vitdet_mask_rcnn.py (68:86, 13%) 19 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (65:84, 14%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (41:60, 20%) 19 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (74:92, 8%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (54:72, 15%) 19 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (225:245, 7%) - configs/detection/common/dataset/autoaug_coco_detection.py (105:125, 14%) 19 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (225:245, 7%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (105:125, 14%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:219, 6%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (81:99, 13%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/edge_models/yolox_l.py (30:49, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/edge_models/yolox_m.py (30:49, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (26:46, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/detection/common/dataset/autoaug_coco_detection.py (1:20, 13%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/edge_models/yolox_tiny.py (30:49, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/edge_models/yolox_s.py (30:49, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/edge_models/yolox_nano.py (30:49, 11%) 18 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (10:27, 11%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (20:37, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (204:222, 6%) - configs/detection/fcos/fcos_r50_caffe_1x_coco.py (23:40, 40%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (26:46, 11%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (1:20, 13%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:219, 6%) - configs/detection/common/dataset/autoaug_coco_detection.py (81:99, 13%) 18 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:163, 6%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (25:45, 11%) 18 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (10:27, 11%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (14:31, 12%) 17 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (28:45, 6%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (39:55, 7%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:161, 5%) - configs/detection/yolox/yolox_s_8xb16_300e_coco.py (29:46, 9%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (1:17, 5%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (1:17, 7%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (197:213, 5%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (120:137, 7%) 16 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (63:78, 10%) - configs/segmentation/stdc/stdc1_cityscape_8xb6_e1290.py (102:118, 8%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:161, 5%) - configs/detection/fcos/coco_detection.py (1:18, 15%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (1:17, 6%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (1:17, 7%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (178:193, 5%) - configs/detection/common/dataset/autoaug_coco_detection.py (43:58, 12%) 16 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (178:193, 5%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (93:108, 8%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/detection/yolox/yolox_s_8xb16_300e_coco_pai.py (10:24, 18%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/vitdet/lsj_coco_instance.py (1:15, 13%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/edge_models/yolox_tiny.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (30:44, 15%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (26:40, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (30:44, 15%) 15 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (86:100, 11%) - configs/classification/imagenet/timm/timm_config.py (59:73, 15%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/config_templates/yolox.py (22:36, 8%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/yolox/yolox_s_8xb16_300e_coco_pai.py (10:24, 18%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/edge_models/yolox_nano.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (26:40, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/config_templates/yolox_edge_itag.py (32:46, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/edge_models/yolox_l.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (25:39, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (6:20, 13%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/common/dataset/autoaug_coco_detection.py (1:15, 11%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/config_templates/yolox_edge.py (31:45, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/config_templates/yolox.py (22:36, 8%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/edge_models/yolox_nano.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/config_templates/yolox_edge_itag.py (32:46, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/vitdet/lsj_coco_instance.py (1:15, 13%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/edge_models/yolox_s.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/edge_models/yolox_s.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (1:15, 11%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/config_templates/yolox_itag.py (31:45, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/yolox/yolox_s_8xb16_300e_coco.py (29:43, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/config_templates/yolox.py (22:36, 8%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/edge_models/yolox_l.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/config_templates/yolox_edge.py (31:45, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/edge_models/yolox_m.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/config_templates/yolox_itag.py (31:45, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/config_templates/yolox_itag.py (31:45, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (30:44, 15%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/yolox/yolox_s_8xb16_300e_coco_pai.py (10:24, 18%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/yolox/yolox_s_8xb16_300e_coco.py (29:43, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/edge_models/yolox_tiny.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/fcos/coco_detection.py (1:15, 14%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (1:15, 11%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (6:20, 13%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (25:39, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/config_templates/yolox_edge_itag.py (32:46, 9%) 15 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (77:91, 11%) - configs/classification/imagenet/timm/timm_config.py (59:73, 15%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/vitdet/lsj_coco_detection.py (1:15, 14%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:158, 5%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (3:17, 7%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (26:40, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/edge_models/yolox_m.py (30:44, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (26:40, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/config_templates/yolox_edge.py (31:45, 9%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/vitdet/lsj_coco_detection.py (1:15, 14%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (6:20, 13%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:17, 6%) - configs/detection/fcos/coco_detection.py (1:15, 14%) 15 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:17, 5%) - configs/detection/common/dataset/autoaug_coco_detection.py (1:15, 11%) 14 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (145:158, 5%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (4:17, 5%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:91, 10%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_224.py (38:51, 24%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:100, 10%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_224.py (38:51, 24%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:100, 10%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (64:77, 15%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:91, 11%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (57:70, 16%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:91, 10%) - configs/classification/imagenet/deit/randaug_imagenet_classification.py (47:60, 18%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:91, 10%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (57:70, 16%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:100, 10%) - configs/metric_learning/imagenet_resnet50_1000kid_jpg.py (68:81, 16%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:91, 10%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_192.py (39:52, 23%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:91, 10%) - configs/metric_learning/imagenet_resnet50_1000kid_jpg.py (68:81, 16%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:91, 11%) - configs/metric_learning/imagenet_resnet50_1000kid_jpg.py (68:81, 16%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (78:91, 11%) - configs/classification/imagenet/swint/imagenet_swin_tiny_patch4_window7_224_jpg_torchacc.py (82:95, 11%) 14 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (81:94, 9%) - configs/segmentation/segformer/segformer_b5_coco.py (72:85, 11%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (78:91, 10%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (64:77, 15%) 14 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (81:94, 9%) - configs/segmentation/stdc/stdc1_cityscape_8xb6_e1290.py (121:134, 7%) 14 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (4:17, 5%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (4:17, 5%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:100, 10%) - configs/classification/imagenet/deit/randaug_imagenet_classification.py (47:60, 18%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:100, 10%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (57:70, 16%) 14 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (87:100, 10%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_192.py (39:52, 23%) 14 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (4:17, 4%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (4:17, 5%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:214, 4%) - configs/detection/fcos/coco_detection.py (53:66, 12%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:15, 4%) - configs/segmentation/segformer/segformer_b0_coco.py (3:15, 5%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:15, 5%) - configs/segmentation/segformer/segformer_b0_coco.py (3:15, 5%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:156, 4%) - configs/segmentation/segformer/segformer_b5_coco.py (3:15, 10%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (210:222, 4%) - configs/detection/fcos/coco_detection.py (47:59, 12%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:193, 5%) - configs/detection/common/dataset/autoaug_coco_detection.py (67:79, 9%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (210:222, 4%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (68:80, 13%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:214, 4%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (131:144, 7%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (3:15, 5%) - configs/segmentation/segformer/segformer_b5_coco.py (3:15, 10%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (144:156, 4%) - configs/segmentation/segformer/segformer_b0_coco.py (3:15, 5%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (189:201, 5%) - configs/detection/fcos/coco_detection.py (47:59, 12%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (3:15, 4%) - configs/segmentation/segformer/segformer_b5_coco.py (3:15, 10%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:193, 5%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (117:129, 7%) 13 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (189:201, 5%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (68:80, 13%) 12 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (29:40, 7%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (39:50, 7%) 12 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (136:148, 4%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (215:227, 5%) 12 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (18:29, 8%) - configs/classification/imagenet/edgevit/imagenet_edgeVIT_s_jpg.py (3:14, 31%) 12 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (18:29, 9%) - configs/classification/imagenet/edgevit/imagenet_edgeVIT_s_jpg.py (3:14, 31%) 12 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (18:29, 9%) - configs/classification/imagenet/edgevit/imagenet_edgeVIT_s_jpg.py (3:14, 31%) 12 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (73:84, 5%) - configs/detection/vitdet/vitdet_faster_rcnn.py (67:78, 9%) 12 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (29:40, 7%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (33:44, 8%) 12 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (141:153, 5%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (215:227, 5%) 12 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (125:137, 4%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (215:227, 5%) 11 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (91:104, 9%) - configs/classification/cifar10/swintiny_b64_5e_jpg.py (64:75, 11%) 11 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (146:159, 7%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (144:156, 7%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (237:248, 3%) - configs/detection/vitdet/lsj_coco_instance.py (82:93, 10%) 11 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (146:159, 7%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12.py (142:154, 7%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (123:133, 4%) - configs/detection/vitdet/vitdet_faster_rcnn.py (118:128, 8%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (139:149, 4%) - configs/detection/vitdet/vitdet_faster_rcnn.py (118:128, 8%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (49:59, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (45:55, 4%) 11 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (68:78, 7%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (86:96, 7%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (52:62, 4%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (45:55, 4%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (70:80, 3%) - configs/detection/vitdet/vitdet_faster_rcnn.py (68:78, 8%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (134:144, 3%) - configs/detection/vitdet/vitdet_faster_rcnn.py (118:128, 8%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (176:187, 4%) - configs/detection/vitdet/lsj_coco_instance.py (41:51, 10%) 11 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (146:159, 7%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (168:180, 6%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:198, 4%) - configs/detection/vitdet/lsj_coco_detection.py (45:55, 10%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (237:248, 3%) - configs/detection/vitdet/lsj_coco_detection.py (82:93, 10%) 11 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (58:68, 4%) - configs/detection/vitdet/vitdet_faster_rcnn.py (68:78, 8%) 11 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (68:78, 7%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12.py (84:94, 7%) 11 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (68:78, 7%) - configs/segmentation/segformer/segformer_b5_coco.py (59:69, 9%) 11 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (91:104, 9%) - configs/classification/cifar10/r50_b128_300e_jpg.py (46:57, 18%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:210, 3%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (74:83, 10%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (204:214, 3%) - configs/detection/common/dataset/autoaug_coco_detection.py (70:79, 7%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (238:248, 3%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (105:115, 7%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (235:245, 3%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (165:175, 5%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (239:249, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (166:176, 4%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (204:214, 3%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (120:129, 5%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (283:292, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (220:229, 4%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (238:248, 3%) - configs/detection/common/dataset/autoaug_coco_detection.py (105:115, 7%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:210, 3%) - configs/detection/fcos/fcos_r50_caffe_1x_coco.py (34:43, 22%) 10 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (235:245, 3%) - configs/detection/fcos/coco_detection.py (87:97, 9%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:104, 6%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (73:83, 10%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/edge_models/yolox_l.py (102:110, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (93:101, 6%) - configs/video_recognition/swin/video_swin_s.py (138:146, 6%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (93:101, 6%) - configs/video_recognition/swin/video_swin_b.py (138:146, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (209:218, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (148:158, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (131:139, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (204:212, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (131:139, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (187:195, 4%) 9 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (58:66, 5%) - configs/segmentation/segformer/segformer_b0_coco.py (117:125, 3%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (81:89, 7%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (131:139, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (170:178, 4%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (1:21, 6%) - configs/classification/imagenet/timm/timm_config.py (1:12, 9%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (203:212, 3%) - configs/detection/vitdet/lsj_coco_instance.py (67:76, 8%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (102:110, 6%) - configs/video_recognition/swin/video_swin_s.py (138:146, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (256:264, 3%) - configs/detection/vitdet/lsj_coco_instance.py (109:118, 8%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (224:232, 3%) - configs/detection/vitdet/lsj_coco_instance.py (67:76, 8%) 9 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (151:159, 5%) - configs/segmentation/segformer/segformer_b0_coco.py (220:228, 3%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (1:21, 7%) - configs/classification/imagenet/timm/timm_config.py (1:12, 9%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (203:212, 3%) - configs/detection/vitdet/lsj_coco_detection.py (67:76, 8%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (93:101, 6%) - configs/video_recognition/swin/video_swin_tiny.py (138:146, 6%) 9 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (116:124, 5%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12aug.py (135:143, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/edge_models/yolox_tiny.py (97:105, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (291:299, 3%) - configs/detection/vitdet/lsj_coco_instance.py (109:118, 8%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/edge_models/yolox_m.py (102:110, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (224:232, 3%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (89:98, 6%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (21:29, 6%) - configs/classification/imagenet/deit/deit_base_patch16_224.py (6:14, 29%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/edge_models/yolox_s.py (102:110, 5%) 9 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (116:124, 5%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (137:145, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (81:89, 7%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (220:229, 3%) - configs/detection/vitdet/lsj_coco_instance.py (84:93, 8%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:104, 6%) - configs/classification/cifar10/r50_b128_300e_jpg.py (49:57, 15%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (93:101, 6%) - configs/video_recognition/stgcn/stgcn_80e_ntu60_xsub_keypoint.py (109:117, 8%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (203:212, 3%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (89:98, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (99:107, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (98:106, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (220:229, 3%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (106:115, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (220:229, 3%) - configs/detection/common/dataset/autoaug_coco_detection.py (106:115, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/edge_models/yolox_nano.py (97:105, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/edge_models/yolox_tiny.py (97:105, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:104, 6%) - configs/classification/imagenet/timm/timm_config.py (76:86, 9%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (99:107, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (31:39, 6%) - configs/selfsup/fast_convmae/fast_convmae_vit_base_patch16_8xb64_50e.py (15:23, 11%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (21:29, 6%) - configs/classification/imagenet/deit/deit_base_patch16_224.py (6:14, 29%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (115:123, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (204:212, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (115:123, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (187:195, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (115:123, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (170:178, 4%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (102:110, 6%) - configs/video_recognition/stgcn/stgcn_80e_ntu60_xsub_keypoint.py (109:117, 8%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (220:229, 3%) - configs/detection/vitdet/lsj_coco_detection.py (84:93, 8%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (99:107, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (102:110, 6%) - configs/video_recognition/swin/video_swin_tiny.py (138:146, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (73:81, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (70:78, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (99:107, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (183:192, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (127:137, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (98:106, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/edge_models/yolox_nano.py (97:105, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:104, 6%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (80:90, 9%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (126:134, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (170:178, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (126:134, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (204:212, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (126:134, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (187:195, 4%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (21:29, 7%) - configs/classification/imagenet/deit/deit_base_patch16_224.py (6:14, 29%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (224:232, 3%) - configs/detection/vitdet/lsj_coco_detection.py (67:76, 8%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (226:235, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (166:175, 4%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (224:232, 3%) - configs/detection/common/dataset/autoaug_coco_detection.py (89:98, 6%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:104, 6%) - configs/classification/cifar10/swintiny_b64_5e_jpg.py (67:75, 9%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/edge_models/yolox_s.py (102:110, 5%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (203:212, 3%) - configs/detection/common/dataset/autoaug_coco_detection.py (89:98, 6%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (244:252, 3%) - configs/edge_models/yolox_l.py (102:110, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:104, 7%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (73:83, 10%) 9 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (225:233, 3%) - configs/edge_models/yolox_m.py (102:110, 5%) 9 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (102:110, 6%) - configs/video_recognition/swin/video_swin_b.py (138:146, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/x3d/x3d_l.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (100:108, 6%) - configs/metric_learning/common/dataset/imagenet_metriclearning.py (146:154, 4%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (80:87, 8%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/video_recognition/x3d/x3d_xs.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (73:80, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (108:115, 3%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (58:65, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (71:78, 3%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/imagenet/timm/timm_config.py (76:83, 8%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:101, 5%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_192.py (55:62, 13%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:101, 5%) - configs/video_recognition/x3d/x3d_m.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/cifar10/r50_b128_300e_jpg.py (49:56, 13%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (73:80, 9%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_192.py (55:62, 13%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/x3d/x3d_m.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/swin/video_swin_b.py (139:146, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/swin/video_swin_tiny.py (139:146, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (91:99, 5%) - configs/metric_learning/common/dataset/imagenet_metriclearning.py (146:154, 4%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:101, 5%) - configs/video_recognition/x3d/x3d_l.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/video_recognition/x3d/x3d_l.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:101, 5%) - configs/video_recognition/x3d/x3d_xs.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/swin/video_swin_s.py (139:146, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/stgcn/stgcn_80e_ntu60_xsub_keypoint.py (110:117, 7%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (168:175, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (132:139, 3%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:101, 6%) - configs/video_recognition/x3d/x3d_xs.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/imagenet/deit/randaug_imagenet_classification.py (63:70, 10%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (217:225, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (195:203, 3%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:101, 5%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_224.py (54:61, 13%) 8 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (152:159, 5%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12aug.py (171:178, 4%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (94:101, 5%) - configs/classification/imagenet/deit/randaug_imagenet_classification.py (63:70, 10%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (73:80, 3%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (89:96, 3%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (221:229, 2%) - configs/detection/fcos/coco_detection.py (73:81, 7%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/cifar10/swintiny_b64_5e_jpg.py (67:74, 8%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (179:186, 2%) - configs/detection/vitdet/lsj_coco_detection.py (36:43, 7%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/video_recognition/x3d/x3d_m.py (134:141, 6%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (168:175, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (104:111, 3%) 8 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (42:52, 5%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (52:62, 4%) 8 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (70:77, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (71:78, 3%) 8 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (103:110, 6%) - configs/classification/imagenet/deitiii/threeaug_imagenet_classification_224.py (54:61, 13%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:187, 2%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (60:66, 7%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:207, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (165:172, 2%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (216:222, 2%) - configs/detection/vitdet/lsj_coco_detection.py (59:65, 6%) 7 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (128:134, 4%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (149:155, 4%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:194, 2%) - configs/detection/fcos/fcos_r50_caffe_1x_coco.py (20:26, 15%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (58:64, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (90:96, 3%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (100:107, 5%) - configs/classification/imagenet/common/dataset/imagenet_classification.py (147:154, 4%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (100:107, 5%) - configs/classification/imagenet/inception/inceptionv3_b32x8_100e.py (176:183, 3%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (73:80, 5%) - configs/selfsup/mae/mae_vit_base_patch16_8xb64_1600e.py (52:58, 9%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:187, 2%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (67:73, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:187, 2%) - configs/detection/vitdet/lsj_coco_detection.py (45:51, 6%) 7 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (118:124, 4%) - configs/segmentation/segformer/segformer_b0_coco.py (170:176, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (216:222, 2%) - configs/detection/vitdet/lsj_coco_instance.py (59:65, 6%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (115:121, 2%) - configs/detection/vitdet/vitdet_faster_rcnn.py (111:117, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (180:187, 2%) - configs/detection/fcos/coco_detection.py (39:45, 6%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (91:98, 5%) - configs/classification/imagenet/common/dataset/imagenet_classification.py (147:154, 4%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (216:222, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (131:137, 3%) 7 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (153:159, 4%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e127_semantic.py (239:245, 2%) 7 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (162:168, 4%) - configs/detection3d/bevformer/bevformer_tiny_r50_nuscenes.py (306:313, 2%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (33:39, 10%) - configs/metric_learning/cub_resnet50_jpg.py (34:40, 7%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (185:191, 2%) - configs/detection/common/dataset/autoaug_coco_detection.py (28:34, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:194, 2%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (67:73, 5%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (21:27, 5%) - configs/classification/imagenet/deitiii/deitiii_base_patch16_192.py (6:12, 19%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (195:201, 2%) - configs/detection/vitdet/lsj_coco_instance.py (59:65, 6%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (33:39, 10%) - configs/metric_learning/imagenet_resnet50_1000kid_jpg.py (48:54, 8%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:194, 2%) - configs/detection/fcos/coco_detection.py (39:45, 6%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (131:137, 2%) - configs/detection/vitdet/vitdet_faster_rcnn.py (111:117, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (58:64, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (109:115, 3%) 7 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (153:159, 4%) - configs/segmentation/stdc/stdc1_cityscape_8xb6_e1290.py (184:190, 3%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (91:98, 5%) - configs/classification/imagenet/inception/inceptionv3_b32x8_100e.py (176:183, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (185:191, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (78:84, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:194, 2%) - configs/detection/common/dataset/autoaug_coco_detection.py (67:73, 5%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (100:107, 5%) - configs/classification/itag/mobilenetv2.py (66:73, 10%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (126:132, 2%) - configs/detection/vitdet/vitdet_faster_rcnn.py (111:117, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (70:76, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (109:115, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (195:201, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (131:137, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (21:27, 2%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (2:9, 5%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (73:80, 5%) - configs/config_templates/mae_vit_base_patch16.py (42:48, 9%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (21:27, 5%) - configs/classification/imagenet/deitiii/deitiii_base_patch16_192.py (6:12, 19%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (201:207, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (140:146, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (82:88, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (124:130, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (195:201, 2%) - configs/detection/common/dataset/autoaug_coco_detection.py (81:87, 5%) 7 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (128:134, 4%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12aug.py (147:153, 4%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (216:222, 2%) - configs/detection/common/dataset/autoaug_coco_detection.py (81:87, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (195:201, 2%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (81:87, 5%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:194, 2%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (60:66, 7%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (195:201, 2%) - configs/detection/vitdet/lsj_coco_detection.py (59:65, 6%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (21:27, 5%) - configs/classification/imagenet/deitiii/deitiii_base_patch16_192.py (6:12, 19%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (188:194, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (117:123, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (70:76, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (124:130, 3%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (91:98, 5%) - configs/classification/itag/mobilenetv2.py (66:73, 10%) 7 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (33:39, 10%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (37:43, 8%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (70:76, 2%) - configs/detection/vitdet/vitdet_cascade_mask_rcnn.py (90:96, 3%) 7 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (216:222, 2%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (81:87, 5%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/edge_models/yolox_s.py (85:90, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (27:32, 2%) - configs/detection/mask_rcnn/mask_rcnn_r50_fpn.py (27:32, 4%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (93:98, 4%) - configs/classification/imagenet/common/dataset/imagenet_classification.py (139:144, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (171:176, 2%) - configs/detection/common/dataset/autoaug_obj2coco_detection.py (34:39, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (176:181, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (120:125, 2%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (173:178, 2%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (53:58, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (171:176, 2%) - configs/detection/common/dataset/autoaug_coco_detection.py (34:39, 4%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/classification/imagenet/swint/imagenet_swin_tiny_patch4_window7_224_jpg_torchacc.py (59:64, 5%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (63:69, 8%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (70:76, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (38:43, 4%) - configs/classification/imagenet/timm/timm_config.py (23:28, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (18:23, 4%) - configs/classification/imagenet/swint/swin_tiny_patch4_window7_224_b64x16_300e_jpg.py (5:10, 7%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (12:19, 4%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (3:10, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (23:28, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (41:46, 2%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/metric_learning/imagenet_resnet50_1000kid_jpg.py (56:61, 7%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (287:292, 2%) - configs/detection/vitdet/lsj_coco_instance.py (113:118, 5%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/edge_models/yolox_tiny.py (80:85, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (64:69, 5%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (38:43, 4%) - configs/classification/imagenet/vit/vit_base_patch16_224_b64x64_300e_jpg.py (19:24, 9%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/edge_models/yolox_tiny.py (80:85, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/classification/cifar10/swintiny_b64_5e_jpg.py (42:47, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (18:23, 4%) - configs/classification/imagenet/swint/swin_tiny_patch4_window7_224_b64x16_300e_jpg.py (5:10, 7%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (14:21, 4%) - configs/classification/imagenet/timm/timm_config.py (5:12, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (288:294, 2%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (148:153, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (288:294, 2%) - configs/segmentation/segformer/segformer_b0_coco.py (220:225, 2%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (45:50, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (259:264, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (224:229, 2%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/edge_models/yolox_s.py (85:90, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (84:89, 4%) - configs/classification/imagenet/inception/inceptionv3_b32x8_100e.py (169:174, 3%) 6 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (15:20, 3%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12.py (24:29, 4%) 6 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (118:123, 3%) - configs/segmentation/stdc/stdc1_cityscape_8xb6_e1290.py (155:160, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (93:98, 4%) - configs/classification/imagenet/resnet/market1501_resnet50_jpg.py (53:58, 9%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (84:89, 4%) - configs/metric_learning/common/dataset/imagenet_metriclearning.py (139:144, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/edge_models/yolox_nano.py (80:85, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (12:19, 4%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (2:9, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/metric_learning/sop_timm_swinb_local.py (79:84, 4%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (85:90, 4%) - configs/metric_learning/sop_timm_swinb_local.py (105:110, 4%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/classification/imagenet/timm/timm_config.py (48:53, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/resnet50_8xb32_100e_finetune.py (40:45, 8%) - configs/metric_learning/cub_resnet50_jpg.py (42:47, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (38:43, 4%) - configs/classification/imagenet/deit/deit_base_patch16_224.py (27:32, 19%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (288:294, 2%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12.py (146:151, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/edge_models/yolox_l.py (85:90, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/detection/yolox/yolox_tiny_8xb16_300e_coco.py (64:69, 5%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (84:89, 4%) - configs/classification/imagenet/resnet/market1501_resnet50_jpg.py (53:58, 9%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (81:86, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (197:202, 2%) - configs/detection/vitdet/lsj_coco_instance.py (41:46, 5%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (294:299, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (224:229, 2%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (23:28, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e127_semantic.py (84:89, 2%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (290:295, 2%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (106:111, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/edge_models/yolox_l.py (85:90, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (30:35, 2%) - configs/video_recognition/swin/video_swin_tiny.py (13:18, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (30:35, 2%) - configs/video_recognition/clipbert/clipbert_multilabel.py (13:18, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/detection/yolox/pai_yoloxs_8xb16_300e_coco.py (81:86, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (94:99, 4%) - configs/metric_learning/common/dataset/imagenet_metriclearning.py (149:154, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (38:43, 4%) - configs/classification/imagenet/swint/imagenet_swin_tiny_patch4_window7_224_jpg_torchacc.py (20:25, 5%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (12:19, 4%) - configs/classification/imagenet/efficientformer/efficientformer_l1.py (2:9, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (173:178, 2%) - configs/detection/fcos/fcos_r50_caffe_1x_coco.py (13:18, 13%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (225:231, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (155:161, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (30:35, 2%) - configs/video_recognition/swin/video_swin_b.py (13:18, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (82:87, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (173:178, 2%) - configs/detection/fcos/coco_detection.py (32:37, 5%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (38:43, 4%) - configs/classification/imagenet/swint/imagenet_swin_tiny_patch4_window7_224_jpg_torchacc.py (20:25, 5%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (38:43, 4%) - configs/classification/imagenet/deit/deit_base_patch16_224.py (27:32, 19%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (93:98, 4%) - configs/metric_learning/common/dataset/imagenet_metriclearning.py (139:144, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (38:43, 4%) - configs/classification/imagenet/vit/vit_base_patch16_224_b64x64_300e_jpg.py (19:24, 9%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (84:89, 4%) - configs/classification/imagenet/resnet/market1501_resnet50_jpg.py (53:58, 9%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (38:43, 4%) - configs/classification/imagenet/swint/swin_tiny_patch4_window7_224_b64x16_300e_jpg.py (20:25, 7%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (84:89, 4%) - configs/metric_learning/common/dataset/imagenet_metriclearning.py (139:144, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (184:189, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (120:125, 2%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (255:260, 2%) - configs/detection/fcos/fcos_r50_torch_1x_pai.py (106:111, 6%) 6 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (85:90, 3%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py (139:144, 2%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (12:19, 4%) - configs/classification/imagenet/edgevit/EdgeVit_b512x8_300e_jpg.py (3:10, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/moby_r50_8xb2048_20e_feature.py (12:19, 11%) - configs/metric_learning/imagenet_resnet50_1000kid_jpg.py (2:9, 7%) 6 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (15:20, 3%) - configs/segmentation/upernet/upernet_r50_512x512_8xb4_60e_voc12aug.py (24:29, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (23:28, 2%) - configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py (68:73, 2%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/moby_r50_8xb2048_20e_feature.py (12:19, 11%) - configs/metric_learning/cub_resnet50_jpg.py (2:9, 6%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (18:23, 4%) - configs/classification/imagenet/swint/swin_tiny_patch4_window7_224_b64x16_300e_jpg.py (5:10, 7%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (85:90, 4%) - configs/metric_learning/sop_timm_swinb_local.py (105:110, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (30:35, 2%) - configs/video_recognition/clipbert/clipbert.py (13:18, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/detection/yolox/pai_yoloxs_asff_tood3_8xb16_300e_coco.py (82:87, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_conv_vitdet_50e_coco.py (283:288, 2%) - configs/detection/common/dataset/autoaug_coco_detection.py (134:139, 4%) 6 duplicated lines in: - benchmarks/selfsup/segmentation/voc/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (42:48, 3%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12.py (46:52, 4%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (93:98, 4%) - configs/classification/imagenet/inception/inceptionv3_b32x8_100e.py (169:174, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/fast_convmae_vit_base_patch16_8xb64_100e_fintune.py (94:99, 4%) - configs/metric_learning/sop_timm_swinb_local.py (105:110, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (238:244, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (155:161, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/edge_models/yolox_nano.py (80:85, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (38:43, 4%) - configs/classification/imagenet/swint/swin_tiny_patch4_window7_224_b64x16_300e_jpg.py (20:25, 7%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (82:87, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (84:89, 4%) - configs/classification/imagenet/inception/inceptionv3_b32x8_100e.py (169:174, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (288:294, 2%) - configs/segmentation/fcn/fcn_r50-d8_512x512_8xb4_60e_voc12aug.py (172:177, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (171:176, 2%) - configs/detection/common/dataset/autoaug_obj365_val5k_detection.py (84:89, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (84:89, 4%) - configs/classification/imagenet/common/dataset/imagenet_classification.py (139:144, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (30:35, 2%) - configs/video_recognition/swin/video_swin_s.py (13:18, 4%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/edge_models/yolox_m.py (85:90, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_large_patch16_8xb16_50e_lrdecay075_fintune.py (38:43, 4%) - configs/classification/imagenet/timm/timm_config.py (23:28, 6%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_r50_fpn_1x_coco.py (208:213, 2%) - configs/detection/yolox/pai_yoloxs_asff_8xb16_300e_coco.py (82:87, 3%) 6 duplicated lines in: - benchmarks/selfsup/detection/coco/mask_rcnn_swin_tiny_1x_coco.py (228:233, 2%) - configs/edge_models/yolox_m.py (85:90, 3%) 6 duplicated lines in: - benchmarks/selfsup/classification/imagenet/mae_vit_base_patch16_8xb64_100e_lrdecay065_fintune.py (84:89, 4%) - configs/classification/imagenet/common/dataset/imagenet_classification.py (139:144, 3%)