title: ONNX converted TensorFlow saved model runs on CPU but not on GPU
body: <p>I converted a tensorflow saved model to ONNX format using tf2onnx :</p>
  <pre><code>python3 -m tf2onnx.convert --saved-model saved_model/ --output onnx/model.onnx --opset 11
  </code></pre>
  <p>The conversion worked fine and I can run inference with the ONNX model using CPU.</p>
  <p>I installed <code>onnxruntime-gpu</code> to run inference with GPU and encountered an error :</p>
  <pre><code>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**)&amp;p, size); 
  Stacktrace:
  
  Stacktrace:
  </code></pre>
  <p>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.</p>
  <p>Versions are :</p>
  <ul>
  <li>tensorflow 1.14.0</li>
  <li>CUDA 10.0</li>
  <li>CuDNN 7.6.5</li>
  <li>onnx 1.6.0</li>
  <li>onnxruntime 1.1.0</li>
  <li>tf2onnx 1.9.2</li>
  <li>python 3.6</li>
  <li>Ubuntu 18.04</li>
  </ul>