python -m tf2onnx.convert --saved-model my_model --output temp.onnx onnx_model = onnx.load_model('temp.onnx') Set an explicit batch size in the ONNX file. Note: By default, TensorFlow does not set an explicit batch size. import onnx BATCH_SIZE = 64 inputs = onnx_model....
_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 2023-04-20 23:40:34.427332: W tensorflow/compiler/tf2...
Since this starter script will also install Docker for you, I thought it would be good to supply a Dockerfile to create an image that will run the same benchmark with the same dataset as above. FROM nvcr.io/nvidia/tensorflow:20.11-tf2-py3 MAINTAINER James Brogan <someone@somewhere.com> #...
python -m tf2onnx.convert --saved-model my_model --output temp.onnx onnx_model = onnx.load_model('temp.onnx') Set an explicit batch size in the ONNX file. Note: By default, TensorFlow does not set an explicit batch size. import onnx BATCH_SIZE = 64 inputs = onnx_model....