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Ning-Ding / Implementation-CVPR2015-CNN-for-ReID

Implementation for CVPR 2015 Paper: "An Improved Deep Learning Architecture for Person Re-Identification".
MIT License
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error in CUHK03 #44

Open seuzxy opened 5 years ago

seuzxy commented 5 years ago

please help me solve this problem： File "main.py", line 460, in validation_steps=1) File "/home/omnisky/anaconda3/envs/zhaoyin_env/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 1509, in fit validation_split=validation_split) File "/home/omnisky/anaconda3/envs/zhaoyin_env/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 953, in _standardize_user_data K.get_session().run(x.initializer) File "/home/omnisky/anaconda3/envs/zhaoyin_env/lib/python3.6/site-packages/tensorflow/python/keras/backend.py", line 461, in get_session _SESSION = session_module.Session(config=config) File "/home/omnisky/anaconda3/envs/zhaoyin_env/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1511, in init super(Session, self).init(target, graph, config=config) File "/home/omnisky/anaconda3/envs/zhaoyin_env/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 634, in init self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts) tensorflow.python.framework.errors_impl.InternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version

bmiftah commented 5 years ago

From the last line, I can see the issue is with cuda version which as can be seen is old version .. make sure you have compatible cuda for your tensor , you may refer to authors setting I saw this :- Test Environment: Ubuntu 18.04 Python 3.6.6 TensorFlow 1.11 Keras 2.1.6-tf CUDA 9.0 cudnn 7.3.1 NVIDIA GTX 1080Ti

seuzxy commented 5 years ago

From the last line, I can see the issue is with cuda version which as can be seen is old version .. make sure you have compatible cuda for your tensor , you may refer to authors setting I saw this :- Test Environment: Ubuntu 18.04 Python 3.6.6 TensorFlow 1.11 Keras 2.1.6-tf CUDA 9.0 cudnn 7.3.1 NVIDIA GTX 1080Ti

but my cuda version is already 9.0