| [04/17 14:10:02 detectron2]: Rank of current process: 0. World size: 8 |
| [04/17 14:10:20 detectron2]: Environment info: |
| ---------------------- -------------------------------------------------------------------------------------------------------------------------- |
| sys.platform linux |
| Python 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] |
| numpy 1.21.5 |
| detectron2 0.6 @/mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2 |
| Compiler GCC 7.3 |
| CUDA compiler CUDA 11.1 |
| detectron2 arch flags 3.7, 5.0, 5.2, 6.0, 6.1, 7.0, 7.5, 8.0, 8.6 |
| DETECTRON2_ENV_MODULE <not set> |
| PyTorch 1.10.0+cu111 @/mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch |
| PyTorch debug build False |
| GPU available Yes |
| GPU 0,1,2,3,4,5,6,7 A100-SXM4-40GB (arch=8.0) |
| Driver version 450.142.00 |
| CUDA_HOME /usr/local/cuda |
| Pillow 8.4.0 |
| torchvision 0.11.1+cu111 @/mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torchvision |
| torchvision arch flags 3.5, 5.0, 6.0, 7.0, 7.5, 8.0, 8.6 |
| fvcore 0.1.5.post20211023 |
| iopath 0.1.9 |
| cv2 Not found |
| ---------------------- -------------------------------------------------------------------------------------------------------------------------- |
| PyTorch built with: |
| - GCC 7.3 |
| - C++ Version: 201402 |
| - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications |
| - Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740) |
| - OpenMP 201511 (a.k.a. OpenMP 4.5) |
| - LAPACK is enabled (usually provided by MKL) |
| - NNPACK is enabled |
| - CPU capability usage: AVX2 |
| - CUDA Runtime 11.1 |
| - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 |
| - CuDNN 8.0.5 |
| - Magma 2.5.2 |
| - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, |
|
|
| [04/17 14:10:20 detectron2]: Command line arguments: Namespace(config_file='cascade_layoutlmv3.yaml', debug=False, dist_url='tcp://127.0.0.1:50156', eval_only=True, machine_rank=0, num_gpus=8, num_machines=1, opts=['MODEL.WEIGHTS', '/mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/model_final.pth', 'OUTPUT_DIR', '/mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/'], resume=False) |
| [04/17 14:10:20 detectron2]: Contents of args.config_file=cascade_layoutlmv3.yaml: |
| MODEL: |
| MASK_ON: True |
| MAX_LENGTH: 510 |
| IMAGE_ONLY: True |
| META_ARCHITECTURE: "VLGeneralizedRCNN" |
| PIXEL_MEAN: [ 127.5, 127.5, 127.5 ] |
| PIXEL_STD: [ 127.5, 127.5, 127.5 ] |
| WEIGHTS: "/mnt/localdata/users/yupanhuang/models/layoutlmv3/pts/layoutlmv3-base/pytorch_model.bin" |
| BACKBONE: |
| NAME: "build_vit_fpn_backbone" |
| VIT: |
| NAME: "layoutlmv3_base" |
| OUT_FEATURES: [ "layer3", "layer5", "layer7", "layer11" ] |
| DROP_PATH: 0.1 |
| IMG_SIZE: [ 224,224 ] |
| POS_TYPE: "abs" |
| ROI_HEADS: |
| NAME: CascadeROIHeads |
| IN_FEATURES: [ "p2", "p3", "p4", "p5" ] |
| NUM_CLASSES: 5 |
| ROI_BOX_HEAD: |
| CLS_AGNOSTIC_BBOX_REG: True |
| NAME: "FastRCNNConvFCHead" |
| NUM_FC: 2 |
| POOLER_RESOLUTION: 7 |
| ROI_MASK_HEAD: |
| NAME: "MaskRCNNConvUpsampleHead" |
| NUM_CONV: 4 |
| POOLER_RESOLUTION: 14 |
| FPN: |
| IN_FEATURES: [ "layer3", "layer5", "layer7", "layer11" ] |
| ANCHOR_GENERATOR: |
| SIZES: [ [ 32 ], [ 64 ], [ 128 ], [ 256 ], [ 512 ] ] # One size for each in feature map |
| ASPECT_RATIOS: [ [ 0.5, 1.0, 2.0 ] ] # Three aspect ratios (same for all in feature maps) |
| RPN: |
| IN_FEATURES: [ "p2", "p3", "p4", "p5", "p6" ] |
| PRE_NMS_TOPK_TRAIN: 2000 # Per FPN level |
| PRE_NMS_TOPK_TEST: 1000 # Per FPN level |
| # Detectron1 uses 2000 proposals per-batch, |
| # (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue) |
| # which is approximately 1000 proposals per-image since the default batch size for FPN is 2. |
| POST_NMS_TOPK_TRAIN: 2000 |
| POST_NMS_TOPK_TEST: 1000 |
| DATASETS: |
| TRAIN: ("publaynet_train",) |
| TEST: ("publaynet_val",) |
| SOLVER: |
| GRADIENT_ACCUMULATION_STEPS: 1 |
| BASE_LR: 0.0002 |
| WARMUP_ITERS: 1000 |
| IMS_PER_BATCH: 32 |
| MAX_ITER: 60000 |
| CHECKPOINT_PERIOD: 2000 |
| LR_SCHEDULER_NAME: "WarmupCosineLR" |
| AMP: |
| ENABLED: True |
| OPTIMIZER: "ADAMW" |
| BACKBONE_MULTIPLIER: 1.0 |
| CLIP_GRADIENTS: |
| ENABLED: True |
| CLIP_TYPE: "full_model" |
| CLIP_VALUE: 1.0 |
| NORM_TYPE: 2.0 |
| WARMUP_FACTOR: 0.01 |
| WEIGHT_DECAY: 0.05 |
| TEST: |
| EVAL_PERIOD: 2000 |
| INPUT: |
| CROP: |
| ENABLED: True |
| TYPE: "absolute_range" |
| SIZE: (384, 600) |
| MIN_SIZE_TRAIN: (480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800) |
| FORMAT: "RGB" |
| DATALOADER: |
| FILTER_EMPTY_ANNOTATIONS: False |
| VERSION: 2 |
| AUG: |
| DETR: True |
| SEED: 42 |
| OUTPUT_DIR: "/mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet/" |
| PUBLAYNET_DATA_DIR_TRAIN: "/mnt/localdata/users/yupanhuang/data/PubLayNet/publaynet/train" |
| PUBLAYNET_DATA_DIR_TEST: "/mnt/localdata/users/yupanhuang/data/PubLayNet/publaynet/val" |
| OCR_DATA_DIR_TRAIN: "/mnt/localdata/users/yupanhuang/data/PubLayNet/ocr/train" |
| OCR_DATA_DIR_TEST: "/mnt/localdata/users/yupanhuang/data/PubLayNet/ocr/val" |
| CACHE_DIR: "/mnt/localdata/users/yupanhuang/cache/huggingface" |
|
|
| [04/17 14:10:20 detectron2]: Running with full config: |
| AUG: |
| DETR: true |
| CACHE_DIR: /mnt/localdata/users/yupanhuang/cache/huggingface |
| CUDNN_BENCHMARK: false |
| DATALOADER: |
| ASPECT_RATIO_GROUPING: true |
| FILTER_EMPTY_ANNOTATIONS: false |
| 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: |
| - publaynet_val |
| TRAIN: |
| - publaynet_train |
| GLOBAL: |
| HACK: 1.0 |
| ICDAR_DATA_DIR_TEST: '' |
| ICDAR_DATA_DIR_TRAIN: '' |
| INPUT: |
| CROP: |
| ENABLED: true |
| SIZE: |
| - 384 |
| - 600 |
| TYPE: absolute_range |
| FORMAT: RGB |
| MASK_FORMAT: polygon |
| MAX_SIZE_TEST: 1333 |
| MAX_SIZE_TRAIN: 1333 |
| MIN_SIZE_TEST: 800 |
| MIN_SIZE_TRAIN: |
| - 480 |
| - 512 |
| - 544 |
| - 576 |
| - 608 |
| - 640 |
| - 672 |
| - 704 |
| - 736 |
| - 768 |
| - 800 |
| MIN_SIZE_TRAIN_SAMPLING: choice |
| RANDOM_FLIP: horizontal |
| MODEL: |
| ANCHOR_GENERATOR: |
| ANGLES: |
| - - -90 |
| - 0 |
| - 90 |
| ASPECT_RATIOS: |
| - - 0.5 |
| - 1.0 |
| - 2.0 |
| NAME: DefaultAnchorGenerator |
| OFFSET: 0.0 |
| SIZES: |
| - - 32 |
| - - 64 |
| - - 128 |
| - - 256 |
| - - 512 |
| BACKBONE: |
| FREEZE_AT: 2 |
| NAME: build_vit_fpn_backbone |
| CONFIG_PATH: '' |
| DEVICE: cuda |
| FPN: |
| FUSE_TYPE: sum |
| IN_FEATURES: |
| - layer3 |
| - layer5 |
| - layer7 |
| - layer11 |
| NORM: '' |
| OUT_CHANNELS: 256 |
| IMAGE_ONLY: true |
| KEYPOINT_ON: false |
| LOAD_PROPOSALS: false |
| MASK_ON: true |
| MAX_LENGTH: 510 |
| META_ARCHITECTURE: VLGeneralizedRCNN |
| 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: |
| - 127.5 |
| - 127.5 |
| - 127.5 |
| PIXEL_STD: |
| - 127.5 |
| - 127.5 |
| - 127.5 |
| 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_LOSS_TYPE: smooth_l1 |
| BBOX_REG_WEIGHTS: &id001 |
| - 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 |
| NORM: '' |
| 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_LOSS_TYPE: smooth_l1 |
| BBOX_REG_LOSS_WEIGHT: 1.0 |
| BBOX_REG_WEIGHTS: |
| - 10.0 |
| - 10.0 |
| - 5.0 |
| - 5.0 |
| CLS_AGNOSTIC_BBOX_REG: true |
| 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 |
| TRAIN_ON_PRED_BOXES: false |
| ROI_HEADS: |
| BATCH_SIZE_PER_IMAGE: 512 |
| IN_FEATURES: |
| - p2 |
| - p3 |
| - p4 |
| - p5 |
| IOU_LABELS: |
| - 0 |
| - 1 |
| IOU_THRESHOLDS: |
| - 0.5 |
| NAME: CascadeROIHeads |
| NMS_THRESH_TEST: 0.5 |
| NUM_CLASSES: 5 |
| 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_LOSS_TYPE: smooth_l1 |
| BBOX_REG_LOSS_WEIGHT: 1.0 |
| BBOX_REG_WEIGHTS: *id001 |
| BOUNDARY_THRESH: -1 |
| CONV_DIMS: |
| - -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: 2000 |
| 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 |
| VIT: |
| DROP_PATH: 0.1 |
| IMG_SIZE: |
| - 224 |
| - 224 |
| MODEL_KWARGS: '{}' |
| NAME: layoutlmv3_base |
| OUT_FEATURES: |
| - layer3 |
| - layer5 |
| - layer7 |
| - layer11 |
| POS_TYPE: abs |
| WEIGHTS: /mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/model_final.pth |
| OCR_DATA_DIR_TEST: /mnt/localdata/users/yupanhuang/data/PubLayNet/ocr/val |
| OCR_DATA_DIR_TRAIN: /mnt/localdata/users/yupanhuang/data/PubLayNet/ocr/train |
| OUTPUT_DIR: /mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/ |
| PUBLAYNET_DATA_DIR_TEST: /mnt/localdata/users/yupanhuang/data/PubLayNet/publaynet/val |
| PUBLAYNET_DATA_DIR_TRAIN: /mnt/localdata/users/yupanhuang/data/PubLayNet/publaynet/train |
| SEED: 42 |
| SOLVER: |
| AMP: |
| ENABLED: true |
| BACKBONE_MULTIPLIER: 1.0 |
| BASE_LR: 0.0002 |
| BIAS_LR_FACTOR: 1.0 |
| CHECKPOINT_PERIOD: 2000 |
| CLIP_GRADIENTS: |
| CLIP_TYPE: full_model |
| CLIP_VALUE: 1.0 |
| ENABLED: true |
| NORM_TYPE: 2.0 |
| GAMMA: 0.1 |
| GRADIENT_ACCUMULATION_STEPS: 1 |
| IMS_PER_BATCH: 32 |
| LR_SCHEDULER_NAME: WarmupCosineLR |
| MAX_ITER: 60000 |
| MOMENTUM: 0.9 |
| NESTEROV: false |
| OPTIMIZER: ADAMW |
| REFERENCE_WORLD_SIZE: 0 |
| STEPS: |
| - 30000 |
| WARMUP_FACTOR: 0.01 |
| WARMUP_ITERS: 1000 |
| WARMUP_METHOD: linear |
| WEIGHT_DECAY: 0.05 |
| WEIGHT_DECAY_BIAS: null |
| 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: 2000 |
| EXPECTED_RESULTS: [] |
| KEYPOINT_OKS_SIGMAS: [] |
| PRECISE_BN: |
| ENABLED: false |
| NUM_ITER: 200 |
| VERSION: 2 |
| VIS_PERIOD: 0 |
|
|
| [04/17 14:10:20 detectron2]: Full config saved to /mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/config.yaml |
| [04/17 14:10:21 fvcore.common.checkpoint]: [Checkpointer] Loading from /mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/model_final.pth ... |
| [04/17 14:10:23 d2.data.datasets.coco]: Loading /mnt/localdata/users/yupanhuang/data/PubLayNet/publaynet/val.json takes 1.71 seconds. |
| [04/17 14:10:24 d2.data.datasets.coco]: Loaded 11245 images in COCO format from /mnt/localdata/users/yupanhuang/data/PubLayNet/publaynet/val.json |
| [04/17 14:10:25 d2.data.build]: Distribution of instances among all 5 categories: |
| | category | #instances | category | #instances | category | #instances | |
| |:----------:|:-------------|:----------:|:-------------|:----------:|:-------------| |
| | text | 88625 | title | 18801 | list | 4239 | |
| | table | 4769 | figure | 4327 | | | |
| | total | 120761 | | | | | |
| [04/17 14:10:25 d2.data.common]: Serializing 11245 elements to byte tensors and concatenating them all ... |
| [04/17 14:10:25 d2.data.common]: Serialized dataset takes 55.80 MiB |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| [04/17 14:10:27 d2.evaluation.evaluator]: Start inference on 1406 batches |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/detectron2/structures/image_list.py:88: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). |
| max_size = (max_size + (stride - 1)) // stride * stride |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. |
| "See the documentation of nn.Upsample for details.".format(mode) |
| /mnt/localdata/users/yupanhuang/Downloads/miniconda3/envs/layoutlmft/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.) |
| return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] |
| [04/17 14:10:39 d2.evaluation.evaluator]: Inference done 11/1406. Dataloading: 0.0029 s/iter. Inference: 0.1609 s/iter. Eval: 0.0212 s/iter. Total: 0.1850 s/iter. ETA=0:04:18 |
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| [04/17 14:15:04 d2.evaluation.evaluator]: Inference done 1385/1406. Dataloading: 0.0031 s/iter. Inference: 0.1767 s/iter. Eval: 0.0125 s/iter. Total: 0.1924 s/iter. ETA=0:00:04 |
| [04/17 14:15:08 d2.evaluation.evaluator]: Total inference time: 0:04:29.845715 (0.192609 s / iter per device, on 8 devices) |
| [04/17 14:15:08 d2.evaluation.evaluator]: Total inference pure compute time: 0:04:07 (0.176466 s / iter per device, on 8 devices) |
| [04/17 14:15:17 d2.evaluation.coco_evaluation]: Preparing results for COCO format ... |
| [04/17 14:15:17 d2.evaluation.coco_evaluation]: Saving results to /mnt/localdata/users/yupanhuang/models/layoutlmv3/fts/publaynet-base/inference/coco_instances_results.json |
| [04/17 14:15:18 d2.evaluation.coco_evaluation]: Evaluating predictions with unofficial COCO API... |
| Loading and preparing results... |
| DONE (t=0.12s) |
| creating index... |
| index created! |
| [04/17 14:15:19 d2.evaluation.fast_eval_api]: Evaluate annotation type *bbox* |
| [04/17 14:15:22 d2.evaluation.fast_eval_api]: COCOeval_opt.evaluate() finished in 3.39 seconds. |
| [04/17 14:15:22 d2.evaluation.fast_eval_api]: Accumulating evaluation results... |
| [04/17 14:15:23 d2.evaluation.fast_eval_api]: COCOeval_opt.accumulate() finished in 0.40 seconds. |
| Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.951 |
| Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.981 |
| Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.969 |
| Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.468 |
| Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.856 |
| Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.976 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.543 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.953 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.964 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.607 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.897 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.986 |
| [04/17 14:15:23 d2.evaluation.coco_evaluation]: Evaluation results for bbox: |
| | AP | AP50 | AP75 | APs | APm | APl | |
| |:------:|:------:|:------:|:------:|:------:|:------:| |
| | 95.088 | 98.066 | 96.933 | 46.800 | 85.592 | 97.626 | |
| [04/17 14:15:23 d2.evaluation.coco_evaluation]: Per-category bbox AP: |
| | category | AP | category | AP | category | AP | |
| |:-----------|:-------|:-----------|:-------|:-----------|:-------| |
| | text | 94.466 | title | 90.569 | list | 95.522 | |
| | table | 97.883 | figure | 97.001 | | | |
| Loading and preparing results... |
| DONE (t=2.05s) |
| creating index... |
| index created! |
| [04/17 14:15:28 d2.evaluation.fast_eval_api]: Evaluate annotation type *segm* |
| [04/17 14:15:38 d2.evaluation.fast_eval_api]: COCOeval_opt.evaluate() finished in 10.92 seconds. |
| [04/17 14:15:39 d2.evaluation.fast_eval_api]: Accumulating evaluation results... |
| [04/17 14:15:39 d2.evaluation.fast_eval_api]: COCOeval_opt.accumulate() finished in 0.43 seconds. |
| Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.928 |
| Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.981 |
| Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.967 |
| Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.506 |
| Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.824 |
| Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.959 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.535 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.938 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.949 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.632 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.879 |
| Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.973 |
| [04/17 14:15:39 d2.evaluation.coco_evaluation]: Evaluation results for segm: |
| | AP | AP50 | AP75 | APs | APm | APl | |
| |:------:|:------:|:------:|:------:|:------:|:------:| |
| | 92.819 | 98.070 | 96.719 | 50.628 | 82.397 | 95.917 | |
| [04/17 14:15:39 d2.evaluation.coco_evaluation]: Per-category segm AP: |
| | category | AP | category | AP | category | AP | |
| |:-----------|:-------|:-----------|:-------|:-----------|:-------| |
| | text | 93.433 | title | 87.009 | list | 88.864 | |
| | table | 97.799 | figure | 96.989 | | | |
| [04/17 14:15:40 d2.evaluation.testing]: copypaste: Task: bbox |
| [04/17 14:15:40 d2.evaluation.testing]: copypaste: AP,AP50,AP75,APs,APm,APl |
| [04/17 14:15:40 d2.evaluation.testing]: copypaste: 95.0883,98.0662,96.9331,46.8005,85.5919,97.6258 |
| [04/17 14:15:40 d2.evaluation.testing]: copypaste: Task: segm |
| [04/17 14:15:40 d2.evaluation.testing]: copypaste: AP,AP50,AP75,APs,APm,APl |
| [04/17 14:15:40 d2.evaluation.testing]: copypaste: 92.8187,98.0704,96.7191,50.6278,82.3972,95.9172 |
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