Jan 1, 2022
Advent of Code 2021 in pure TensorFlow - day 9
The day 9 challenge can be seen as a computer vision problem. TensorFlow contains some computer vision utilities that we'll use - like the image gradient - but it's not a complete framework for computer vision (like OpenCV). Anyway, the framework offers primitive data types like tf.TensorArray and tf.queue that we can use for implementing a flood-fill algorithm in pure TensorFlow and solve the problem.
Dec 28, 2021
Advent of Code 2021 in pure TensorFlow - day 8
The day 8 challenge is, so far, the most boring challenge faced 😅. Designing a TensorFlow program - hence reasoning in graph mode - would have been too complicated since the solution requires lots of conditional branches. A known AutoGraph limitation forbids variables to be defined in only one branch of a TensorFlow conditional if the variable is used afterward. That's why the solution is in pure TensorFlow eager.
Dec 28, 2021
Advent of Code 2021 in pure TensorFlow - day 7
The day 7 challenge is easily solvable with the help of the TensorFlow ragged tensors. In this article, we'll solve the puzzle while learning what ragged tensors are and how to use them.
Dec 25, 2021
Advent of Code 2021 in pure TensorFlow - day 6
The day 6 challenge has been the first one that obliged me to completely redesign for part 2 the solution I developed for part 1. For this reason, in this article, we'll see two different approaches to the problem. The former will be computationally inefficient but will completely model the problem, hence it will be easy to understand. The latter, instead, will be completely different and it will focus on the puzzle goal instead of the complete modeling.