From my point of view, ONNX is a model description spec and ONNX model needs Deep Learning framework or backend tool/compiler which supports it to run.
The advantage of ONNX as I know is about portable and exchangeable between DL frameworks.
Here I will use this tutorial to convert TensorFlow's model to ONNX model by myself.
https://github.com/onnx/tutorials/blob/master/tutorials/OnnxTensorflowExport.ipynb
Wednesday, August 8, 2018
Tuesday, July 31, 2018
[Fun] compress and composite dataset to one image file
Tuesday, July 17, 2018
[Confusion Matrix] How to calculate confusion matrix, precision and recall list from scratch
I directly give an example which is with 10 categories, such as CIFAR-10 and MNIST. It explains how to calculate the confusion matrix, precision and recall list from scratch in Python. My data is generated at random. You should replace by yours. Here it goes:
Saturday, July 14, 2018
[Qt5] How to develop Qt5 GUI with TensorFlow C++ library?
Here I give a simple and complete example of how to develop Qt5 GUI with TensorFlow C++ library on Linux platform. Please check out my GitHub's repository as follow:
https://github.com/teyenliu/tf_inference_gui
https://github.com/teyenliu/tf_inference_gui
Monday, July 9, 2018
[TensorFlow] How to implement LMDBDataset in tf.data API?
Thursday, July 5, 2018
[TensorFlow] How to build your C++ program or application with TensorFlow library using CMake
When you want to build your C++ program or application using TensorFlow library or functions, you probably will encounter some header file missed issues or linking problems. Here is the step list that I have verified and it works well.
1. Prepare TensorFlow ( v1.10) and its third party's library
2. Modify .tf_.tf_configure.bazelrc
1. Prepare TensorFlow ( v1.10) and its third party's library
$ git clone --recursive https://github.com/tensorflow/tensorflow
$ cd tensorflow/contrib/makefile
$ ./build_all_linux.sh
2. Modify .tf_.tf_configure.bazelrc
$ cd tensorflow/
$ vim .tf_configure.bazelrc
append this line in the bottom of the file
==>
build --define=grpc_no_ares=true
Wednesday, June 27, 2018
[XLA JIT] How to turn on XLA JIT compilation at multiple GPUs training
Before I discuss this question, let's recall how to turn on XLA JIT compilation and use it in TensorFlow python API.
1. Session
Turning on JIT compilation at the session level will result in all possible operators being greedily compiled into XLA computations. Each XLA computation will be compiled into one or more kernels for the underlying device.
1. Session
Turning on JIT compilation at the session level will result in all possible operators being greedily compiled into XLA computations. Each XLA computation will be compiled into one or more kernels for the underlying device.
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