Category Archives: machine learning

Some tips about using Keras

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1. How to use part of a model

The ‘img_embed’ model is part of ‘branch_model’. We should realise that ‘Model()’ is a heavy cpu-cost function so it need to be create only once and then could be used many times. 2. How to save a model when using ‘multi_gpu_model’… Read more »

LinearSVC versus SVC in scikit-learn

In competition ‘Quora Insincere Questions Classification’, I want to use simple TF-IDF statistics as a baseline.

The result is not bad:

But after I change LinearSVC to SVC(kernel=’linear’), the program couldn’t work out any result even after 12 hours! Am I doing anything wrong? In the page of… Read more »

Some errors in dataset pipeline of Tensorflow

To extend image datasets by using mixup,I use this snippet to mix two images:

But after generating images by using this snippet, the training report errors:

The size of each image is 512x512x4 = 1048576 bytes. But I can’t understand why there is image has the size of… Read more »

Compare implementation of tf.AdamOptimizer to its paper

When I reviewed the implementation of Adam optimizer in tensorflow yesterday, I noticed that it’s code is different from the formulas that I saw in Adam’s paper. In tensorflow’s formulas for Adam are: But the algorithm in the paper is: Then quickly I found these words in the document of… Read more »

The bug about using hooks and MirroredStrategy in tf.estimator.Estimator

When I was using MirroedStrategy in my tf.estimator.Estimator:

and add hooks for training:

The tensorflow report errors:

Without finding any answers on google, I have to look into the code of ‘estimator.py’ in tensorflow. Fortunately, the code defect is obvious:

class Estimator havn’t any private argument… Read more »

Some lessons from Kaggle’s competition

About two months ago, I joined the competition of ‘RSNA Pneumonia Detection’ in Kaggle. It’s ended yesterday, but I still have many experiences and lessons to be rethinking. 1. Augmentation is extremely crucial. After using tf.image.sample_distorted_bounding_box() in my program, the mAP(mean Average Precision) of evaluating dataset thrived to a perfect… Read more »

How Tensorflow set device for each Operation ?

In Tensorflow, we only need to use snippet below to assign a device to a Operation:

How dose it implement? Let’s take a look. There is a mechanism called ‘context manager’ in Python. For example, we can use it to add a wrapper for a few codes:

The… Read more »

Some tips about using google’s TPU (Cont.)

Sometimes I get this error from TPUEstimator:

And after stop and restart TPU in console of GCP, the error disappeared. TPU doesn’t allow users to use it directly like GPU. You can’t see the device in VM looks like ‘/dev/tpu’ or something like this. Google provides TPU as RPC… Read more »

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/ssd_vgg_512.py’ 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 »