CODEWITHSUNDEEP
tensorflowonnxruntime
CDuvert
CDuvert

Reputation: 387

ONNX converted TensorFlow saved model runs on CPU but not on GPU

I converted a tensorflow saved model to ONNX format using tf2onnx :

python3 -m tf2onnx.convert --saved-model saved_model/ --output onnx/model.onnx --opset 11

The conversion worked fine and I can run inference with the ONNX model using CPU.

I installed onnxruntime-gpu to run inference with GPU and encountered an error :

RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Non-zero status code returned while running Relu node. Name:'FirstStageFeatureExtractor/resnet_v1_101/resnet_v1_101/conv1/Relu' Status Message: /onnxruntime_src/onnxruntime/core/providers/cuda/cuda_call.cc:97 bool onnxruntime::CudaCall(ERRTYPE, const char*, const char*, ERRTYPE, const char*) [with ERRTYPE = cudaError; bool THRW = true] /onnxruntime_src/onnxruntime/core/providers/cuda/cuda_call.cc:91 bool onnxruntime::CudaCall(ERRTYPE, const char*, const char*, ERRTYPE, const char*) [with ERRTYPE = cudaError; bool THRW = true] CUDA failure 2: out of memory ; GPU=0 ; hostname=coincoin; expr=cudaMalloc((void**)&p, size); 
Stacktrace:

Stacktrace:

I am the only one using the GPU which is a Titan RTX (24GB of RAM). The model runs fine on GPU using its tensorflow saved model version, with 10GB of the GPU's RAM.

Versions are :

Upvotes: 0

Views: 4195

Answers (1)

zhicheng duan
zhicheng duan

Reputation: 101

according to your information and Versions, maybe two solutions to solve the problem:

    1. the information is out of memory, please check the gpu memory is available yet, if not available, set the gpu memory:

enter image description here

config = tf.ConfigProto()                                                                           
config.gpu_options.visible_device_list = "0"                                                        
config.gpu_options.per_process_gpu_memory_fraction = 0.1                                            
set_session(tf.Session(config=config))

Upvotes: 0

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