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PyTorch Tutorials Refresh – Behind the Scenes

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Hi, I’m Jessica, a Developer Advocate on the Facebook Open Source team. In this blog, I’ll take you behind the scenes to show you how Facebook supports and sustains our open source products – specifically PyTorch, an open source deep learning library. With every new release version, PyTorch pushes out new features, updates existing ones, and adds documentation and tutorials that cover how to implement these new changes.

On May 5, 2020, PyTorch released improvements to Tutorials homepage with new content and a fresh usability experience out into the world (see the Twitter thread) for the community. We introduced keyword based search tags and a new recipes format (bite-sized, ready-to-deploy examples) and more clearly highlighted helpful resources, which resulted in the fresh homepage style you see today.

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As the framework grows with each release, we’re continuously collaborating with our community to not only create more learning content, but also make learning the content easier.

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What Changed

The tutorials refresh project focused on re-envisioning the learning experience by updating the UX and updating the learning content itself.

Our 3 major goals for the refresh were:

  • Reduce blocks of text and make it easy for users to find important resources (e.g. PyTorch Cheat Sheet, New to PyTorch tutorials)
  • Improve discoverability of relevant tutorials and surface more information for users to know about the available tutorial content
  • Create content that allows users to quickly learn and deploy commonly used code snippets

And we addressed these goals by:

  • Adding callout blocks with direct links to highlight important resource such as the beginner tutorial, the PyTorch Cheat Sheet and new recipes
  • Adding filterable tags to help users easily find relevant tutorials; and formatting the tutorials cards with summaries so users know what to expect without having to click in
  • Creating a new learning format, Recipes, and 15 brand new recipes covering some of the most popular PyTorch topics such as interpretability and quantization as well as basics such as how to load data in PyTorch
  • In summary:
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Goals

Implementation

Reduce blocks of text and make it easy for users to find important resources (e.g. PyTorch Cheat Sheet, New to PyTorch tutorials)

Add callouts with direct links to highlight important resources

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Improve discoverability of relevant tutorials and surface more information for users to know about the available tutorial content

Add filterable tags to help users easily find relevant tutorials. Reformat tutorial cards with summaries so users know what to expect

Create content that allow users to quickly learn and deploy commonly used code snippets

Create a new learning format – Recipes. These are bite-sized, actionable examples of how to use specific Pytorch features, different from our previous full-length tutorials

Why We Made These Changes

Now, what drove these changes? These efforts were driven by feedback from the community; two sources of feedback were the UX research study and direct community interactions:

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  • UX Research study – Earlier in 2020, we conducted a UX research study of our website in collaboration with the Facebook UX Research team to understand how our developer community is using the website and evaluate ways we can improve it to better meet their needs
  • In-person events and online feedback – The team gathered community feedback about existing tutorials to help identify learning gaps.

We used these channels of input to fuel revisioning our learning experience.

Rethinking the Learning Experience

Given the feedback from the UX Research study and the in-person workshop, we went back and rethought the current learning experience.

  • 3 levels
    PyTorch Tutorials Refresh - Behind the Scenes
    • Level 1: API docs. Currently these exist and they contain code snippets that provide an easily understandable (and reproducible) example that allows a user to implement that particular API
    • Level 2: The missing puzzle piece
    • Level 3: Tutorials ideally provide an end-to-end experience that provides users an understanding of how to take data, train a model and deploy it into a production setting using PyTorch. These exist, but needed to be pruned of outdated content and cleaned up to better fit this model
    • Realized we were missing something in between, content that was short, informative, and actionable. That’s how recipes were born. Level 2: Recipes are bite-sized, actionable examples of how to use specific PyTorch features, different from our tutorials

What Was the Process

Just as it took a large team effort, this was more of a marathon as opposed to a sprint. Let’s look at the process:

Timeline of the process:

PyTorch Tutorials Refresh - Behind the Scenes

Overall, the project took about 6 months, not including the UX research and prior feedback collection time. It started off with the kickoff discussion to align on the changes. We assessed the existing tutorials, pruned outdated content and decided on new recipe topics and assigned authors. In the meantime, marketing and documentation engineers collaborated with our web design team on the upcoming UI needs, created mocks to preview with the rest of the team and built out the infrastructure.

For logistics, we created a roadmap and set milestones for the team of authors. We held weekly standup meetings, and the team bounced ideas in chat. The changes were all made in a staging branch in GitHub, which allowed us to create previews of the final build. Next, the build process. Many of the recipe authors were first time content creators, so we held a live onboarding session where we discussed teaching mindset, writing with an active voice, outlining, code standards and requirements; and this was all captured in a new set of content creation documentation.

The bulk of the process was spent in building out the content, copy editing and implementing the UI experience.

With the product out the door, we took some time to perform a team retrospective – asking what went well? What went poorly? What can we do better next time? In addition, we continue to gather ongoing feedback from the community through GitHub issues.

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Moving forward, we are brainstorming and forming a longer-term plan for the PyTorch learning experience as it relates to docs and tutorials.

Ways to Improve

Looking back on ways we could have improved:

  • Timeline – Our timeline ended up taking longer than anticipated because it had been coupled with a previous version release and team members were serving double-duty working on release content, as well as tutorials refresh content. As version release approached, we took a step back and realized we needed more time to put out a more polished product.
  • Testing – In software development, if there is an impending deadline, typically testing is the first thing to get squished; however, more focused testing will always save time in the bigger picture. For us, we would always welcome more time for more CI tests of the tutorial build, as well as beta tests of the user experience. Both of these are ongoing works in progress, as we continue to improve the tutorials experience overall.

What’s Next

So what’s next? We understand that this was just one change in a larger landscape of the overall PyTorch learning experience, but we are excited to keep improving this experience for you, our dedicated PyTorch user.

We would like to hear from you about your experience in the new tutorials. Found a tutorial you loved? Tweet about it and tag us (@PyTorch). Ran into an issue you can help fix? File an issue in https://github.com/pytorch/tutorials. We are excited to continue building the future of machine learning with you!

To learn more about Facebook Open Source, subscribe on YouTube, or follow us on Twitter and Facebook.

Facebook Developers

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Facebook-Meta Earns the ‘Worst Company of 2021’ Title in This Survey

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Facebook has had its share of controversies this year. The company was under more scrutiny after whistleblower Frances Haugen leaked a series of internal documents.

Facebook parent Meta has been named the Worst Company of the Year (2021) by Yahoo Finance respondents. According to the publication, an “open-ended” survey was published on Yahoo Finance on December 4 and 5, where 1,541 respondents participated. Facebook received 8 percent of the write-in vote, but respondents were seemingly mad about the Robinhood trading app as well. Electric truck startup Nikola, which was named last year’s worst company by the same publication also faced respondents ire.

Yahoo Finance notes, “Facebook has had its share of controversies this year.” Starting in January, Meta-owned WhatsApp got caught up in a huge controversy after the messaging app announced a new privacy policy (Terms of Service). WhatsApp said it would collect user information and share it with third-party apps for a better user experience. However, the app gave users no choice but later made modifications to the policy under pressure. Similarly, the company was under more scrutiny after whistleblower and former Facebook employee Frances Haugen leaked a series of internal documents showing the company’s problematic practices. It was revealed that Meta-owned Instagram had a negative impact on teenage girls, but the company did almost nothing to rectify the problem.

Yahoo Finance even highlights, “At the same time, some critics, including conservatives, say Facebook over-policed the platform’s speech and stifled their voices.” Critics also blame Facebook and other social media platforms for not curbing hate speech that led to Capitol Building riots.

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However, around 30 percent of Yahoo Finance readers said that Facebook or Meta could redeem itself. One respondent suggested that the company could issue a formal apology for negligence and donate a sizable amount of its profits to a foundation to help reverse its harm.

On the other hand, respondents chose Microsoft as the Company of the Year (2021). The Satya Nadella-led company touched the trillion-mark this year and introduced notable upgrades. The most notable is the Windows 11 OS update that succeeds Windows 10.

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Facebook pays 1.7 Cr fine to Russia after failing to delete content Moscow deems illegal

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In the latest legal tussle with Russia over controversial social media regulation laws, Facebook paid 17 million roubles (Rs 1.7 Crore) for failing to remove content deemed illegal by Moscow. With a threat of potential larger fines looming, Facebook parent company Meta, owned by Mark Zuckerberg, is scheduled to face court next week over repeated violations of Russian legislation on content, Interfax News Agency reported. As per the latest updates, the social media giant could be fined a percentage of its annual revenue.

In October, Moscow sent state bailiffs to enforce the collection of 17 million roubles. Meanwhile, as per Interfax report citing a federal bailiffs’ database, on Sunday, there were more enforcement proceedings against the company. Apart from the popular social media app, Telegram has also paid 15 million roubles in fines for failing to comply with the Russian social media legislations that came into force in 2016.

Facebook pays $53k to Russia for refusing controversial social media laws

It is pertinent to mention that Facebook has locked horns with Moscow earlier in November, resulting in it paying 4 million roubles ($53,000) over its refusal to adhere to Russian data localisation laws, the Moscow Times reported. The Moscow court on November 25 had said that Facebook paid the fine levied in February, following which all proceedings against the US-based social media giant. The payment comes against the litigation filed against the company in 2018, alongside Twitter. The tech companies were also forced to pay an additional 3000 rubles ($40) for failing to comply with user data sharing rules as per the law. The Russian authorities have also previously blocked LinkedIn, owned by Microsoft, for failing to abide by the laws.

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Russian social media laws

As per Moscow Times, under the Russian social media regulation laws, all foreign technology companies are required to store data related to Russian customers and users on servers located in Russia. Additionally, the Russian tech companies will also have to share encryption data with the federal authorities as well as record user calls, messages and civil society group conversation records. The apparatus is said to be a severe breach of privacy rights and unfettered back-door access to personal data that could be used to harass Kremlin critics.

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Facebook Messenger Is Launching a Split Payments Feature for Users to Quickly Share Expenses

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Facebook Messenger Is Launching a Split Payments Feature for Users to Quickly Share Expenses

Meta has announced the arrival of a new Split Payments feature in Facebook Messenger. This feature, as the name suggests, will let you calculate and split expenses with others right from Facebook Messenger. This feature essentially looks to bring an easier method to share the cost of bills and expenses — for example, splitting a dinner bill with friends. Using this new Split Payment feature, Facebook Messenger users will be able to split bills evenly or modify the contribution for each individual, including their own.

The company took to its blog post to announce the new Split Payment feature in Facebook Messenger. 9to5Mac reports that this new bill splitting feature is still in beta and will be exclusive to US users at first. The rollout will begin early next week. As mentioned, it will help users share the cost of bills, expenses, and payments. This feature is especially useful for those who share an apartment and need to split the monthly rent and other expenses with their mates. It could also come handy at a group dinner with many people.

With Split Payments, users can add the number of people the expense needs to be divided with and, by default, the amount entered will be divided in equal parts. A user can also modify each person’s contribution including their own. To use Split Payments, click the Get Started button in a group chat or the Payments Hub in Messenger. Users can modify the contribution in the Split Payments option and send a notification to all the users who need to make payments. After entering a personalised message and confirming your Facebook Pay details, the request will be sent and viewable in the group chat thread.

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Once someone has made the payment, you can mark their transaction as ‘completed’. The Split Payment feature will automatically take into account your share as well and calculate the amount owed accordingly.


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Tasneem Akolawala is a Senior Reporter for Gadgets 360. Her reporting expertise encompasses smartphones, wearables, apps, social media, and the overall tech industry. She reports out of Mumbai, and also writes about the ups and downs in the Indian telecom sector. Tasneem can be reached on Twitter at @MuteRiot, and leads, tips, and releases can be sent to tasneema@ndtv.com.

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