diff --git "a/grounding_rgbd_dat_mixdata/job.log" "b/grounding_rgbd_dat_mixdata/job.log" new file mode 100644--- /dev/null +++ "b/grounding_rgbd_dat_mixdata/job.log" @@ -0,0 +1,11469 @@ +172.16.166.96 +172.16.165.65 +url2IP complete ! +172.16.166.96 +172.16.165.65 +172.16.166.96 +Warning: Permanently added '172.16.166.96' (ED25519) to the list of known hosts. +172.16.165.65 +Warning: Permanently added '172.16.165.65' (ED25519) to the list of known hosts. +/running_package/bip3d/ssh_launcher.py:107: DeprecationWarning: setDaemon() is deprecated, set the daemon attribute instead + thread.setDaemon(True) +Warning: Permanently added '172.16.165.65' (ED25519) to the list of known hosts. +Warning: Permanently added '172.16.166.96' (ED25519) to the list of known hosts. +bash: line 1: export: `-Xmx10000m': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `1': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `4': not a valid identifier +bash: line 1: export: `/mpi_run.sh': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_ssh.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +python3: can't open file '/running_package/bip3d/nccl_check.py': [Errno 2] No such file or directory +bash: line 1: export: `-Xmx10000m': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `1': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `4': not a valid identifier +bash: line 1: export: `/mpi_run.sh': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_ssh.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +subprocess(ssh -o StrictHostKeyChecking=no 172.16.166.96 'export GPU_STR=0,1,2,3,4,5,6,7; export LIBRARY_PATH=/usr/local/cuda/lib64/stubs:; export TBOARD_DIR=/job_tboard; export KUBERNETES_SERVICE_PORT=443; export AITC_MODE=prod; export KUBERNETES_PORT=tcp://20.254.0.1:443; export JOB_ID=70328269; export MAIL=/var/mail/xuewu.lin; export JAVA_TOOL_OPTIONS=-Xms512m -Xmx10000m; export HOSTNAME=hobot-job-70328269-task-1; export RAW_JOBNAME=bip3d_det_grounding_fromdetpret_step5w-20250223-111041.468432; export VC_TASK_NUM=2; export XDG_CACHE_HOME=/home/linuxbrew/.cache; export SHLVL=0; export LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64::/usr/local/cuda/lib64/:/App/hadoop-2.7.2/lib/native:/usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server; export PBS_JOBNAME=bip3d_det_grounding_fromdetpret_step5w-20250223-111041.468432; export HOME=/home/users/xuewu.lin; export OLDPWD=/running_package; export HADOOP_PREFIX=/App/hadoop-2.7.2; export JOB_SCHEDULE_TYPE=topo; export VC_TASK_HOSTS=hobot-job-70328269-task-0.hobot-job-70328269,hobot-job-70328269-task-1.hobot-job-70328269; export LOCAL_MPI_SUBMIT=python /App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py -n 1 -s 4; export TENSORBOARD_LOG_PATH=/job_tboard/; export bucket_robot_lab=/bucket/output/robot_lab; export RUN_ENV=prod; export USER_TOKEN=eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjIzMTkwOTg0MDIsIlRva2VuVHlwZSI6ImxkYXAiLCJVSUQiOjgyMywiSGFzaFVJRCI6MjgyMzU5NzU0NywiVXNlck5hbWUiOiJ4dWV3dS5saW4iLCJFbWFpbCI6IiIsIlRlbmFudCI6InJlZ3VsYXItZW5naW5lZXIiLCJUZW5hbnRJRCI6MSwiT3JnYW5pemF0aW9uIjoicmVndWxhci1lbmdpbmVlciIsIk9yZ2FuaXphdGlvbklEIjoxLCJWZXJzaW9uIjoidjIifQ.HeQ1ZVjIBbKUwVPEPn5u4P-wXaB4_xh6bAm-FQh_G6kILgvd1xXb0nB0Km8yfz7goUrhtiqhoRaWGZPNttqnsXUNgoGR0eMT7dhB01P61ksOIi5bLJcwfGAiqbPaRFFG0lfarIOOV8UEUQh8Honlu5C50qAIP64831gKrNKbiIst34pLfz_vpqvccMkYeKaQihM7F9sxm9SmPSR_Vwoh_RStuVGbF5xIwBT19_yW4gRvUUW4xIU42kdVr_4z0nBZiG3qZP-R_30kgNjT2Yn8exuHrK0LUt0J4GbCGb-4EkUo1CdtOVZDd7lkoEd3-KayHW0qiNJydkwz-LuoTGy1ng; export NODE_NAME=idcgpu-4090-075.hogpu.cc; export _=/usr/bin/sh; export DIR_OUT=/job_tboard; export JOB_SCRIPT=sh ${WORKING_PATH}/mpi_run.sh; export NVIDIA_DRIVER_CAPABILITIES=all; export WORKER_NUM=2; export JOB_PASSWORD=6150; export KUBERNETES_PORT_443_TCP_ADDR=20.254.0.1; export CLUSTER=idc-newage; export PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin; export MEM_LIMIT=773094113280; export KUBERNETES_PORT_443_TCP_PORT=443; export JOB_USER=xuewu.lin; export VC_TASK_INDEX=1; export PACKAGE_PATH=s3://job-package-bos/user/xuewu.lin/bip3d_det_grounding_fromdetpret_step5w-20250223-111041.468432/job.tar.gz.enc; export KUBERNETES_PORT_443_TCP_PROTO=tcp; export SSH_SUBMIT=python /App/hr-mxnet/ps-lite/tracker/dmlc_ssh.py -n 2 -s 2 -H /etc/volcano/task.host; export LANG=en_US.UTF-8; export UNI_API_ADDR=dl-nginx-service.dlp; export JOB_TYPE=train; export CPU_LIMIT=104; export MAX_PREPARE_DISTRIBUTE_TIME=1800; export KUBERNETES_SERVICE_PORT_HTTPS=443; export VK_TASK_INDEX=1; export KUBERNETES_PORT_443_TCP=tcp://20.254.0.1:443; export CLASSPATH=/App/hadoop-2.7.2/lib/classpath_hdfs.jar; export WORKING_PATH=/running_package/bip3d; export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre; export PWD=/running_package/bip3d; export KUBERNETES_SERVICE_HOST=20.254.0.1; export HADOOP_HDFS_HOME=/App/hadoop-2.7.2; export NVIDIA_VISIBLE_DEVICES=GPU-591c622a-8228-a2ec-8a7f-85a0ae5066f1,GPU-91b33d46-0773-7a86-902a-1efdde7933f9,GPU-b89685ba-fdfc-6da0-030e-5d7134a4ddeb,GPU-0f54d44f-6dbf-9603-6581-7992265edfc3,GPU-b73abd35-5c29-422f-dbca-591b16964453,GPU-78803c2a-974f-0362-a9ce-9d3b0b413b18,GPU-f2c3a530-126d-b344-b31c-f62c494ef9b4,GPU-09a87582-cb58-04e3-29c7-fabcea173b18; export MPI_SUBMIT=python /App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py -n 2 -s 2 -H /etc/volcano/task.host; export TZ=Asia/Shanghai; export HOMEBREW_RUBY3=1; export HADOOP_HOME=/App/hadoop-2.7.2; export DEVICE=; export HOST_NODE_ADDR=172.16.166.96; export HOST_NODE=172.16.166.96; cd /running_package/bip3d/; python3 nccl_check.py --driver --ngpus 8 --nccl') failed(2)! None. + +python3: can't open file '/running_package/bip3d/nccl_check.py': [Errno 2] No such file or directory +subprocess(ssh -o StrictHostKeyChecking=no 172.16.165.65 'export GPU_STR=0,1,2,3,4,5,6,7; export LIBRARY_PATH=/usr/local/cuda/lib64/stubs:; export TBOARD_DIR=/job_tboard; export KUBERNETES_SERVICE_PORT=443; export AITC_MODE=prod; export KUBERNETES_PORT=tcp://20.254.0.1:443; export JOB_ID=70328269; export MAIL=/var/mail/xuewu.lin; export JAVA_TOOL_OPTIONS=-Xms512m -Xmx10000m; export HOSTNAME=hobot-job-70328269-task-1; export RAW_JOBNAME=bip3d_det_grounding_fromdetpret_step5w-20250223-111041.468432; export VC_TASK_NUM=2; export XDG_CACHE_HOME=/home/linuxbrew/.cache; export SHLVL=0; export LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64::/usr/local/cuda/lib64/:/App/hadoop-2.7.2/lib/native:/usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server; export PBS_JOBNAME=bip3d_det_grounding_fromdetpret_step5w-20250223-111041.468432; export HOME=/home/users/xuewu.lin; export OLDPWD=/running_package; export HADOOP_PREFIX=/App/hadoop-2.7.2; export JOB_SCHEDULE_TYPE=topo; export VC_TASK_HOSTS=hobot-job-70328269-task-0.hobot-job-70328269,hobot-job-70328269-task-1.hobot-job-70328269; export LOCAL_MPI_SUBMIT=python /App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py -n 1 -s 4; export TENSORBOARD_LOG_PATH=/job_tboard/; export bucket_robot_lab=/bucket/output/robot_lab; export RUN_ENV=prod; export USER_TOKEN=eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjIzMTkwOTg0MDIsIlRva2VuVHlwZSI6ImxkYXAiLCJVSUQiOjgyMywiSGFzaFVJRCI6MjgyMzU5NzU0NywiVXNlck5hbWUiOiJ4dWV3dS5saW4iLCJFbWFpbCI6IiIsIlRlbmFudCI6InJlZ3VsYXItZW5naW5lZXIiLCJUZW5hbnRJRCI6MSwiT3JnYW5pemF0aW9uIjoicmVndWxhci1lbmdpbmVlciIsIk9yZ2FuaXphdGlvbklEIjoxLCJWZXJzaW9uIjoidjIifQ.HeQ1ZVjIBbKUwVPEPn5u4P-wXaB4_xh6bAm-FQh_G6kILgvd1xXb0nB0Km8yfz7goUrhtiqhoRaWGZPNttqnsXUNgoGR0eMT7dhB01P61ksOIi5bLJcwfGAiqbPaRFFG0lfarIOOV8UEUQh8Honlu5C50qAIP64831gKrNKbiIst34pLfz_vpqvccMkYeKaQihM7F9sxm9SmPSR_Vwoh_RStuVGbF5xIwBT19_yW4gRvUUW4xIU42kdVr_4z0nBZiG3qZP-R_30kgNjT2Yn8exuHrK0LUt0J4GbCGb-4EkUo1CdtOVZDd7lkoEd3-KayHW0qiNJydkwz-LuoTGy1ng; export NODE_NAME=idcgpu-4090-075.hogpu.cc; export _=/usr/bin/sh; export DIR_OUT=/job_tboard; export JOB_SCRIPT=sh ${WORKING_PATH}/mpi_run.sh; export NVIDIA_DRIVER_CAPABILITIES=all; export WORKER_NUM=2; export JOB_PASSWORD=6150; export KUBERNETES_PORT_443_TCP_ADDR=20.254.0.1; export CLUSTER=idc-newage; export PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin; export MEM_LIMIT=773094113280; export KUBERNETES_PORT_443_TCP_PORT=443; export JOB_USER=xuewu.lin; export VC_TASK_INDEX=1; export PACKAGE_PATH=s3://job-package-bos/user/xuewu.lin/bip3d_det_grounding_fromdetpret_step5w-20250223-111041.468432/job.tar.gz.enc; export KUBERNETES_PORT_443_TCP_PROTO=tcp; export SSH_SUBMIT=python /App/hr-mxnet/ps-lite/tracker/dmlc_ssh.py -n 2 -s 2 -H /etc/volcano/task.host; export LANG=en_US.UTF-8; export UNI_API_ADDR=dl-nginx-service.dlp; export JOB_TYPE=train; export CPU_LIMIT=104; export MAX_PREPARE_DISTRIBUTE_TIME=1800; export KUBERNETES_SERVICE_PORT_HTTPS=443; export VK_TASK_INDEX=1; export KUBERNETES_PORT_443_TCP=tcp://20.254.0.1:443; export CLASSPATH=/App/hadoop-2.7.2/lib/classpath_hdfs.jar; export WORKING_PATH=/running_package/bip3d; export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre; export PWD=/running_package/bip3d; export KUBERNETES_SERVICE_HOST=20.254.0.1; export HADOOP_HDFS_HOME=/App/hadoop-2.7.2; export NVIDIA_VISIBLE_DEVICES=GPU-591c622a-8228-a2ec-8a7f-85a0ae5066f1,GPU-91b33d46-0773-7a86-902a-1efdde7933f9,GPU-b89685ba-fdfc-6da0-030e-5d7134a4ddeb,GPU-0f54d44f-6dbf-9603-6581-7992265edfc3,GPU-b73abd35-5c29-422f-dbca-591b16964453,GPU-78803c2a-974f-0362-a9ce-9d3b0b413b18,GPU-f2c3a530-126d-b344-b31c-f62c494ef9b4,GPU-09a87582-cb58-04e3-29c7-fabcea173b18; export MPI_SUBMIT=python /App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py -n 2 -s 2 -H /etc/volcano/task.host; export TZ=Asia/Shanghai; export HOMEBREW_RUBY3=1; export HADOOP_HOME=/App/hadoop-2.7.2; export DEVICE=; export HOST_NODE_ADDR=172.16.166.96; export HOST_NODE=172.16.165.65; cd /running_package/bip3d/; python3 nccl_check.py --driver --ngpus 8 --nccl') failed(2)! None. + +Warning: Permanently added '172.16.165.65' (ED25519) to the list of known hosts. +Warning: Permanently added '172.16.166.96' (ED25519) to the list of known hosts. +bash: line 1: export: `-Xmx10000m': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `1': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `4': not a valid identifier +bash: line 1: export: `/mpi_run.sh': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_ssh.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +dist_url= +anchor_files +bip3d +ckpt +configs +custom_cmd_per_machine.sh +data +draw_bbox3d_utils.py +get_rank.py +mpi_run.sh +python_run.sh +ssh_launcher.py +tools +url2IP.py +/running_package/bip3d!!!!! +bash: line 1: export: `-Xmx10000m': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `1': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `4': not a valid identifier +bash: line 1: export: `/mpi_run.sh': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_ssh.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +bash: line 1: export: `/App/hr-mxnet/ps-lite/tracker/dmlc_mpi.py': not a valid identifier +bash: line 1: export: `-n': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-s': not a valid identifier +bash: line 1: export: `2': not a valid identifier +bash: line 1: export: `-H': not a valid identifier +bash: line 1: export: `/etc/volcano/task.host': not a valid identifier +dist_url= +anchor_files +bip3d +ckpt +configs +custom_cmd_per_machine.sh +data +draw_bbox3d_utils.py +get_rank.py +mpi_run.sh +python_run.sh +ssh_launcher.py +tools +url2IP.py +/running_package/bip3d!!!!! +--node_rank 1 --master_addr 172.16.166.96 +--node_rank 0 --master_addr 172.16.166.96 +/usr/local/lib/python3.10/dist-packages/torch/distributed/launch.py:181: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use-env is set by default in torchrun. +If your script expects `--local-rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +[2025-02-23 11:13:17,689] torch.distributed.run: [WARNING] +[2025-02-23 11:13:17,689] torch.distributed.run: [WARNING] ***************************************** +[2025-02-23 11:13:17,689] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +[2025-02-23 11:13:17,689] torch.distributed.run: [WARNING] ***************************************** +/usr/local/lib/python3.10/dist-packages/torch/distributed/launch.py:181: FutureWarning: The module torch.distributed.launch is deprecated +and will be removed in future. Use torchrun. +Note that --use-env is set by default in torchrun. +If your script expects `--local-rank` argument to be set, please +change it to read from `os.environ['LOCAL_RANK']` instead. See +https://pytorch.org/docs/stable/distributed.html#launch-utility for +further instructions + + warnings.warn( +[2025-02-23 11:13:17,705] torch.distributed.run: [WARNING] +[2025-02-23 11:13:17,705] torch.distributed.run: [WARNING] ***************************************** +[2025-02-23 11:13:17,705] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +[2025-02-23 11:13:17,705] torch.distributed.run: [WARNING] ***************************************** +[2025-02-23 11:13:28,734] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,737] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,737] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,750] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,750] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,750] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,750] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,752] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,756] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,757] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,757] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,757] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +df: /home/users/xuewu.lin/.triton/autotune: No such file or directory +[2025-02-23 11:13:28,784] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,784] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +[2025-02-23 11:13:28,790] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +df: df: df: /home/users/xuewu.lin/.triton/autotune/home/users/xuewu.lin/.triton/autotune/home/users/xuewu.lin/.triton/autotune: No such file or directory +: No such file or directory +: No such file or directory +[2025-02-23 11:13:28,795] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io requires the dev libaio .so object and headers but these were not found. + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt [WARNING]  async_io: please install the libaio-dev package with apt + + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt [WARNING]  async_io: please install the libaio-dev package with apt + + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  async_io: please install the libaio-dev package with apt + [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. + [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible + [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1 + [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +/usr/local/lib/python3.10/dist-packages/mmengine/utils/dl_utils/setup_env.py:56: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. + warnings.warn( +02/23 11:13:31 - mmengine - WARNING - Failed to search registry with scope "bip3d" in the "log_processor" registry tree. As a workaround, the current "log_processor" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "bip3d" is a correct scope, or whether the registry is initialized. +02/23 11:13:31 - mmengine - INFO - +------------------------------------------------------------ +System environment: + sys.platform: linux + Python: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] + CUDA available: True + MUSA available: False + numpy_random_seed: 0 + GPU 0,1,2,3,4,5,6,7: NVIDIA GeForce RTX 4090 + CUDA_HOME: /usr/local/cuda + NVCC: Cuda compilation tools, release 11.8, V11.8.89 + GCC: x86_64-linux-gnu-gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 + PyTorch: 2.1.0+cu118 + PyTorch compiling details: PyTorch built with: + - GCC 9.3 + - C++ Version: 201703 + - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v3.1.1 (Git Hash 64f6bcbcbab628e96f33a62c3e975f8535a7bde4) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX512 + - CUDA Runtime 11.8 + - NVCC architecture flags: -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;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_90,code=sm_90 + - CuDNN 8.9.4 + - Built with CuDNN 8.7 + - Magma 2.6.1 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-unused-private-field -Wno-aligned-allocation-unavailable -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.1.0, 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=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + + TorchVision: 0.16.0+cu118 + OpenCV: 4.10.0 + MMEngine: 0.10.4 + +Runtime environment: + cudnn_benchmark: False + mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} + dist_cfg: {'backend': 'nccl'} + seed: 0 + Distributed launcher: pytorch + Distributed training: True + GPU number: 16 +------------------------------------------------------------ + +02/23 11:13:33 - mmengine - INFO - Config: +backend_args = None +cam_standardization = True +class_names = ( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', +) +common_labels = [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, +] +custom_hooks = [ + dict(after_iter=False, type='EmptyCacheHook'), +] +data_root = 'data' +data_version = 'v1' +dataset_type = 'EmbodiedScanDetGroundingDataset' +default_hooks = dict( + checkpoint=dict( + by_epoch=False, + interval=20000, + max_keep_ckpts=3, + type='CheckpointHook'), + logger=dict(interval=25, log_metric_by_epoch=False, type='LoggerHook'), + param_scheduler=dict(type='ParamSchedulerHook'), + sampler_seed=dict(type='DistSamplerSeedHook'), + timer=dict(type='IterTimerHook')) +default_scope = 'bip3d' +depth = True +depth_loss = True +det_train_dataset = dict( + ann_file='embodiedscan/embodiedscan_infos_train.pkl', + box_type_3d='Euler-Depth', + data_root='data', + filter_empty_gt=True, + metainfo=dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )), + pipeline=[ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=18, + n_images=1, + ordered=False, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + dict( + data_aug_conf=dict( + H=512, + W=512, + bot_pct_lim=( + 0.0, + 0.05, + ), + final_dim=( + 512, + 512, + ), + rand_flip=False, + resize_lim=( + 1.0, + 1.0, + ), + rot_lim=( + 0, + 0, + )), + type='ResizeCropFlipImage'), + ], + type='MultiViewPipeline'), + dict( + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + filter_others=True, + max_class=128, + sep_token='[SEP]', + training=True, + type='CategoryGroundingDataPrepare', + z_range=[ + -0.2, + 3, + ]), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + dict( + max_depth=10, + min_depth=0.25, + num_depth=64, + origin_stride=4, + type='DepthProbLabelGenerator'), + ], + test_mode=False, + type='EmbodiedScanDetGroundingDataset') +env_cfg = dict( + cudnn_benchmark=False, + dist_cfg=dict(backend='nccl'), + mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) +find_unused_parameters = False +head_labels = [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, +] +if_cluster = True +image_wh = ( + 512, + 512, +) +launcher = 'pytorch' +load_from = 'http://svcspawner.bcloud.hobot.cc/user/homespace/xuewu.lin/plat_gpu/bip3d_det_withdepth_img18-20250209-112800.789859/output/work_dirs/epoch_24.pth' +log_level = 'INFO' +log_processor = dict(by_epoch=False, type='LogProcessor', window_size=50) +lr = 0.0002 +max_depth = 10 +max_epochs = 2 +max_iters = 50000 +metainfo = dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )) +min_depth = 0.25 +model = dict( + backbone=dict( + attn_drop_rate=0.0, + convert_weights=False, + depths=[ + 2, + 2, + 6, + 2, + ], + drop_path_rate=0.2, + drop_rate=0.0, + embed_dims=96, + mlp_ratio=4, + num_heads=[ + 3, + 6, + 12, + 24, + ], + out_indices=( + 1, + 2, + 3, + ), + patch_norm=True, + qk_scale=None, + qkv_bias=True, + type='mmdet.SwinTransformer', + window_size=7, + with_cp=True), + backbone_3d=dict( + base_channels=4, + depth=34, + in_channels=1, + norm_cfg=dict(requires_grad=True, type='BN'), + norm_eval=True, + num_stages=4, + out_indices=( + 1, + 2, + 3, + ), + style='pytorch', + type='mmdet.ResNet', + with_cp=True), + data_preprocessor=dict( + bgr_to_rgb=True, + mean=[ + 123.675, + 116.28, + 103.53, + ], + pad_size_divisor=32, + std=[ + 58.395, + 57.12, + 57.375, + ], + type='CustomDet3DDataPreprocessor'), + decoder=dict( + anchor_encoder=dict(embed_dims=256, rot_dims=3, type='DoF9BoxEncoder'), + deformable_model=dict( + embed_dims=256, + filter_outlier=True, + kps_generator=dict( + fix_scale=[ + [ + 0, + 0, + 0, + ], + [ + 0.45, + 0, + 0, + ], + [ + -0.45, + 0, + 0, + ], + [ + 0, + 0.45, + 0, + ], + [ + 0, + -0.45, + 0, + ], + [ + 0, + 0, + 0.45, + ], + [ + 0, + 0, + -0.45, + ], + ], + num_learnable_pts=9, + type='SparseBox3DKeyPointsGenerator'), + max_depth=10, + min_depth=0.25, + num_groups=8, + num_levels=4, + type='DeformableFeatureAggregation', + use_camera_embed=True, + use_deformable_func=True, + with_depth=True, + with_value_proj=True), + ffn=dict( + embed_dims=256, + feedforward_channels=2048, + ffn_drop=0.0, + type='FFN'), + graph_model=dict( + batch_first=True, + dropout=0.0, + embed_dims=256, + num_heads=8, + type='MultiheadAttention'), + gt_cls_key='tokens_positive', + gt_reg_key='gt_bboxes_3d', + instance_bank=dict( + anchor='anchor_files/embodiedscan_kmeans_det_cam_log_z-0.2-3.npy', + anchor_in_camera=True, + embed_dims=256, + num_anchor=50, + type='InstanceBank'), + look_forward_twice=True, + loss_cls=dict( + alpha=0.25, + gamma=2.0, + loss_weight=1.0, + type='mmdet.FocalLoss', + use_sigmoid=True), + loss_reg=dict( + loss_weight_cd=0.8, + loss_weight_pcd=0.0, + loss_weight_wd=1.0, + type='DoF9BoxLoss'), + norm_layer=dict(normalized_shape=256, type='LN'), + post_processor=dict(num_output=1000, type='GroundingBox3DPostProcess'), + refine_layer=dict( + cls_bias=True, + embed_dims=256, + output_dim=9, + type='GroundingRefineClsHead'), + sampler=dict( + box_weight=1.0, + cls_weight=1.0, + cost_weight_cd=0.8, + cost_weight_pcd=0.0, + cost_weight_wd=1.0, + embed_dims=256, + num_classes=284, + num_dn=100, + type='Grounding3DTarget', + with_dn_query=True), + text_cross_attn=dict( + batch_first=True, + dropout=0.0, + embed_dims=256, + num_heads=8, + type='MultiheadAttention'), + type='BBox3DDecoder', + with_instance_id=False), + feature_enhancer=dict( + embed_dims=256, + img_attn_block=dict( + ffn_cfg=dict( + embed_dims=256, feedforward_channels=2048, ffn_drop=0.0), + self_attn_cfg=dict( + dropout=0.0, embed_dims=256, im2col_step=64, num_levels=4)), + num_feature_levels=4, + num_layers=6, + positional_encoding=dict( + normalize=True, num_feats=128, offset=0.0, temperature=20), + text_attn_block=dict( + ffn_cfg=dict( + embed_dims=256, feedforward_channels=1024, ffn_drop=0.0), + self_attn_cfg=dict(dropout=0.0, embed_dims=256, num_heads=4)), + text_img_attn_block=dict( + embed_dim=1024, + init_values=0.0001, + l_dim=256, + num_heads=4, + v_dim=256), + type='TextImageDeformable2DEnhancer'), + input_3d='depth_img', + neck=dict( + act_cfg=None, + bias=True, + in_channels=[ + 192, + 384, + 768, + ], + kernel_size=1, + norm_cfg=dict(num_groups=32, type='GN'), + num_outs=4, + out_channels=256, + type='mmdet.ChannelMapper'), + neck_3d=dict( + act_cfg=None, + bias=True, + in_channels=[ + 8, + 16, + 32, + ], + kernel_size=1, + norm_cfg=dict(num_groups=4, type='GN'), + num_outs=4, + out_channels=32, + type='mmdet.ChannelMapper'), + spatial_enhancer=dict( + embed_dims=256, + feature_3d_dim=32, + loss_depth_weight=1.0, + max_depth=10, + min_depth=0.25, + num_depth=64, + num_depth_layers=2, + type='DepthFusionSpatialEnhancer', + with_feature_3d=True), + text_encoder=dict( + add_pooling_layer=False, + max_tokens=768, + name='./ckpt/bert-base-uncased', + pad_to_max=False, + return_tokenized=True, + special_tokens_list=[ + '[CLS]', + '[SEP]', + ], + type='BertModel', + use_checkpoint=True, + use_sub_sentence_represent=True), + type='BIP3D', + use_depth_grid_mask=True) +num_depth = 64 +optim_wrapper = dict( + clip_grad=dict(max_norm=10, norm_type=2), + optimizer=dict(lr=0.0002, type='AdamW', weight_decay=0.0005), + paramwise_cfg=dict( + custom_keys=dict({ + 'absolute_pos_embed': dict(decay_mult=0.0), + 'backbone.': dict(lr_mult=0.1), + 'text_encoder': dict(lr_mult=0.05) + })), + type='OptimWrapper') +param_scheduler = [ + dict( + begin=0, by_epoch=False, end=500, start_factor=0.001, type='LinearLR'), + dict( + begin=0, + by_epoch=False, + end=50000, + gamma=0.1, + milestones=[ + 40000, + 47500, + ], + type='MultiStepLR'), +] +randomness = dict(seed=0) +resize = dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization') +resume = False +rotate_3rscan = True +sep_token = '[SEP]' +tail_labels = [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, +] +test_ann_file = 'embodiedscan/embodiedscan_infos_test.pkl' +test_cfg = dict(type='TestLoop') +test_dataloader = dict( + batch_size=1, + dataset=dict( + ann_file='embodiedscan/embodiedscan_infos_test.pkl', + box_type_3d='Euler-Depth', + data_root='data', + filter_empty_gt=True, + metainfo=dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )), + mode='grounding', + pipeline=[ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=50, + n_images=1, + ordered=True, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + ], + type='MultiViewPipeline'), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + ], + test_mode=True, + type='EmbodiedScanDetGroundingDataset', + vg_file='embodiedscan/embodiedscan_test_vg.json'), + drop_last=False, + num_workers=4, + persistent_workers=False, + sampler=dict(shuffle=False, type='DefaultSampler')) +test_evaluator = dict( + collect_dir='/job_data/.dist_test', + format_only=True, + result_dir='/job_data', + submit_info=dict({ + 'authors': [ + 'xuewu lin', + ], + 'country': 'China', + 'e-mail': '878585984@qq.com', + 'institution': 'Horizon', + 'method': 'BIP3D', + 'team': 'robot-lab manipulation team' + }), + type='GroundingMetric') +test_pipeline = [ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=50, + n_images=1, + ordered=True, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + ], + type='MultiViewPipeline'), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), +] +test_vg_file = 'embodiedscan/embodiedscan_test_vg.json' +train_ann_file = 'embodiedscan/embodiedscan_infos_train.pkl' +train_cfg = dict( + max_iters=50000, type='IterBasedTrainLoop', val_interval=25000) +train_dataloader = dict( + batch_size=1, + dataset=dict( + datasets=[ + dict( + dataset=dict( + ann_file='embodiedscan/embodiedscan_infos_train.pkl', + box_type_3d='Euler-Depth', + data_root='data', + filter_empty_gt=True, + metainfo=dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )), + pipeline=[ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=18, + n_images=1, + ordered=False, + rotate_3rscan=True, + transforms=[ + dict( + backend_args=None, + type='LoadImageFromFile'), + dict( + backend_args=None, + type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + dict( + data_aug_conf=dict( + H=512, + W=512, + bot_pct_lim=( + 0.0, + 0.05, + ), + final_dim=( + 512, + 512, + ), + rand_flip=False, + resize_lim=( + 1.0, + 1.0, + ), + rot_lim=( + 0, + 0, + )), + type='ResizeCropFlipImage'), + ], + type='MultiViewPipeline'), + dict( + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + filter_others=True, + max_class=128, + sep_token='[SEP]', + training=True, + type='CategoryGroundingDataPrepare', + z_range=[ + -0.2, + 3, + ]), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + dict( + max_depth=10, + min_depth=0.25, + num_depth=64, + origin_stride=4, + type='DepthProbLabelGenerator'), + ], + test_mode=False, + type='EmbodiedScanDetGroundingDataset'), + times=20, + type='RepeatDataset'), + dict( + ann_file='embodiedscan/embodiedscan_infos_train.pkl', + box_type_3d='Euler-Depth', + data_root='data', + filter_empty_gt=True, + metainfo=dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )), + mode='grounding', + num_text=10, + pipeline=[ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=18, + n_images=1, + ordered=True, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + dict( + data_aug_conf=dict( + H=512, + W=512, + bot_pct_lim=( + 0.0, + 0.05, + ), + final_dim=( + 512, + 512, + ), + rand_flip=False, + resize_lim=( + 1.0, + 1.0, + ), + rot_lim=( + 0, + 0, + )), + type='ResizeCropFlipImage'), + ], + type='MultiViewPipeline'), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + dict( + max_depth=10, + min_depth=0.25, + num_depth=64, + origin_stride=4, + type='DepthProbLabelGenerator'), + ], + sep_token='[SEP]', + test_mode=False, + type='EmbodiedScanDetGroundingDataset', + vg_file='embodiedscan/embodiedscan_train_vg_all.json'), + ], + type='ConcatDataset'), + num_workers=4, + persistent_workers=False, + sampler=dict(shuffle=True, type='DefaultSampler')) +train_dataset = dict( + ann_file='embodiedscan/embodiedscan_infos_train.pkl', + box_type_3d='Euler-Depth', + data_root='data', + filter_empty_gt=True, + metainfo=dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )), + mode='grounding', + num_text=10, + pipeline=[ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=18, + n_images=1, + ordered=True, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + dict( + data_aug_conf=dict( + H=512, + W=512, + bot_pct_lim=( + 0.0, + 0.05, + ), + final_dim=( + 512, + 512, + ), + rand_flip=False, + resize_lim=( + 1.0, + 1.0, + ), + rot_lim=( + 0, + 0, + )), + type='ResizeCropFlipImage'), + ], + type='MultiViewPipeline'), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + dict( + max_depth=10, + min_depth=0.25, + num_depth=64, + origin_stride=4, + type='DepthProbLabelGenerator'), + ], + sep_token='[SEP]', + test_mode=False, + type='EmbodiedScanDetGroundingDataset', + vg_file='embodiedscan/embodiedscan_train_vg_all.json') +train_pipeline = [ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=18, + n_images=1, + ordered=True, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + dict( + data_aug_conf=dict( + H=512, + W=512, + bot_pct_lim=( + 0.0, + 0.05, + ), + final_dim=( + 512, + 512, + ), + rand_flip=False, + resize_lim=( + 1.0, + 1.0, + ), + rot_lim=( + 0, + 0, + )), + type='ResizeCropFlipImage'), + ], + type='MultiViewPipeline'), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + dict( + max_depth=10, + min_depth=0.25, + num_depth=64, + origin_stride=4, + type='DepthProbLabelGenerator'), +] +train_vg_file = 'embodiedscan/embodiedscan_train_vg_all.json' +trainval = False +val_ann_file = 'embodiedscan/embodiedscan_infos_val.pkl' +val_cfg = dict(type='ValLoop') +val_dataloader = dict( + batch_size=1, + dataset=dict( + ann_file='embodiedscan/embodiedscan_infos_val.pkl', + box_type_3d='Euler-Depth', + data_root='data', + filter_empty_gt=True, + metainfo=dict( + box_type_3d='euler-depth', + classes=( + 'adhesive tape', + 'air conditioner', + 'alarm', + 'album', + 'arch', + 'backpack', + 'bag', + 'balcony', + 'ball', + 'banister', + 'bar', + 'barricade', + 'baseboard', + 'basin', + 'basket', + 'bathtub', + 'beam', + 'beanbag', + 'bed', + 'bench', + 'bicycle', + 'bidet', + 'bin', + 'blackboard', + 'blanket', + 'blinds', + 'board', + 'body loofah', + 'book', + 'boots', + 'bottle', + 'bowl', + 'box', + 'bread', + 'broom', + 'brush', + 'bucket', + 'cabinet', + 'calendar', + 'camera', + 'can', + 'candle', + 'candlestick', + 'cap', + 'car', + 'carpet', + 'cart', + 'case', + 'chair', + 'chandelier', + 'cleanser', + 'clock', + 'clothes', + 'clothes dryer', + 'coat hanger', + 'coffee maker', + 'coil', + 'column', + 'commode', + 'computer', + 'conducting wire', + 'container', + 'control', + 'copier', + 'cosmetics', + 'couch', + 'counter', + 'countertop', + 'crate', + 'crib', + 'cube', + 'cup', + 'curtain', + 'cushion', + 'decoration', + 'desk', + 'detergent', + 'device', + 'dish rack', + 'dishwasher', + 'dispenser', + 'divider', + 'door', + 'door knob', + 'doorframe', + 'doorway', + 'drawer', + 'dress', + 'dresser', + 'drum', + 'duct', + 'dumbbell', + 'dustpan', + 'dvd', + 'eraser', + 'excercise equipment', + 'fan', + 'faucet', + 'fence', + 'file', + 'fire extinguisher', + 'fireplace', + 'flowerpot', + 'flush', + 'folder', + 'food', + 'footstool', + 'frame', + 'fruit', + 'furniture', + 'garage door', + 'garbage', + 'glass', + 'globe', + 'glove', + 'grab bar', + 'grass', + 'guitar', + 'hair dryer', + 'hamper', + 'handle', + 'hanger', + 'hat', + 'headboard', + 'headphones', + 'heater', + 'helmets', + 'holder', + 'hook', + 'humidifier', + 'ironware', + 'jacket', + 'jalousie', + 'jar', + 'kettle', + 'keyboard', + 'kitchen island', + 'kitchenware', + 'knife', + 'label', + 'ladder', + 'lamp', + 'laptop', + 'ledge', + 'letter', + 'light', + 'luggage', + 'machine', + 'magazine', + 'mailbox', + 'map', + 'mask', + 'mat', + 'mattress', + 'menu', + 'microwave', + 'mirror', + 'molding', + 'monitor', + 'mop', + 'mouse', + 'napkins', + 'notebook', + 'ottoman', + 'oven', + 'pack', + 'package', + 'pad', + 'pan', + 'panel', + 'paper', + 'paper cutter', + 'partition', + 'pedestal', + 'pen', + 'person', + 'piano', + 'picture', + 'pillar', + 'pillow', + 'pipe', + 'pitcher', + 'plant', + 'plate', + 'player', + 'plug', + 'plunger', + 'pool', + 'pool table', + 'poster', + 'pot', + 'price tag', + 'printer', + 'projector', + 'purse', + 'rack', + 'radiator', + 'radio', + 'rail', + 'range hood', + 'refrigerator', + 'remote control', + 'ridge', + 'rod', + 'roll', + 'roof', + 'rope', + 'sack', + 'salt', + 'scale', + 'scissors', + 'screen', + 'seasoning', + 'shampoo', + 'sheet', + 'shelf', + 'shirt', + 'shoe', + 'shovel', + 'shower', + 'sign', + 'sink', + 'soap', + 'soap dish', + 'soap dispenser', + 'socket', + 'speaker', + 'sponge', + 'spoon', + 'stairs', + 'stall', + 'stand', + 'stapler', + 'statue', + 'steps', + 'stick', + 'stool', + 'stopcock', + 'stove', + 'structure', + 'sunglasses', + 'support', + 'switch', + 'table', + 'tablet', + 'teapot', + 'telephone', + 'thermostat', + 'tissue', + 'tissue box', + 'toaster', + 'toilet', + 'toilet paper', + 'toiletry', + 'tool', + 'toothbrush', + 'toothpaste', + 'towel', + 'toy', + 'tray', + 'treadmill', + 'trophy', + 'tube', + 'tv', + 'umbrella', + 'urn', + 'utensil', + 'vacuum cleaner', + 'vanity', + 'vase', + 'vent', + 'ventilation', + 'wardrobe', + 'washbasin', + 'washing machine', + 'water cooler', + 'water heater', + 'window', + 'window frame', + 'windowsill', + 'wine', + 'wire', + 'wood', + 'wrap', + ), + classes_split=( + [ + 48, + 177, + 82, + 179, + 37, + 243, + 28, + 277, + 32, + 84, + 215, + 145, + 182, + 170, + 22, + 72, + 30, + 141, + 65, + 257, + 221, + 225, + 52, + 75, + 231, + 158, + 236, + 156, + 47, + 74, + 6, + 18, + 71, + 242, + 217, + 251, + 66, + 263, + 5, + 45, + 14, + 73, + 278, + 198, + 24, + 23, + 196, + 252, + 19, + 135, + 26, + 229, + 183, + 200, + 107, + 272, + 246, + 269, + 125, + 59, + 279, + 15, + 163, + 258, + 57, + 195, + 51, + 88, + 97, + 58, + 102, + 36, + 137, + 31, + 80, + 160, + 155, + 61, + 238, + 96, + 190, + 25, + 219, + 152, + 142, + 201, + 274, + 249, + 178, + 192, + ], + [ + 189, + 164, + 101, + 205, + 273, + 233, + 131, + 180, + 86, + 220, + 67, + 268, + 224, + 270, + 53, + 203, + 237, + 226, + 10, + 133, + 248, + 41, + 55, + 16, + 199, + 134, + 99, + 185, + 2, + 20, + 234, + 194, + 253, + 35, + 174, + 8, + 223, + 13, + 91, + 262, + 230, + 121, + 49, + 63, + 119, + 162, + 79, + 168, + 245, + 267, + 122, + 104, + 100, + 1, + 176, + 280, + 140, + 209, + 259, + 143, + 165, + 147, + 117, + 85, + 105, + 95, + 109, + 207, + 68, + 175, + 106, + 60, + 4, + 46, + 171, + 204, + 111, + 211, + 108, + 120, + 157, + 222, + 17, + 264, + 151, + 98, + 38, + 261, + 123, + 78, + 118, + 127, + 240, + 124, + ], + [ + 76, + 149, + 173, + 250, + 275, + 255, + 34, + 77, + 266, + 283, + 112, + 115, + 186, + 136, + 256, + 40, + 254, + 172, + 9, + 212, + 213, + 181, + 154, + 94, + 191, + 193, + 3, + 130, + 146, + 70, + 128, + 167, + 126, + 81, + 7, + 11, + 148, + 228, + 239, + 247, + 21, + 42, + 89, + 153, + 161, + 244, + 110, + 0, + 29, + 114, + 132, + 159, + 218, + 232, + 260, + 56, + 92, + 116, + 282, + 33, + 113, + 138, + 12, + 188, + 44, + 150, + 197, + 271, + 169, + 206, + 90, + 235, + 103, + 281, + 184, + 208, + 216, + 202, + 214, + 241, + 129, + 210, + 276, + 64, + 27, + 87, + 139, + 227, + 187, + 62, + 43, + 50, + 69, + 93, + 144, + 166, + 265, + 54, + 83, + 39, + ], + )), + mode='grounding', + pipeline=[ + dict(type='LoadAnnotations3D'), + dict( + max_n_images=50, + n_images=1, + ordered=True, + rotate_3rscan=True, + transforms=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(backend_args=None, type='LoadDepthFromFile'), + dict( + dst_intrinsic=[ + [ + 432.57943431339237, + 0.0, + 256, + ], + [ + 0.0, + 539.8570854208559, + 256, + ], + [ + 0.0, + 0.0, + 1.0, + ], + ], + dst_wh=( + 512, + 512, + ), + type='CamIntrisicStandardization'), + ], + type='MultiViewPipeline'), + dict( + keys=[ + 'img', + 'depth_img', + 'gt_bboxes_3d', + 'gt_labels_3d', + ], + type='Pack3DDetInputs'), + ], + test_mode=True, + type='EmbodiedScanDetGroundingDataset', + vg_file='embodiedscan/embodiedscan_val_vg_all.json'), + drop_last=False, + num_workers=4, + persistent_workers=False, + sampler=dict(shuffle=False, type='DefaultSampler')) +val_evaluator = dict( + collect_dir='/job_data/.dist_test', type='GroundingMetric') +val_vg_file = 'embodiedscan/embodiedscan_val_vg_all.json' +vis_backends = [ + dict(save_dir='/job_tboard', type='TensorboardVisBackend'), +] +visualizer = dict( + name='visualizer', + type='Visualizer', + vis_backends=[ + dict(save_dir='/job_tboard', type='TensorboardVisBackend'), + ]) +work_dir = '/job_data/work_dirs' +z_range = [ + -0.2, + 3, +] + +02/23 11:13:33 - mmengine - WARNING - Failed to search registry with scope "bip3d" in the "visualizer" registry tree. As a workaround, the current "visualizer" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "bip3d" is a correct scope, or whether the registry is initialized. +02/23 11:13:33 - mmengine - WARNING - Failed to search registry with scope "bip3d" in the "vis_backend" registry tree. As a workaround, the current "vis_backend" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "bip3d" is a correct scope, or whether the registry is initialized. +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() + return self.fget.__get__(instance, owner)() +02/23 11:13:41 - mmengine - WARNING - Failed to search registry with scope "bip3d" in the "hook" registry tree. As a workaround, the current "hook" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "bip3d" is a correct scope, or whether the registry is initialized. +02/23 11:13:41 - mmengine - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) RuntimeInfoHook +(BELOW_NORMAL) LoggerHook + -------------------- +before_train: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_train_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) EmptyCacheHook + -------------------- +before_train_iter: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook + -------------------- +after_train_iter: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook +(BELOW_NORMAL) LoggerHook +(LOW ) ParamSchedulerHook +(VERY_LOW ) CheckpointHook + -------------------- +after_train_epoch: +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook +(LOW ) ParamSchedulerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_val: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +before_val_epoch: +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook + -------------------- +before_val_iter: +(NORMAL ) IterTimerHook + -------------------- +after_val_iter: +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_val_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook +(BELOW_NORMAL) LoggerHook +(LOW ) ParamSchedulerHook +(VERY_LOW ) CheckpointHook + -------------------- +after_val: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +after_train: +(VERY_HIGH ) RuntimeInfoHook +(VERY_LOW ) CheckpointHook + -------------------- +before_test: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +before_test_epoch: +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook + -------------------- +before_test_iter: +(NORMAL ) IterTimerHook + -------------------- +after_test_iter: +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_test_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(NORMAL ) EmptyCacheHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_test: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +after_run: +(BELOW_NORMAL) LoggerHook + -------------------- +02/23 11:13:44 - mmengine - WARNING - Failed to search registry with scope "bip3d" in the "loop" registry tree. As a workaround, the current "loop" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "bip3d" is a correct scope, or whether the registry is initialized. +02/23 11:13:44 - mmengine - WARNING - euler-depth is not a meta file, simply parsed as meta information + Loading Train dataset: 0%| | 0/3113 [00:00