Preventing accidental struct copies in Go
Prevent dangerous struct copies with noCopy sentinel and go vet's copylock checker. Protect mutexes and sync primitives from value copies.
Prevent dangerous struct copies with noCopy sentinel and go vet's copylock checker. Protect mutexes and sync primitives from value copies.
In transformer models, the attention block is typically followed by a feed forward layer (FF), which is a simple fully-connected NN with a hidden layer and nonlinearity. Here's the code for such a block that uses ReLU: def feed_forward_relu(x, W1, W2): """Feed-...
Quick takeaways Focus on applying what you learn - reading books or watching videos isn’t enough without practice Build real projects that challenge you - trivial examples don’t expose you to the hidden complexities you’ll face in actual work Expect and embrace...
#550 — April 16, 2025 Unsub | Web Version 🥚 We're taking a little break for Easter but didn't want to take the entire week off, so we have a slimline issue for you today :-) Back to full speed next Wednesday!__Peter Cooper, your editor...
This blogpost is the second installment in a three-part series exploring the mechanics and semantics of the Go scheduler. Despite being published in 2018, the content remains relevant today, as the Go scheduler’s design continues to influence the development of efficient a...
Go 1.24 added a new tool directive that makes it easier to manage your project’s tooling. I used to rely on Make targets to install and run tools like stringer, mockgen, and linters like gofumpt, goimports, staticcheck, and errcheck. Problem is, these installations were glo...
Go 1.24 added a new tool directive that makes it easier to manage your project’s tooling. I used to rely on Make targets to install and run tools like stringer, mockgen, and linters like gofumpt, goimports, staticcheck, and errcheck. Problem is, these installations were glo...
Pin tool versions in Go 1.24 with the new 'tool' directive. Replace tools.go pattern with native go.mod support for project tooling.
Cross-entropy is widely used in modern ML to compute the loss for classification tasks. This post is a brief overview of the math behind it and a related concept called Kullback-Leibler (KL) divergence. Information content of a single random event We'll start with a single event...