- 1 year ago
Trying to use onnxruntime with GPU. SessionOptionsAppendExecutionProvider_CUDA gives error
If you're trying to use onnxruntime
with GPU and getting an error with SessionOptionsAppendExecutionProvider_CUDA
, here are some steps you can try to resolve the issue:
Make sure CUDA is installed:
onnxruntime
requires CUDA to run on GPU. Make sure you have CUDA installed on your system and that it's compatible with your GPU andonnxruntime
version.Check your system architecture: Make sure that you're using the correct version of
onnxruntime
and CUDA for your system architecture (32-bit or 64-bit).Update
onnxruntime
: Make sure you have the latest version ofonnxruntime
installed. You can check the latest version and upgrade using pip:csspip install --upgrade onnxruntime
Specify the CUDA device ID: If you have multiple GPUs or CUDA devices on your system, you may need to specify which one to use with
onnxruntime
. You can do this using theSessionOptions
object:pythonimport onnxruntime as ort
options = ort.SessionOptions()
options.append_execution_provider_cuda(device_id=0)
# Create the session with the specified options
session = ort.InferenceSession("model.onnx", options)
Replace
device_id=0
with the ID of the CUDA device you want to use.Check your CUDA environment variables: Make sure your CUDA environment variables are set correctly. You can check the CUDA environment variables by running the following commands in a command prompt or terminal:
bashecho %CUDA_HOME%
echo %PATH%
The
CUDA_HOME
variable should point to the directory where CUDA is installed, and thePATH
variable should include thebin
directory of the CUDA installation.
By trying these steps, you may be able to resolve the issue with SessionOptionsAppendExecutionProvider_CUDA
in onnxruntime
and use GPU for inference. If the issue persists, you may need to seek further assistance or consult the onnxruntime
documentation for more information.