关于3.9 torch高版本 requirement_for_higher version_torch.txt 当中numpy版本的问题

[dhyuk54]

当我按照您 train的步骤运行了之后 出现了ValueError的问题。
这是我目前的环境 Ubuntu18.04 python3.9
Package Version

---

absl-py 2.1.0
astra-toolbox 2.1.2
Brotli 1.0.9
cachetools 5.5.0
certifi 2024.8.30
charset-normalizer 3.3.2
cycler 0.12.1
future 1.0.0
google-auth 2.35.0
google-auth-oauthlib 0.4.6
grpcio 1.66.1
h5py 3.10.0
idna 3.7
importlib_metadata 8.5.0
joblib 1.4.2
kiwisolver 1.4.7
Markdown 3.7
MarkupSafe 2.1.5
matplotlib 3.1.1
mkl_fft 1.3.10
mkl_random 1.2.7
mkl-service 2.4.0
numpy 2.0.1
oauthlib 3.2.2
odl 1.0.0.dev0
packaging 24.1
pillow 10.4.0
pip 24.2
protobuf 3.19.6
pyasn1 0.6.1
pyasn1_modules 0.4.1
pyparsing 3.1.4
PySocks 1.7.1
python-dateutil 2.9.0.post0
PyYAML 6.0.2
requests 2.32.3
requests-oauthlib 2.0.0
rsa 4.9
scikit-learn 1.4.2
scipy 1.13.1
setuptools 75.1.0
six 1.16.0
tb-nightly 2.11.0a20220906
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorboardX 1.8
threadpoolctl 3.5.0
torch 1.13.1
torchaudio 0.13.1
torchvision 0.14.1
tqdm 4.66.1
typing_extensions 4.11.0
tzdata 2024.1
urllib3 2.1.0
wcwidth 0.2.13
Werkzeug 3.0.2
wheel 0.44.0
yacs 0.1.8
zipp 3.20.2

当我运行 CUDA_VISIBLE_DEVICES=0 python train.py --data_path "deeplesion/train/" --log_dir "logs" --model_dir "pretrained_model/"
之后
:~/InDuDoNet# CUDA_VISIBLE_DEVICES=0 python train.py --data_path "deeplesion/train/" --log_dir "logs" --model_dir "pretrained_model/"
Traceback (most recent call last):
File "/root/InDuDoNet/train.py", line 23, in
from deeplesion.Dataset import MARTrainDataset
File "/root/InDuDoNet/deeplesion/init.py", line 1, in
from .Dataset import MARTrainDataset
File "/root/InDuDoNet/deeplesion/Dataset.py", line 5, in
import h5py
File "/root/miniconda3/envs/my39/lib/python3.9/site-packages/h5py/init.py", line 25, in
from . import _errors
File "h5py/_errors.pyx", line 1, in init h5py._errors
ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject

出现了ValueError 错误 ，想请问 博主您的3.9 torch高版本的 numpy 版本是多少呢？ 其他的lib装的还是没有问题的。
期待您的回复，谢谢

[hongwang01]

当我按照您 train的步骤运行了之后 出现了ValueError的问题。 这是我目前的环境 Ubuntu18.04 python3.9 Package Version

absl-py 2.1.0 astra-toolbox 2.1.2 Brotli 1.0.9 cachetools 5.5.0 certifi 2024.8.30 charset-normalizer 3.3.2 cycler 0.12.1 future 1.0.0 google-auth 2.35.0 google-auth-oauthlib 0.4.6 grpcio 1.66.1 h5py 3.10.0 idna 3.7 importlib_metadata 8.5.0 joblib 1.4.2 kiwisolver 1.4.7 Markdown 3.7 MarkupSafe 2.1.5 matplotlib 3.1.1 mkl_fft 1.3.10 mkl_random 1.2.7 mkl-service 2.4.0 numpy 2.0.1 oauthlib 3.2.2 odl 1.0.0.dev0 packaging 24.1 pillow 10.4.0 pip 24.2 protobuf 3.19.6 pyasn1 0.6.1 pyasn1_modules 0.4.1 pyparsing 3.1.4 PySocks 1.7.1 python-dateutil 2.9.0.post0 PyYAML 6.0.2 requests 2.32.3 requests-oauthlib 2.0.0 rsa 4.9 scikit-learn 1.4.2 scipy 1.13.1 setuptools 75.1.0 six 1.16.0 tb-nightly 2.11.0a20220906 tensorboard-data-server 0.6.1 tensorboard-plugin-wit 1.8.1 tensorboardX 1.8 threadpoolctl 3.5.0 torch 1.13.1 torchaudio 0.13.1 torchvision 0.14.1 tqdm 4.66.1 typing_extensions 4.11.0 tzdata 2024.1 urllib3 2.1.0 wcwidth 0.2.13 Werkzeug 3.0.2 wheel 0.44.0 yacs 0.1.8 zipp 3.20.2

当我运行 CUDA_VISIBLE_DEVICES=0 python train.py --data_path "deeplesion/train/" --log_dir "logs" --model_dir "pretrained_model/" 之后 :~/InDuDoNet# CUDA_VISIBLE_DEVICES=0 python train.py --data_path "deeplesion/train/" --log_dir "logs" --model_dir "pretrained_model/" Traceback (most recent call last): File "/root/InDuDoNet/train.py", line 23, in from deeplesion.Dataset import MARTrainDataset File "/root/InDuDoNet/deeplesion/init.py", line 1, in from .Dataset import MARTrainDataset File "/root/InDuDoNet/deeplesion/Dataset.py", line 5, in import h5py File "/root/miniconda3/envs/my39/lib/python3.9/site-packages/h5py/init.py", line 25, in from . import _errors File "h5py/_errors.pyx", line 1, in init h5py._errors ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject

出现了ValueError 错误 ，想请问 博主您的3.9 torch高版本的 numpy 版本是多少呢？ 其他的lib装的还是没有问题的。 期待您的回复，谢谢

感谢对我们工作关注。 抱歉，numpy==1.26.3，我们已经补充到requirement中，谢谢。

[dhyuk54]

当我按照您 train的步骤运行了之后 出现了ValueError的问题。 这是我目前的环境 Ubuntu18.04 python3.9 Package Version
absl-py 2.1.0 astra-toolbox 2.1.2 Brotli 1.0.9 cachetools 5.5.0 certifi 2024.8.30 charset-normalizer 3.3.2 cycler 0.12.1 future 1.0.0 google-auth 2.35.0 google-auth-oauthlib 0.4.6 grpcio 1.66.1 h5py 3.10.0 idna 3.7 importlib_metadata 8.5.0 joblib 1.4.2 kiwisolver 1.4.7 Markdown 3.7 MarkupSafe 2.1.5 matplotlib 3.1.1 mkl_fft 1.3.10 mkl_random 1.2.7 mkl-service 2.4.0 numpy 2.0.1 oauthlib 3.2.2 odl 1.0.0.dev0 packaging 24.1 pillow 10.4.0 pip 24.2 protobuf 3.19.6 pyasn1 0.6.1 pyasn1_modules 0.4.1 pyparsing 3.1.4 PySocks 1.7.1 python-dateutil 2.9.0.post0 PyYAML 6.0.2 requests 2.32.3 requests-oauthlib 2.0.0 rsa 4.9 scikit-learn 1.4.2 scipy 1.13.1 setuptools 75.1.0 six 1.16.0 tb-nightly 2.11.0a20220906 tensorboard-data-server 0.6.1 tensorboard-plugin-wit 1.8.1 tensorboardX 1.8 threadpoolctl 3.5.0 torch 1.13.1 torchaudio 0.13.1 torchvision 0.14.1 tqdm 4.66.1 typing_extensions 4.11.0 tzdata 2024.1 urllib3 2.1.0 wcwidth 0.2.13 Werkzeug 3.0.2 wheel 0.44.0 yacs 0.1.8 zipp 3.20.2
当我运行 CUDA_VISIBLE_DEVICES=0 python train.py --data_path "deeplesion/train/" --log_dir "logs" --model_dir "pretrained_model/" 之后 :~/InDuDoNet# CUDA_VISIBLE_DEVICES=0 python train.py --data_path "deeplesion/train/" --log_dir "logs" --model_dir "pretrained_model/" Traceback (most recent call last): File "/root/InDuDoNet/train.py", line 23, in from deeplesion.Dataset import MARTrainDataset File "/root/InDuDoNet/deeplesion/init.py", line 1, in from .Dataset import MARTrainDataset File "/root/InDuDoNet/deeplesion/Dataset.py", line 5, in import h5py File "/root/miniconda3/envs/my39/lib/python3.9/site-packages/h5py/init.py", line 25, in from . import _errors File "h5py/_errors.pyx", line 1, in init h5py._errors ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject
出现了ValueError 错误 ，想请问 博主您的3.9 torch高版本的 numpy 版本是多少呢？ 其他的lib装的还是没有问题的。 期待您的回复，谢谢

感谢对我们工作关注。 抱歉，numpy==1.26.3，我们已经补充到requirement中，谢谢。

谢谢您的回复