defset_random_seed(seed: Optional[int] =None, deterministic: bool=False, diff_rank_seed: bool= False) ->int:"""Set random seed. Args: seed (int, optional): Seed to be used. deterministic (bool): Whether to set the deterministic option for CUDNN backend, i.e., set `torch.backends....
set_random_seed_learn FlexibleRunner_learn 本部分内容学习mmengine中的runner目录 runner目录下的方法列表如下: 'BaseLoop', 'load_state_dict', 'get_torchvision_models', 'get_external_models', 'get_mmcls_models', 'get_deprecated_model_names', 'CheckpointLoader', 'load_checkpoint', 'weights_to_cp...
set_interval.md set_random_seed.md speed_up_training.md design examples get_started migration notes tutorials Makefile conf.py cp_origin_docs.sh docutils.conf index.rst make.bat switch_language.md README.md examples mmengine requirements tests .gitignore .owners.yml .pre-commit-config-zh-cn....
Translate "how to set random seed" by @xin-li-67 in https://github.com/open-mmlab/mmengine/pull/930 Fix typo by @zhouzaida in https://github.com/open-mmlab/mmengine/pull/965 Fix typo in hook document by @acdart in https://github.com/open-mmlab/mmengine/pull/980 Fix changelog dat...
numpy_random_seed: 1275144488 GPU 0: NVIDIA GeForce RTX 3080 Ti CUDA_HOME: /home/fazal/anaconda3/envs/mmd NVCC: Cuda compilation tools, release 11.6, V11.6.124 GCC: gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0 PyTorch: 1.13.1 PyTorch compiling details: PyTorch built with: ...
inputs = Image.fromarray(np.random.randint(0, 255, (150, 150, 3)).astype(np.uint8)) outputs = compose_obj(inputs) print(outputs.size()) force_full_init def force_full_init_learn(): """ force_full_init为mmengine定义的一种全初始化的装饰器,被修饰的方法调用时将会首先调用其内部的full...
usually for indoor dataset. - 'Camera': Box in camera coordinates. filter_empty_gt (bool): Whether to filter the data with empty GT. If it's set to be True, the example with empty annotations after data pipeline will be dropped and a random example will be chosen in `__getitem__`....
(AMD64)] 07/03 10:52:49 - mmengine - INFO - CUDA available: True 07/03 10:52:49 - mmengine - INFO - numpy_random_seed: 2147483648 07/03 10:52:49 - mmengine - INFO - GPU 0: NVIDIA GeForce RTX 3060 Laptop GPU 07/03 10:52:49 - mmengine - INFO - CUDA_HOME: C:\Program...
When I run 'python tools\train.py configs\yolox\yolox_x_8xb8-300e_coco.py', it reported the following error,My detection class is one, which I have set in 'mmdet\datasets\coco.py': METAINFO = { 'classes':('pig',), 'palette':[(220,60,20)] } ...
numpy_random_seed: 2147483648 GPU 0,1: NVIDIA GeForce RTX 4090 CUDA_HOME: /usr/local/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 6.5.0-2ubuntu1~18.04) 6.5.0 20181026 PyTorch: 1.9.0+cu111