Please provide the following information when requesting support.
• Hardware (3080ti)
• Network Type (Detectnet_v2)
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
There is a error when dataset_convert.
!tao detectnet_v2 dataset_convert \
-d $SPECS_DIR/all_train_tfrecords_kitti_trainval.txt \
-o $DATA_DOWNLOAD_DIR/tfrecords/kitti_trainval/kitti_trainval
Converting Tfrecords for kitti trainval dataset
2022-09-13 19:23:02,327 [INFO] root: Registry: ['nvcr.io']
2022-09-13 19:23:02,385 [INFO] tlt.components.instance_handler.local_instance: Running command in container: nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.4-py3
Traceback (most recent call last):
File "/home/user/miniconda3/envs/tao/bin/tao", line 8, in <module>
sys.exit(main())
File "/home/user/miniconda3/envs/tao/lib/python3.7/site-packages/tlt/entrypoint/entrypoint.py", line 115, in main
args[1:]
File "/home/user/miniconda3/envs/tao/lib/python3.7/site-packages/tlt/components/instance_handler/local_instance.py", line 319, in launch_command
docker_handler.run_container(command)
File "/home/user/miniconda3/envs/tao/lib/python3.7/site-packages/tlt/components/docker_handler/docker_handler.py", line 290, in run_container
self.start_container(volumes, env_variables, docker_options)
File "/home/user/miniconda3/envs/tao/lib/python3.7/site-packages/tlt/components/docker_handler/docker_handler.py", line 248, in start_container
docker_args = self.get_docker_option_args(docker_options)
File "/home/user/miniconda3/envs/tao/lib/python3.7/site-packages/tlt/components/docker_handler/docker_handler.py", line 231, in get_docker_option_args
"\nPlease choose one of the following: {}".format(key, VALID_DOCKER_ARGS)
AssertionError: The parameter "entrypoint" mentioned in the config file isn't a valid option.
Please choose one of the following: ['user', 'ports', 'shm_size', 'ulimits', 'privileged', 'network']
My all_train_tfrecords_kitti_trainval.txt is
kitti_config {
root_directory_path: "/workspace/tao-experiments/data/training"
image_dir_name: "image_2"
label_dir_name: "label_2"
image_extension: ".jpg"
partition_mode: "random"
num_partitions: 2
val_split: 20
num_shards: 10
}
image_directory_path: "/workspace/tao-experiments/data/training"