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Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
https://detectron2.readthedocs.io/en/latest/
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Problem on input type and weight type #220

Closed Nobosaseru closed 4 years ago

Nobosaseru commented 4 years ago

When I ran code on my custom datset , the trouble happened. Here is the traceback. Command Line Args: Namespace(config_file='configs/COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', dist_url='tcp://127.0.0.1:50159', eval_only=False, machine_rank=0, num_gpus=1, num_machines=1, opts=['SOLVER.IMS_PER_BATCH', '2', 'SOLVER.BASE_LR', '0.0025'], resume=False) Config 'configs/COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml' has no VERSION. Assuming it to be compatible with latest v2. [11/02 10:57:13 detectron2]: Rank of current process: 0. World size: 1 [11/02 10:57:18 detectron2]: Environment info:

sys.platform linux Python 3.6.9 Anaconda, Inc. (default, Jul 30 2019, 19:07:31) [GCC 7.3.0] Numpy 1.17.2 Detectron2 Compiler GCC 5.4 Detectron2 CUDA Compiler 10.0 DETECTRON2_ENV_MODULE PyTorch 1.3.0 PyTorch Debug Build False torchvision 0.4.1a0+d94043a CUDA available True GPU 0,1,2,3,4,5,6,7,8 GeForce GTX 1080 Ti CUDA_HOME /usr/local/cuda NVCC Cuda compilation tools, release 10.0, V10.0.130 Pillow 6.2.0 cv2 4.1.1

PyTorch built with:

[11/02 10:57:18 detectron2]: Command line arguments: Namespace(config_file='configs/COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', dist_url='tcp://127.0.0.1:50159', eval_only=False, machine_rank=0, num_gpus=1, num_machines=1, opts=['SOLVER.IMS_PER_BATCH', '2', 'SOLVER.BASE_LR', '0.0025'], resume=False) [11/02 10:57:18 detectron2]: Contents of args.config_file=configs/COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml: BASE: "../Base-RCNN-Detnet-FPN.yaml" MODEL: WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl" MASK_ON: False RESNETS: DEPTH: 50 SOLVER: STEPS: (210000, 250000) MAX_ITER: 270000

[11/02 10:57:18 detectron2]: Running with full config: CUDNN_BENCHMARK: False DATALOADER: ASPECT_RATIO_GROUPING: True FILTER_EMPTY_ANNOTATIONS: True NUM_WORKERS: 4 REPEAT_THRESHOLD: 0.0 SAMPLER_TRAIN: TrainingSampler DATASETS: PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000 PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000 PROPOSAL_FILES_TEST: () PROPOSAL_FILES_TRAIN: () TEST: ('coco_2017_val',) TRAIN: ('coco_2017_train',) GLOBAL: HACK: 1.0 INPUT: CROP: ENABLED: False SIZE: [0.9, 0.9] TYPE: relative_range FORMAT: BGR MASK_FORMAT: polygon MAX_SIZE_TEST: 1333 MAX_SIZE_TRAIN: 1333 MIN_SIZE_TEST: 800 MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800) MIN_SIZE_TRAIN_SAMPLING: choice MODEL: ANCHOR_GENERATOR: ANGLES: [[-90, 0, 90]] ASPECT_RATIOS: [[0.5, 1.0, 2.0]] NAME: DefaultAnchorGenerator SIZES: [[32], [64], [128], [256], [512]] BACKBONE: FREEZE_AT: 2 NAME: build_detnet_fpn_backbone DETNETS: DEPTH: 50 DILATE_ON_PER_STAGE: [False, False, False, True, True] FINAL_DILATION: 2 NORM: FrozenBN NUM_GROUPS: 1 OUT_FEATURES: ['res2', 'res3', 'res4', 'res5', 'res6'] RES2_OUT_CHANNELS: 256 RES5_DILATION: 1 STEM_OUT_CHANNELS: 64 STRIDE_IN_1X1: True WIDTH_PER_GROUP: 64 DEVICE: cuda FPN: FUSE_TYPE: sum IN_FEATURES: ['res2', 'res3', 'res4', 'res5', 'res6'] NORM: OUT_CHANNELS: 256 KEYPOINT_ON: False LOAD_PROPOSALS: False MASK_ON: False META_ARCHITECTURE: GeneralizedRCNN PANOPTIC_FPN: COMBINE: ENABLED: True INSTANCES_CONFIDENCE_THRESH: 0.5 OVERLAP_THRESH: 0.5 STUFF_AREA_LIMIT: 4096 INSTANCE_LOSS_WEIGHT: 1.0 PIXEL_MEAN: [103.53, 116.28, 123.675] PIXEL_STD: [1.0, 1.0, 1.0] PROPOSAL_GENERATOR: MIN_SIZE: 0 NAME: RPN RESNETS: DEFORM_MODULATED: False DEFORM_NUM_GROUPS: 1 DEFORM_ON_PER_STAGE: [False, False, False, False] DEPTH: 50 NORM: FrozenBN NUM_GROUPS: 1 OUT_FEATURES: ['res4'] RES2_OUT_CHANNELS: 256 RES5_DILATION: 1 STEM_OUT_CHANNELS: 64 STRIDE_IN_1X1: True WIDTH_PER_GROUP: 64 RETINANET: BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0) FOCAL_LOSS_ALPHA: 0.25 FOCAL_LOSS_GAMMA: 2.0 IN_FEATURES: ['p3', 'p4', 'p5', 'p6', 'p7'] IOU_LABELS: [0, -1, 1] IOU_THRESHOLDS: [0.4, 0.5] NMS_THRESH_TEST: 0.5 NUM_CLASSES: 80 NUM_CONVS: 4 PRIOR_PROB: 0.01 SCORE_THRESH_TEST: 0.05 SMOOTH_L1_LOSS_BETA: 0.1 TOPK_CANDIDATES_TEST: 1000 ROI_BOX_CASCADE_HEAD: BBOX_REG_WEIGHTS: ((10.0, 10.0, 5.0, 5.0), (20.0, 20.0, 10.0, 10.0), (30.0, 30.0, 15.0, 15.0)) IOUS: (0.5, 0.6, 0.7) ROI_BOX_HEAD: BBOX_REG_WEIGHTS: (10.0, 10.0, 5.0, 5.0) CLS_AGNOSTIC_BBOX_REG: False CONV_DIM: 256 FC_DIM: 1024 NAME: FastRCNNConvFCHead NORM: NUM_CONV: 0 NUM_FC: 2 POOLER_RESOLUTION: 7 POOLER_SAMPLING_RATIO: 0 POOLER_TYPE: ROIAlignV2 SMOOTH_L1_BETA: 0.0 ROI_HEADS: BATCH_SIZE_PER_IMAGE: 512 IN_FEATURES: ['p2', 'p3', 'p4', 'p5', 'p6'] IOU_LABELS: [0, 1] IOU_THRESHOLDS: [0.5] NAME: StandardROIHeads NMS_THRESH_TEST: 0.5 NUM_CLASSES: 10 POSITIVE_FRACTION: 0.25 PROPOSAL_APPEND_GT: True SCORE_THRESH_TEST: 0.05 ROI_KEYPOINT_HEAD: CONV_DIMS: (512, 512, 512, 512, 512, 512, 512, 512) LOSS_WEIGHT: 1.0 MIN_KEYPOINTS_PER_IMAGE: 1 NAME: KRCNNConvDeconvUpsampleHead NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: True NUM_KEYPOINTS: 17 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_TYPE: ROIAlignV2 ROI_MASK_HEAD: CLS_AGNOSTIC_MASK: False CONV_DIM: 256 NAME: MaskRCNNConvUpsampleHead NORM: NUM_CONV: 4 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_TYPE: ROIAlignV2 RPN: BATCH_SIZE_PER_IMAGE: 256 BBOX_REG_WEIGHTS: (1.0, 1.0, 1.0, 1.0) BOUNDARY_THRESH: -1 HEAD_NAME: StandardRPNHead IN_FEATURES: ['p2', 'p3', 'p4', 'p5', 'p6'] IOU_LABELS: [0, -1, 1] IOU_THRESHOLDS: [0.3, 0.7] LOSS_WEIGHT: 1.0 NMS_THRESH: 0.7 POSITIVE_FRACTION: 0.5 POST_NMS_TOPK_TEST: 1000 POST_NMS_TOPK_TRAIN: 1000 PRE_NMS_TOPK_TEST: 1000 PRE_NMS_TOPK_TRAIN: 2000 SMOOTH_L1_BETA: 0.0 SEM_SEG_HEAD: COMMON_STRIDE: 4 CONVS_DIM: 128 IGNORE_VALUE: 255 IN_FEATURES: ['p2', 'p3', 'p4', 'p5'] LOSS_WEIGHT: 1.0 NAME: SemSegFPNHead NORM: GN NUM_CLASSES: 54 WEIGHTS: detectron2://ImageNetPretrained/MSRA/R-50.pkl OUTPUT_DIR: ./output SEED: -1 SOLVER: BASE_LR: 0.0025 BIAS_LR_FACTOR: 1.0 CHECKPOINT_PERIOD: 5000 GAMMA: 0.1 IMS_PER_BATCH: 2 LR_SCHEDULER_NAME: WarmupMultiStepLR MAX_ITER: 270000 MOMENTUM: 0.9 STEPS: (210000, 250000) WARMUP_FACTOR: 0.001 WARMUP_ITERS: 1000 WARMUP_METHOD: linear WEIGHT_DECAY: 0.0001 WEIGHT_DECAY_BIAS: 0.0001 WEIGHT_DECAY_NORM: 0.0 TEST: AUG: ENABLED: False FLIP: True MAX_SIZE: 4000 MIN_SIZES: (400, 500, 600, 700, 800, 900, 1000, 1100, 1200) DETECTIONS_PER_IMAGE: 100 EVAL_PERIOD: 0 EXPECTED_RESULTS: [] KEYPOINT_OKS_SIGMAS: [] PRECISE_BN: ENABLED: False NUM_ITER: 200 VERSION: 2 [11/02 10:57:18 detectron2]: Full config saved to /home/lxj/detectron2/output/config.yaml [11/02 10:57:18 d2.utils.env]: Using a generated random seed 18461503

GeneralizedRCNN( (backbone): FPN( (fpn_lateral2): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1)) (fpn_output2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (fpn_lateral3): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1)) (fpn_output3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (fpn_lateral4): Conv2d(4096, 256, kernel_size=(1, 1), stride=(1, 1)) (fpn_output4): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (top_block): LastLevelMaxPool() (bottom_up): DetNet( (stem): BasicStem( (conv1): Conv2d( 3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) ) (res2): Sequential( (0): BottleneckBlock( (shortcut): Conv2d( 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv1): Conv2d( 64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) (conv2): Conv2d( 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) (conv3): Conv2d( 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) ) (1): BottleneckBlock( (conv1): Conv2d( 256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) (conv2): Conv2d( 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) (conv3): Conv2d( 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) ) (2): BottleneckBlock( (conv1): Conv2d( 256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) (conv2): Conv2d( 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=64, eps=1e-05) ) (conv3): Conv2d( 64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) ) ) (res3): Sequential( (0): BottleneckBlock( (shortcut): Conv2d( 256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) (conv1): Conv2d( 256, 128, kernel_size=(1, 1), stride=(2, 2), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv2): Conv2d( 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv3): Conv2d( 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) ) (1): BottleneckBlock( (conv1): Conv2d( 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv2): Conv2d( 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv3): Conv2d( 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) ) (2): BottleneckBlock( (conv1): Conv2d( 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv2): Conv2d( 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv3): Conv2d( 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) ) (3): BottleneckBlock( (conv1): Conv2d( 512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv2): Conv2d( 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=128, eps=1e-05) ) (conv3): Conv2d( 128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) ) ) (res4): Sequential( (0): BottleneckBlock( (shortcut): Conv2d( 512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) (conv1): Conv2d( 512, 256, kernel_size=(1, 1), stride=(2, 2), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv2): Conv2d( 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv3): Conv2d( 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) ) (1): BottleneckBlock( (conv1): Conv2d( 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv2): Conv2d( 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv3): Conv2d( 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) ) (2): BottleneckBlock( (conv1): Conv2d( 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv2): Conv2d( 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv3): Conv2d( 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) ) (3): BottleneckBlock( (conv1): Conv2d( 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv2): Conv2d( 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv3): Conv2d( 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) ) (4): BottleneckBlock( (conv1): Conv2d( 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv2): Conv2d( 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv3): Conv2d( 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) ) (5): BottleneckBlock( (conv1): Conv2d( 1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv2): Conv2d( 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=256, eps=1e-05) ) (conv3): Conv2d( 256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) ) ) (res5): Sequential( (0): DilateBottleneckBlock( (shortcut): Conv2d( 1024, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05) ) (conv1): Conv2d( 1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2)) (conv3): Conv2d( 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05) ) ) (1): DilateBottleneckBlock( (conv1): Conv2d( 2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2)) (conv3): Conv2d( 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05) ) ) (2): DilateBottleneckBlock( (conv1): Conv2d( 2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=512, eps=1e-05) ) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2)) (conv3): Conv2d( 512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=2048, eps=1e-05) ) ) ) (res6): Sequential( (0): DilateBottleneckBlock( (shortcut): Conv2d( 2048, 4096, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=4096, eps=1e-05) ) (conv1): Conv2d( 2048, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) (conv2): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2)) (conv3): Conv2d( 1024, 4096, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=4096, eps=1e-05) ) ) (1): DilateBottleneckBlock( (conv1): Conv2d( 4096, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) (conv2): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2)) (conv3): Conv2d( 1024, 4096, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=4096, eps=1e-05) ) ) (2): DilateBottleneckBlock( (conv1): Conv2d( 4096, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=1024, eps=1e-05) ) (conv2): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2)) (conv3): Conv2d( 1024, 4096, kernel_size=(1, 1), stride=(1, 1), bias=False (norm): FrozenBatchNorm2d(num_features=4096, eps=1e-05) ) ) ) ) ) (proposal_generator): RPN( (anchor_generator): DefaultAnchorGenerator( (cell_anchors): BufferList() ) (rpn_head): StandardRPNHead( (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (objectness_logits): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1)) (anchor_deltas): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1)) ) ) (roi_heads): StandardROIHeads( (box_pooler): ROIPooler( (level_poolers): ModuleList( (0): ROIAlign(output_size=(7, 7), spatial_scale=0.25, sampling_ratio=0, aligned=True) (1): ROIAlign(output_size=(7, 7), spatial_scale=0.125, sampling_ratio=0, aligned=True) (2): ROIAlign(output_size=(7, 7), spatial_scale=0.0625, sampling_ratio=0, aligned=True) (3): ROIAlign(output_size=(7, 7), spatial_scale=0.03125, sampling_ratio=0, aligned=True) (4): ROIAlign(output_size=(7, 7), spatial_scale=0.0625, sampling_ratio=0, aligned=True) ) ) (box_head): FastRCNNConvFCHead( (fc1): Linear(in_features=12544, out_features=1024, bias=True) (fc2): Linear(in_features=1024, out_features=1024, bias=True) ) (box_predictor): FastRCNNOutputLayers( (cls_score): Linear(in_features=1024, out_features=11, bias=True) (bbox_pred): Linear(in_features=1024, out_features=40, bias=True) ) ) ) [11/02 10:57:25 d2.data.datasets.coco]: Loading datasets/coco/annotations/instances_train2017.json takes 2.11 seconds. {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9} [11/02 10:57:25 d2.data.datasets.coco]: Loaded 6471 images in COCO format from datasets/coco/annotations/instances_train2017.json [11/02 10:57:26 d2.data.build]: Removed 0 images with no usable annotations. 6471 images left. [11/02 10:57:26 d2.data.build]: Distribution of training instances among all 10 categories: category #instances category #instances category #instances
pedestrian 0 person 79337 car 27059
van 10480 bus 144867 trunk 24956
motor 12875 bicycle 4812 awning-tric.. 3246
tricycle 35573
total 343205

[11/02 10:57:26 d2.data.detection_utils]: TransformGens used in training: [ResizeShortestEdge(short_edge_length=(640, 672, 704, 736, 768, 800), max_size=1333, sample_style='choice'), RandomFlip()] [11/02 10:57:26 d2.data.build]: Using training sampler TrainingSampler [11/02 10:57:27 fvcore.common.checkpoint]: Loading checkpoint from detectron2://ImageNetPretrained/MSRA/R-50.pkl [11/02 10:57:27 fvcore.common.file_io]: URL https://dl.fbaipublicfiles.com/detectron2/ImageNetPretrained/MSRA/R-50.pkl cached in /home/lxj/.torch/fvcore_cache/detectron2/ImageNetPretrained/MSRA/R-50.pkl [11/02 10:57:27 d2.checkpoint.c2_model_loading]: Remapping C2 weights ...... [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv1.norm.bias loaded from res2_0_branch2a_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv1.norm.running_mean loaded from res2_0_branch2a_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv1.norm.running_var loaded from res2_0_branch2a_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv1.norm.weight loaded from res2_0_branch2a_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv1.weight loaded from res2_0_branch2a_w of shape (64, 64, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv2.norm.bias loaded from res2_0_branch2b_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv2.norm.running_mean loaded from res2_0_branch2b_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv2.norm.running_var loaded from res2_0_branch2b_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv2.norm.weight loaded from res2_0_branch2b_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv2.weight loaded from res2_0_branch2b_w of shape (64, 64, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv3.norm.bias loaded from res2_0_branch2c_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv3.norm.running_mean loaded from res2_0_branch2c_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv3.norm.running_var loaded from res2_0_branch2c_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv3.norm.weight loaded from res2_0_branch2c_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.conv3.weight loaded from res2_0_branch2c_w of shape (256, 64, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.shortcut.norm.bias loaded from res2_0_branch1_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.shortcut.norm.running_mean loaded from res2_0_branch1_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.shortcut.norm.running_var loaded from res2_0_branch1_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.shortcut.norm.weight loaded from res2_0_branch1_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.0.shortcut.weight loaded from res2_0_branch1_w of shape (256, 64, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv1.norm.bias loaded from res2_1_branch2a_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv1.norm.running_mean loaded from res2_1_branch2a_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv1.norm.running_var loaded from res2_1_branch2a_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv1.norm.weight loaded from res2_1_branch2a_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv1.weight loaded from res2_1_branch2a_w of shape (64, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv2.norm.bias loaded from res2_1_branch2b_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv2.norm.running_mean loaded from res2_1_branch2b_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv2.norm.running_var loaded from res2_1_branch2b_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv2.norm.weight loaded from res2_1_branch2b_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv2.weight loaded from res2_1_branch2b_w of shape (64, 64, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv3.norm.bias loaded from res2_1_branch2c_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv3.norm.running_mean loaded from res2_1_branch2c_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv3.norm.running_var loaded from res2_1_branch2c_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv3.norm.weight loaded from res2_1_branch2c_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.1.conv3.weight loaded from res2_1_branch2c_w of shape (256, 64, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv1.norm.bias loaded from res2_2_branch2a_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv1.norm.running_mean loaded from res2_2_branch2a_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv1.norm.running_var loaded from res2_2_branch2a_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv1.norm.weight loaded from res2_2_branch2a_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv1.weight loaded from res2_2_branch2a_w of shape (64, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv2.norm.bias loaded from res2_2_branch2b_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv2.norm.running_mean loaded from res2_2_branch2b_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv2.norm.running_var loaded from res2_2_branch2b_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv2.norm.weight loaded from res2_2_branch2b_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv2.weight loaded from res2_2_branch2b_w of shape (64, 64, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv3.norm.bias loaded from res2_2_branch2c_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv3.norm.running_mean loaded from res2_2_branch2c_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv3.norm.running_var loaded from res2_2_branch2c_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv3.norm.weight loaded from res2_2_branch2c_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res2.2.conv3.weight loaded from res2_2_branch2c_w of shape (256, 64, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv1.norm.bias loaded from res3_0_branch2a_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv1.norm.running_mean loaded from res3_0_branch2a_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv1.norm.running_var loaded from res3_0_branch2a_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv1.norm.weight loaded from res3_0_branch2a_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv1.weight loaded from res3_0_branch2a_w of shape (128, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv2.norm.bias loaded from res3_0_branch2b_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv2.norm.running_mean loaded from res3_0_branch2b_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv2.norm.running_var loaded from res3_0_branch2b_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv2.norm.weight loaded from res3_0_branch2b_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv2.weight loaded from res3_0_branch2b_w of shape (128, 128, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv3.norm.bias loaded from res3_0_branch2c_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv3.norm.running_mean loaded from res3_0_branch2c_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv3.norm.running_var loaded from res3_0_branch2c_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv3.norm.weight loaded from res3_0_branch2c_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.conv3.weight loaded from res3_0_branch2c_w of shape (512, 128, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.shortcut.norm.bias loaded from res3_0_branch1_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.shortcut.norm.running_mean loaded from res3_0_branch1_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.shortcut.norm.running_var loaded from res3_0_branch1_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.shortcut.norm.weight loaded from res3_0_branch1_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.0.shortcut.weight loaded from res3_0_branch1_w of shape (512, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv1.norm.bias loaded from res3_1_branch2a_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv1.norm.running_mean loaded from res3_1_branch2a_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv1.norm.running_var loaded from res3_1_branch2a_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv1.norm.weight loaded from res3_1_branch2a_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv1.weight loaded from res3_1_branch2a_w of shape (128, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv2.norm.bias loaded from res3_1_branch2b_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv2.norm.running_mean loaded from res3_1_branch2b_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv2.norm.running_var loaded from res3_1_branch2b_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv2.norm.weight loaded from res3_1_branch2b_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv2.weight loaded from res3_1_branch2b_w of shape (128, 128, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv3.norm.bias loaded from res3_1_branch2c_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv3.norm.running_mean loaded from res3_1_branch2c_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv3.norm.running_var loaded from res3_1_branch2c_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv3.norm.weight loaded from res3_1_branch2c_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.1.conv3.weight loaded from res3_1_branch2c_w of shape (512, 128, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv1.norm.bias loaded from res3_2_branch2a_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv1.norm.running_mean loaded from res3_2_branch2a_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv1.norm.running_var loaded from res3_2_branch2a_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv1.norm.weight loaded from res3_2_branch2a_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv1.weight loaded from res3_2_branch2a_w of shape (128, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv2.norm.bias loaded from res3_2_branch2b_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv2.norm.running_mean loaded from res3_2_branch2b_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv2.norm.running_var loaded from res3_2_branch2b_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv2.norm.weight loaded from res3_2_branch2b_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv2.weight loaded from res3_2_branch2b_w of shape (128, 128, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv3.norm.bias loaded from res3_2_branch2c_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv3.norm.running_mean loaded from res3_2_branch2c_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv3.norm.running_var loaded from res3_2_branch2c_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv3.norm.weight loaded from res3_2_branch2c_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.2.conv3.weight loaded from res3_2_branch2c_w of shape (512, 128, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv1.norm.bias loaded from res3_3_branch2a_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv1.norm.running_mean loaded from res3_3_branch2a_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv1.norm.running_var loaded from res3_3_branch2a_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv1.norm.weight loaded from res3_3_branch2a_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv1.weight loaded from res3_3_branch2a_w of shape (128, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv2.norm.bias loaded from res3_3_branch2b_bn_beta of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv2.norm.running_mean loaded from res3_3_branch2b_bn_running_mean of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv2.norm.running_var loaded from res3_3_branch2b_bn_running_var of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv2.norm.weight loaded from res3_3_branch2b_bn_gamma of shape (128,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv2.weight loaded from res3_3_branch2b_w of shape (128, 128, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv3.norm.bias loaded from res3_3_branch2c_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv3.norm.running_mean loaded from res3_3_branch2c_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv3.norm.running_var loaded from res3_3_branch2c_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv3.norm.weight loaded from res3_3_branch2c_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res3.3.conv3.weight loaded from res3_3_branch2c_w of shape (512, 128, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv1.norm.bias loaded from res4_0_branch2a_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv1.norm.running_mean loaded from res4_0_branch2a_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv1.norm.running_var loaded from res4_0_branch2a_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv1.norm.weight loaded from res4_0_branch2a_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv1.weight loaded from res4_0_branch2a_w of shape (256, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv2.norm.bias loaded from res4_0_branch2b_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv2.norm.running_mean loaded from res4_0_branch2b_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv2.norm.running_var loaded from res4_0_branch2b_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv2.norm.weight loaded from res4_0_branch2b_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv2.weight loaded from res4_0_branch2b_w of shape (256, 256, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv3.norm.bias loaded from res4_0_branch2c_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv3.norm.running_mean loaded from res4_0_branch2c_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv3.norm.running_var loaded from res4_0_branch2c_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv3.norm.weight loaded from res4_0_branch2c_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.conv3.weight loaded from res4_0_branch2c_w of shape (1024, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.shortcut.norm.bias loaded from res4_0_branch1_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.shortcut.norm.running_mean loaded from res4_0_branch1_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.shortcut.norm.running_var loaded from res4_0_branch1_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.shortcut.norm.weight loaded from res4_0_branch1_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.0.shortcut.weight loaded from res4_0_branch1_w of shape (1024, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv1.norm.bias loaded from res4_1_branch2a_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv1.norm.running_mean loaded from res4_1_branch2a_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv1.norm.running_var loaded from res4_1_branch2a_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv1.norm.weight loaded from res4_1_branch2a_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv1.weight loaded from res4_1_branch2a_w of shape (256, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv2.norm.bias loaded from res4_1_branch2b_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv2.norm.running_mean loaded from res4_1_branch2b_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv2.norm.running_var loaded from res4_1_branch2b_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv2.norm.weight loaded from res4_1_branch2b_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv2.weight loaded from res4_1_branch2b_w of shape (256, 256, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv3.norm.bias loaded from res4_1_branch2c_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv3.norm.running_mean loaded from res4_1_branch2c_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv3.norm.running_var loaded from res4_1_branch2c_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv3.norm.weight loaded from res4_1_branch2c_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.1.conv3.weight loaded from res4_1_branch2c_w of shape (1024, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv1.norm.bias loaded from res4_2_branch2a_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv1.norm.running_mean loaded from res4_2_branch2a_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv1.norm.running_var loaded from res4_2_branch2a_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv1.norm.weight loaded from res4_2_branch2a_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv1.weight loaded from res4_2_branch2a_w of shape (256, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv2.norm.bias loaded from res4_2_branch2b_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv2.norm.running_mean loaded from res4_2_branch2b_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv2.norm.running_var loaded from res4_2_branch2b_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv2.norm.weight loaded from res4_2_branch2b_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv2.weight loaded from res4_2_branch2b_w of shape (256, 256, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv3.norm.bias loaded from res4_2_branch2c_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv3.norm.running_mean loaded from res4_2_branch2c_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv3.norm.running_var loaded from res4_2_branch2c_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv3.norm.weight loaded from res4_2_branch2c_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.2.conv3.weight loaded from res4_2_branch2c_w of shape (1024, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv1.norm.bias loaded from res4_3_branch2a_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv1.norm.running_mean loaded from res4_3_branch2a_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv1.norm.running_var loaded from res4_3_branch2a_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv1.norm.weight loaded from res4_3_branch2a_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv1.weight loaded from res4_3_branch2a_w of shape (256, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv2.norm.bias loaded from res4_3_branch2b_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv2.norm.running_mean loaded from res4_3_branch2b_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv2.norm.running_var loaded from res4_3_branch2b_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv2.norm.weight loaded from res4_3_branch2b_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv2.weight loaded from res4_3_branch2b_w of shape (256, 256, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv3.norm.bias loaded from res4_3_branch2c_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv3.norm.running_mean loaded from res4_3_branch2c_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv3.norm.running_var loaded from res4_3_branch2c_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv3.norm.weight loaded from res4_3_branch2c_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.3.conv3.weight loaded from res4_3_branch2c_w of shape (1024, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv1.norm.bias loaded from res4_4_branch2a_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv1.norm.running_mean loaded from res4_4_branch2a_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv1.norm.running_var loaded from res4_4_branch2a_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv1.norm.weight loaded from res4_4_branch2a_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv1.weight loaded from res4_4_branch2a_w of shape (256, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv2.norm.bias loaded from res4_4_branch2b_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv2.norm.running_mean loaded from res4_4_branch2b_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv2.norm.running_var loaded from res4_4_branch2b_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv2.norm.weight loaded from res4_4_branch2b_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv2.weight loaded from res4_4_branch2b_w of shape (256, 256, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv3.norm.bias loaded from res4_4_branch2c_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv3.norm.running_mean loaded from res4_4_branch2c_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv3.norm.running_var loaded from res4_4_branch2c_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv3.norm.weight loaded from res4_4_branch2c_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.4.conv3.weight loaded from res4_4_branch2c_w of shape (1024, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv1.norm.bias loaded from res4_5_branch2a_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv1.norm.running_mean loaded from res4_5_branch2a_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv1.norm.running_var loaded from res4_5_branch2a_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv1.norm.weight loaded from res4_5_branch2a_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv1.weight loaded from res4_5_branch2a_w of shape (256, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv2.norm.bias loaded from res4_5_branch2b_bn_beta of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv2.norm.running_mean loaded from res4_5_branch2b_bn_running_mean of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv2.norm.running_var loaded from res4_5_branch2b_bn_running_var of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv2.norm.weight loaded from res4_5_branch2b_bn_gamma of shape (256,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv2.weight loaded from res4_5_branch2b_w of shape (256, 256, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv3.norm.bias loaded from res4_5_branch2c_bn_beta of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv3.norm.running_mean loaded from res4_5_branch2c_bn_running_mean of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv3.norm.running_var loaded from res4_5_branch2c_bn_running_var of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv3.norm.weight loaded from res4_5_branch2c_bn_gamma of shape (1024,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res4.5.conv3.weight loaded from res4_5_branch2c_w of shape (1024, 256, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv1.norm.bias loaded from res5_0_branch2a_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv1.norm.running_mean loaded from res5_0_branch2a_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv1.norm.running_var loaded from res5_0_branch2a_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv1.norm.weight loaded from res5_0_branch2a_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv1.weight loaded from res5_0_branch2a_w of shape (512, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv2.weight loaded from res5_0_branch2b_w of shape (512, 512, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv3.norm.bias loaded from res5_0_branch2c_bn_beta of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv3.norm.running_mean loaded from res5_0_branch2c_bn_running_mean of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv3.norm.running_var loaded from res5_0_branch2c_bn_running_var of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv3.norm.weight loaded from res5_0_branch2c_bn_gamma of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.conv3.weight loaded from res5_0_branch2c_w of shape (2048, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.shortcut.norm.bias loaded from res5_0_branch1_bn_beta of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.shortcut.norm.running_mean loaded from res5_0_branch1_bn_running_mean of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.shortcut.norm.running_var loaded from res5_0_branch1_bn_running_var of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.shortcut.norm.weight loaded from res5_0_branch1_bn_gamma of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.0.shortcut.weight loaded from res5_0_branch1_w of shape (2048, 1024, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv1.norm.bias loaded from res5_1_branch2a_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv1.norm.running_mean loaded from res5_1_branch2a_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv1.norm.running_var loaded from res5_1_branch2a_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv1.norm.weight loaded from res5_1_branch2a_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv1.weight loaded from res5_1_branch2a_w of shape (512, 2048, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv2.weight loaded from res5_1_branch2b_w of shape (512, 512, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv3.norm.bias loaded from res5_1_branch2c_bn_beta of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv3.norm.running_mean loaded from res5_1_branch2c_bn_running_mean of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv3.norm.running_var loaded from res5_1_branch2c_bn_running_var of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv3.norm.weight loaded from res5_1_branch2c_bn_gamma of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.1.conv3.weight loaded from res5_1_branch2c_w of shape (2048, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv1.norm.bias loaded from res5_2_branch2a_bn_beta of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv1.norm.running_mean loaded from res5_2_branch2a_bn_running_mean of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv1.norm.running_var loaded from res5_2_branch2a_bn_running_var of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv1.norm.weight loaded from res5_2_branch2a_bn_gamma of shape (512,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv1.weight loaded from res5_2_branch2a_w of shape (512, 2048, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv2.weight loaded from res5_2_branch2b_w of shape (512, 512, 3, 3) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv3.norm.bias loaded from res5_2_branch2c_bn_beta of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv3.norm.running_mean loaded from res5_2_branch2c_bn_running_mean of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv3.norm.running_var loaded from res5_2_branch2c_bn_running_var of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv3.norm.weight loaded from res5_2_branch2c_bn_gamma of shape (2048,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.res5.2.conv3.weight loaded from res5_2_branch2c_w of shape (2048, 512, 1, 1) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.stem.conv1.norm.bias loaded from res_conv1_bn_beta of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.stem.conv1.norm.running_mean loaded from res_conv1_bn_running_mean of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.stem.conv1.norm.running_var loaded from res_conv1_bn_running_var of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.stem.conv1.norm.weight loaded from res_conv1_bn_gamma of shape (64,) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: backbone.bottom_up.stem.conv1.weight loaded from conv1_w of shape (64, 3, 7, 7) [11/02 10:57:27 d2.checkpoint.c2_model_loading]: Some model parameters are not in the checkpoint: backbone.bottom_up.res5.0.conv2.bias backbone.bottom_up.res5.1.conv2.bias backbone.bottom_up.res5.2.conv2.bias backbone.bottom_up.res6.0.conv1.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.0.conv1.weight backbone.bottom_up.res6.0.conv2.{bias, weight} backbone.bottom_up.res6.0.conv3.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.0.conv3.weight backbone.bottom_up.res6.0.shortcut.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.0.shortcut.weight backbone.bottom_up.res6.1.conv1.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.1.conv1.weight backbone.bottom_up.res6.1.conv2.{bias, weight} backbone.bottom_up.res6.1.conv3.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.1.conv3.weight backbone.bottom_up.res6.2.conv1.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.2.conv1.weight backbone.bottom_up.res6.2.conv2.{bias, weight} backbone.bottom_up.res6.2.conv3.norm.{bias, running_mean, running_var, weight} backbone.bottom_up.res6.2.conv3.weight backbone.fpn_lateral2.{bias, weight} backbone.fpn_lateral3.{bias, weight} backbone.fpn_lateral4.{bias, weight} backbone.fpn_output2.{bias, weight} backbone.fpn_output3.{bias, weight} backbone.fpn_output4.{bias, weight} proposal_generator.anchor_generator.cell_anchors.{0, 1, 2, 3, 4} proposal_generator.rpn_head.anchor_deltas.{bias, weight} proposal_generator.rpn_head.conv.{bias, weight} proposal_generator.rpn_head.objectness_logits.{bias, weight} roi_heads.box_head.fc1.{bias, weight} roi_heads.box_head.fc2.{bias, weight} roi_heads.box_predictor.bbox_pred.{bias, weight} roi_heads.box_predictor.cls_score.{bias, weight} [11/02 10:57:27 d2.checkpoint.c2_model_loading]: The checkpoint contains parameters not used by the model: fc1000_b fc1000_w res5_0_branch2b_bn_beta res5_0_branch2b_bn_running_mean res5_0_branch2b_bn_running_var res5_0_branch2b_bn_gamma res5_1_branch2b_bn_beta res5_1_branch2b_bn_running_mean res5_1_branch2b_bn_running_var res5_1_branch2b_bn_gamma res5_2_branch2b_bn_beta res5_2_branch2b_bn_running_mean res5_2_branch2b_bn_running_var res5_2_branch2b_bn_gamma conv1_b [11/02 10:57:27 d2.engine.train_loop]: Starting training from iteration 0 [11/02 10:57:28 d2.engine.hooks]: Total training time: 0:00:00 (0:00:00 on hooks) Traceback (most recent call last): File "tools/train_net.py", line 161, in args=(args,), File "/home/lxj/detectron2/detectron2/engine/launch.py", line 52, in launch main_func(args) File "tools/train_net.py", line 149, in main return trainer.train() File "/home/lxj/detectron2/detectron2/engine/defaults.py", line 350, in train super().train(self.start_iter, self.max_iter) File "/home/lxj/detectron2/detectron2/engine/train_loop.py", line 132, in train self.run_step() File "/home/lxj/detectron2/detectron2/engine/train_loop.py", line 212, in run_step loss_dict = self.model(data) File "/home/lxj/anaconda3/envs/detectron2/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in call result = self.forward(input, kwargs) File "/home/lxj/detectron2/detectron2/modeling/meta_arch/rcnn.py", line 79, in forward features = self.backbone(images.tensor) File "/home/lxj/anaconda3/envs/detectron2/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in call result = self.forward(*input, *kwargs) File "/home/lxj/detectron2/detectron2/modeling/backbone/fpn.py", line 134, in forward lateral_features = lateral_conv(features) File "/home/lxj/anaconda3/envs/detectron2/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in call result = self.forward(input, kwargs) File "/home/lxj/detectron2/detectron2/layers/wrappers.py", line 87, in forward x = super().forward(x) File "/home/lxj/anaconda3/envs/detectron2/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 345, in forward return self.conv2d_forward(input, self.weight) File "/home/lxj/anaconda3/envs/detectron2/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 342, in conv2d_forward self.padding, self.dilation, self.groups) RuntimeError: Input type (torch.cuda.FloatTensor) and weight type (torch.FloatTensor) should be the same I don't know how to solve it. Can anyone help me?

ppwwyyxx commented 4 years ago

I suppose the problem did not happen on the original code? Since you made modifications or wrote your own code that caused the problem, and we don't know what you did, we could not help with the problem.