the official pytorch implementation of “Mamba-YOLO:SSMs-based for Object Detection”
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Invalid CUDA 'device=0,1,2,3,4,5,6,7' requested. Use 'device=cpu' or pass valid CUDA device(s) if available, i.e. 'device=0' or 'device=0,1,2,3' for Multi-GPU. #31
based projA module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.0 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
Traceback (most recent call last): File "/data/dyz/Mamba-YOLO-main/mbyolo_train.py", line 1, in
from ultralytics import YOLO
File "/data/dyz/Mamba-YOLO-main/ultralytics/init.py", line 10, in
from ultralytics.data.explorer.explorer import Explorer
File "/data/dyz/Mamba-YOLO-main/ultralytics/data/init.py", line 3, in
from .base import BaseDataset
File "/data/dyz/Mamba-YOLO-main/ultralytics/data/base.py", line 15, in
from torch.utils.data import Dataset
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/init.py", line 1382, in
from .functional import # noqa: F403
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/functional.py", line 7, in
import torch.nn.functional as F
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/init.py", line 1, in
from .modules import # noqa: F403
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/modules/init.py", line 35, in
from .transformer import TransformerEncoder, TransformerDecoder, \
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/modules/transformer.py", line 20, in
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
WARNING ⚠️ no model scale passed. Assuming scale='L'.
Ultralytics YOLOv8.2.29 🚀 Python-3.11.9 torch-2.1.0+cu121
Traceback (most recent call last):
File "/data/dyz/Mamba-YOLO-main/mbyolo_train.py", line 44, in
"train": YOLO(model_conf).train(**args),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/dyz/Mamba-YOLO-main/ultralytics/engine/model.py", line 655, in train
self.trainer = (trainer or self._smart_load("trainer"))(overrides=args, _callbacks=self.callbacks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/dyz/Mamba-YOLO-main/ultralytics/engine/trainer.py", line 101, in init
self.device = select_device(self.args.device, self.args.batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/dyz/Mamba-YOLO-main/ultralytics/utils/torch_utils.py", line 136, in select_device
raise ValueError(
ValueError: Invalid CUDA 'device=0,1,2,3,4,5,6,7' requested. Use 'device=cpu' or pass valid CUDA device(s) if available, i.e. 'device=0' or 'device=0,1,2,3' for Multi-GPU.
based projA module that was compiled using NumPy 1.x cannot be run in NumPy 2.0.0 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2.
Traceback (most recent call last): File "/data/dyz/Mamba-YOLO-main/mbyolo_train.py", line 1, in
from ultralytics import YOLO
File "/data/dyz/Mamba-YOLO-main/ultralytics/init.py", line 10, in
from ultralytics.data.explorer.explorer import Explorer
File "/data/dyz/Mamba-YOLO-main/ultralytics/data/init.py", line 3, in
from .base import BaseDataset
File "/data/dyz/Mamba-YOLO-main/ultralytics/data/base.py", line 15, in
from torch.utils.data import Dataset
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/init.py", line 1382, in
from .functional import # noqa: F403
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/functional.py", line 7, in
import torch.nn.functional as F
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/init.py", line 1, in
from .modules import # noqa: F403
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/modules/init.py", line 35, in
from .transformer import TransformerEncoder, TransformerDecoder, \
File "/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/modules/transformer.py", line 20, in
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
/home/anaconda3/envs/mambayoloD/lib/python3.11/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
WARNING ⚠️ no model scale passed. Assuming scale='L'.
Ultralytics YOLOv8.2.29 🚀 Python-3.11.9 torch-2.1.0+cu121
Traceback (most recent call last):
File "/data/dyz/Mamba-YOLO-main/mbyolo_train.py", line 44, in
"train": YOLO(model_conf).train(**args),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/dyz/Mamba-YOLO-main/ultralytics/engine/model.py", line 655, in train
self.trainer = (trainer or self._smart_load("trainer"))(overrides=args, _callbacks=self.callbacks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/dyz/Mamba-YOLO-main/ultralytics/engine/trainer.py", line 101, in init
self.device = select_device(self.args.device, self.args.batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/dyz/Mamba-YOLO-main/ultralytics/utils/torch_utils.py", line 136, in select_device
raise ValueError(
ValueError: Invalid CUDA 'device=0,1,2,3,4,5,6,7' requested. Use 'device=cpu' or pass valid CUDA device(s) if available, i.e. 'device=0' or 'device=0,1,2,3' for Multi-GPU.
torch.cuda.is_available(): True torch.cuda.device_count(): 4 os.environ['CUDA_VISIBLE_DEVICES']: None ects