Author Archives: Robin Dong

Some modifications about SSD-Tensorflow

In the previous article, I introduced a new library for Object Detection. But yesterday, after I added slim.batch_norm() into ‘nets/’ like this:

Although training could still run correctly, the evaluation reported errors:

I wondered why adding some simple batch_norm will make shape incorrect for quite a while. Finally… Read more »

Choosing a Object Detection Framework written by Tensorflow

Recently I need to train a DNN model for object detection task. In the past, I am using the object detection framework from tensorflows’s subject — models. But there are two reasons that I couldn’t use it to do my own project: First, it’s too big. There are more than… Read more »

Finding core-dump file

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In a new server, my program got ‘core dump’. But I haven’t found the core-dump file in the current directory as usual. First I checked the ‘ulimit’ configuration:

Seems ok. The system will generate core-dump file when the program crashed. But where is it? Eventually, I found out the… Read more »

Source code analysis for Autograd

Autograd is a convenient tool to automatically differentiate native Python and Numpy code. Let’s look at an example first:

The result is 3.2 f(x) = sqaure(x) + 1, its derivative is 2*x, so the result is correct. Function grad() actually return a ‘function object’, which is ‘grad_f’. When we… Read more »

Prediction of Red Wine Quality

In Kaggle platform, there is an example dataset about Quality of Red Wine. I wrote some code for it by using scikit-learn and pandas:

The results reported by snippet above:

Looks the most important feature to predict quality of red wine is ‘alcohol’. Intuitively, right?

Use PCA (Principal Component Analysis) to blur color image

I wrote an example of blurring color picture by using PCA from scikit-learn:

But it reports

The correct solution is transforming image to 2 dimensions shape, and inverse transform it after PCA:

It works very well now. Let’s see the original image and blurring image: Original Image… Read more »

Do tf.random_crop() operation on GPU

When I run code like:

it reports:

Looks operation tf.random_crop() doen’t have CUDA kernel implementation. Therefore I need to write it myself. The solution is surprisingly simple: write a function to do random_crop on one image by using tf.random_uniform() and tf.slice(), and then use tf.map_fn() to apply it… Read more »

Regularization loss in ‘slim’ library of Tensorflow

My python code using slim library to train classification model in Tensorflow:

It works fine. However, no matter what value the ‘weight_decay’ is, the training accuracy of the model could reach higher than 90% easily. It seems ‘weight_decay’ just doesn’t work. In order to find out the reason, I… Read more »

Using multi-GPUs for training in distributed environment of Tensorflow

I am trying to write code for training on multi-GPUs. The code is mainly from the example of ‘Distributed Tensorflow‘. I have changed the code slightly for runing on GPU:

But after launch the script below:

it reports:

Seems one MonitoredTrainingSession will occupy all the memory of… Read more »