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CUDA support doesnot work #21
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it supports both GPU and CPU. Please ensure tensorflow-gpu compatible with cuda version. |
there is something wrong ! pip install --upgrade tensorflow-gpu==1.15 and the tensorflow official documentation shown : then pip install "modelscope[cv]==1.3.2" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html install log shown and then Loaded runtime CuDNN library: 8.5.0 but source was compiled with: 7.6.4. CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration. so I failed ! I tested tensorflow-gpu python
Python 3.7.16 (default, Jan 17 2023, 22:20:44)
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.test.is_gpu_available()
...
True |
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Hi i have noticied that CUDA is not working? Does DCT-Net suports CUDA calculations?
I had to install first
conda install cudatoolkit=10.1
conda install cudnn
It uses CUDA but with error
2022-12-04 09:31:23.527110: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA RTX A4500, Compute Capability 8.6
2022-12-04 09:31:23.527239: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-12-04 09:31:23.527364: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:0a:00.0 name: NVIDIA RTX A4500 computeCapability: 8.6
coreClock: 1.65GHz coreCount: 56 deviceMemorySize: 19.70GiB deviceMemoryBandwidth: 596.12GiB/s
2022-12-04 09:31:23.527408: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2022-12-04 09:31:23.528422: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10
2022-12-04 09:31:23.529403: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
2022-12-04 09:31:23.529550: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
2022-12-04 09:31:23.530466: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
2022-12-04 09:31:23.530985: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
2022-12-04 09:31:23.532948: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7
2022-12-04 09:31:23.533015: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-12-04 09:31:23.533156: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-12-04 09:31:23.533241: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2022-12-04 09:31:23.533267: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2022-12-04 09:31:23.552689: E tensorflow/core/common_runtime/session.cc:91] Failed to create session: Internal: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid
2022-12-04 09:31:23.552708: E tensorflow/c/c_api.cc:2184] Internal: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid
Traceback (most recent call last):
File "/home/alexandr/miniforge3/envs/dctnet/lib/python3.8/site-packages/modelscope/utils/registry.py", line 211, in build_from_cfg
return obj_cls(**args)
File "/home/alexandr/miniforge3/envs/dctnet/lib/python3.8/site-packages/modelscope/pipelines/cv/image_cartoon_pipeline.py", line 42, in init
self.facer = FaceAna(self.model)
File "/home/alexandr/miniforge3/envs/dctnet/lib/python3.8/site-packages/modelscope/models/cv/cartoon/facelib/facer.py", line 20, in init
self.face_detector = FaceDetector(model_dir)
File "/home/alexandr/miniforge3/envs/dctnet/lib/python3.8/site-packages/modelscope/models/cv/cartoon/facelib/face_detector.py", line 26, in init
self._graph, self._sess = self.init_model(self.model_path)
File "/home/alexandr/miniforge3/envs/dctnet/lib/python3.8/site-packages/modelscope/models/cv/cartoon/facelib/face_detector.py", line 113, in init_model
model = init_pb(pb_path)
File "/home/alexandr/miniforge3/envs/dctnet/lib/python3.8/site-packages/modelscope/models/cv/cartoon/facelib/face_detector.py", line 105, in init_pb
sess = tf.Session(config=config)
File "/home/alexandr/.local/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1586, in init
super(Session, self).init(target, graph, config=config)
File "/home/alexandr/.local/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 701, in init
self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid
During handling of the above exception, another exception occurred:
The text was updated successfully, but these errors were encountered: