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:
Tuesday, July 17, 2018
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.
Monday, June 25, 2018
[PCIe] How to read/write PCIe Switch Configuration Space?
Thursday, June 21, 2018
[TensorFlow] How to get CPU configuration flags (such as SSE4.1, SSE4.2, and AVX...) in a bash script for building TensorFlow from source
The AVX and SSE4.2 and others are offered by Intel CPU. (AVX and SSE4.2 are CPU infrastructures for faster matrix computations) Did you wonder what CPU configuration flags (such as SSE4.1, SSE4.2, and AVX...) you should use on your machine when building Tensorflow from source? If so, here is a quick solution for you.
[TensorFlow 記憶體優化實驗] Compare the memory options in Grappler Memory Optimizer
As we know that in Tensorflow, there is an optimization module called "Grappler". It provides many kinds of optimization functionalities, such as: Layout, Memory, ModelPruner, and so on... In this experiment, we can see the effect of some memory options enabled in a simple CNN model using MNIST dataset.
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