Two-way doors decisions

Working for a tech behemoth corp is significantly different than what I expected joining. There is plenty of corpo bullshit, “vapor-ware” and ass-lickers that simply want to game out the system to climb the ladder. But, obviously, that’s not all it has. Can’t tell how is everywhere, but where I am, I must admit that I’m surrounded mainly by competent people and well-matured ideas.

One of the ideas/approaches that we’re trying to strive to is two-way door decision. It’s a literal analogy to the two-way door which in contrast to one-way door allow going through, and if you don’t like what you see, go back.

It’s obvious, isn’t it? When was the last time you saw one-way doors? Those things typically don’t make much sense so you don’t see them around. Why would you want to go somewhere you don’t know much about and not be able to get back? The concept with doors and action on them — go, check, return — is easy to understand but it can be extended to any activity.

We should strive to make such circumstances where we can make a decision and if we don’t like the outcome we should be able to come back. In down to earth example, this is often what retailers allow us to do; we can buy things and if we don’t like it we can return them. Examples in the software development include using feature flags to allow quickly turn off new futures when they don’t do well or make a rollback mechanism for quickly reverting broken builds to the previous state.

Often “backup plan” comes as a similar concept. To me, the backup is more like a pair of one-way doors. Once you go through the doors it will allow you to run away from that place but where you go don’t have to be exactly the same place from where you came. This is not “worse” but it’s a different concept and in some situations will be better. Maybe consider situations where you know, where you are is a bad situation and you simply want to run away from it.

Shortly:
One-way doors: A -> B
Two-way doors: A -> B ( -> A)
Backup plan: A -> B ( -> C)

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Toggling academia status to halted

There was a significant update on my title. Since the end of November, I am officially a PhD. The relief is immense. Obviously, life goes on and nothing has significantly changed on the outside but I can see that my approach to things lighten up and the approach of “Yes can do” returned. I’m open to new projects and ideas.

Surprisingly enough once just before submitting the final version, I stared (again?) to recognise the greater contribution that the work has and it might have. Given that the Machine Learning community is again gradually incorporating the model-based approaches and go smaller on distance (calculus). Such progress opens up opportunities to apply my work to the broader area of interest.

When will this finish…

For the past few years, my life is on hold. Yes, I go to work and do something there but the majority of the time I’m still spending on PhD. It’s such an existential trap. It’s close to the second year when I’m trying to impress a single person who doesn’t really care. It’s close to four years when I’m trying to improve some idea that I had and thought that it might work because the previous 3 years gave no results.

When I started the PhD I was motivated, interested in everything and shaking from the excitement that I’ll be pushing humanity forward. Now, I just want to do the minimum required. In the hindsight, I’ve wasted my life. Nothing good is coming from this. Hopefully, that is “yet”. December is in or out and, at this stage, I don’t really care.

AWS Polly GUI

Although learning and book knowledge are the best, my personal relationship with reading activity is not the friendliest. Being focused on the text is a huge struggle and I often need to re-read sentences to actually read it. That’s why sometimes I use text-to-speech (TTS) software or service.

Few years ago I discovered an Ivona Text-to-speech software which was far superior to any other TTS solution. It was able to quickly read out loud (and clear) text from my clipboard. Not only it was better than others but also it supported Polish – my language. Even though the default software wasn’t useful for my use cases, i.e. scientific papers have unusual formatting, it wasn’t that difficult to write a wrapper and GUI around the Ivona. Unfortunately, it’s not supported anymore and one cannot download the offline version.

Currently, Ivona is owned by the Amazon and its voices are accessible through the Polly AWS service. It’s a relatively a cheap service but one still has to have an internet connection and it’s not provided with any gui. At least officially.

I’ve written an application to use AWS Polly. It’s a simple graphical interface with some formatting options for the text but it does its job. The AWS Polly GUI is accessible from my GitHub page. It’s running on Python3 with PyQt5.

Features are updated as needed so if something might be helpful to anyone, feel free to contact me or create a ticket issue on the repository. I’m using this for my personal work so I’m not planning on leaving this on a side.

Google wants back my microphone

My “writing” work currently goes somewhere else and have little motivation to write anything here. But, there’s something that only internet can help, whether that’s through actual help or simply transferring my annoyance.

In the past few days/weeks there has been some uproar about Facebook listening to us and later subtly suggesting products about which we talked with others. With these it’s hard to point who is objective, so I’ll paste link to web searches and I’m sure you’ll find some “evidence” – Google, Bing and DuckDuckGO. Let me also suggest Reply All podcast who recently had episode on this mysteriously called Is Facebook Spying on You?. Obviously Facebook denies all of this, but they confirm having lots of information about you whether that’s from you directly or from your friends.

Facebook and I are not in good terms for a long time. It’s more a fun social experiment rather than actual social platform. Since it isn’t on my phone there’s nothing to complain about, but there’s another omnipresent God – Google. Actually I have one of its branded phone with turned on Google Assistant, so it had to be there and had to listen to me.

Long story short, I removed microphone permissions from all Google services. Obviously some weren’t happy with this, but I can’t see how this should affect their usage. Except for Google Assistant or occasional input features, nothing should care, right? No. This is really tough break up as from time to time I’m getting vocal suggestions that are close to being commands. Google calls me to when it’s safe you’ll first need to use your phone’s screen and tap the notification then you can let the Google App access some things on your device. This is especially annoying when I’m listening to podcasts or music.

In the beginning this would go on and on, but now it’s more once a day. I don’t think that it has some “time decreasing” variable build in, so it’s definitely my action. More surprising is that even if I quickly unlock phone there won’t be anything new to give permissions to. Also, it might be only happening when the phone is locked as I haven’t had this happening otherwise.

Free AWS is good. Not awesome, but good.

Amazon with it’s Amazon Web Service (AWS) is pretty cool. It gives you access to remote machine which you don’t have to maintain. Actually you don’t have to do anything other than use it. All machines come in different flavours, but what tastes better than free? Granted that it’s extremely limited, but surely we can squeeze something out of it. Right?

AWS instances, i.e. remote machines, differ in the amount of RAM, disc space, operating system, whether they have GPU access and so on. As you can expect free tier instance is pretty low on all measure values. To be more precise free tier instance is of t2.micro type, which is a general purpose burstable instance with a single CPU, 1 GiB memory and EBS data storage (default 4Gb storage).

What is this good for? Depending on the needs, this might be good for almost anything that doesn’t require whatever these instances are lacking. (Did I help?) Obviously. So it’s not so good for heavy computations, training machine learning models or storing data. First of all, it’s better to use for these some other services like S3, DynamoDB, Lex or general machine learning. However, in case of specific requirements, it’s always better just to rent(?) more powerful instance.

These cheap instances, in my option, are very good for few tasks. The main one is web scrapping. This is tedious task that requires small CPU bandwidth, but constant access to the internet. Moreover, we don’t really want to make many calls in small time period so there needs to be a delay between each download. That’s either because we would like to avoid being detect as a bot, or for simply politeness to the owner of the server (not clogging bandwidth).

Internet is full of examples of scrappers for different type of data. I’m adding my own to the collection with r-u-listening project. The core of the project is to allow for users to find similar music to their input. It is a bit more than recommender, but more on this project probably in the future. The scraper itself is more in two parts, i.e. crawler.py and scraper.py. The database that I’m using is FreeMusicArchive.org, which goes with slogan “It’s not just free music; it’s good music”. I do recommend it and once I have something valuable I’d like to share it with them.

Unfortunately these instances don’t come with big default memory and storage. By default they have only 4 Gb storage, which when downloading mp3 tracks will be enough for about 800 tracks (assuming about 5 Mb per track). Again, as always, it depends on the task, but for machine learning algorithms we go with The more, the merrier.

As mentioned before, free tier instances allow up to 32 Gb. To do so go to EC2 service in your AWS console. In the options tab (left side) find Elastic Block Store (EBS) and select Volumes. Then select your instance and Actions, and Modify Volume. Simple, right? In all honesty, like many things in the AWS.

I’ve been using AWS for a while. Even finished AWS general course, its essentials and 3 day onsite workshop on Architecting on AWS. All is pretty simple and consistent. I like it.

Python Empirical Mode Decomposition on Image

One of the packages I intend long term maintain and support is Python implementation of Empirical Mode Decomposition (EMD) called PyEMD. I will skip introduction of the method as it has been explained in few other posts [1, 2, 3, …]. This blog entry is more about announcement of new feature which also means new version.

PyEMD version 0.2 is out. This means that PyEMD now supports 2D data (image) decomposition. Other visible improvements include documentation and more thorough testing both of code and data cases. Installation instructions are provided on the project’s webpage.

I am more than happy to include other improvements or suggestions. The next big step will be support for 3D and multi dimensional data. Please get in touch if you feel that there is something missing.

Image decomposition is based on the simple extremum definition: a point that is above (max) or below (min) surrounding. Behind the hood this is done using SciPy’s ndim maximum_filter. These are then connected using SmoothBivariateSpline. Stopping criteria can be chosen to be either based on the number of sifting operations or threshold values for mean and standard deviations.

Below is included exemplary decomposition, with the top image being input and the following two are the outputs. Exact formula with which the image was generated is
sin(4\pi \cdot x) \cdot \left( cos(8\pi y + 8\pi x) + 3\right) + \left(5x + 2y - 0.4 \right) y + 2. Python code generating this example is in provided in documentation in Examples/EMD2D.