Building MicroTorch: Indexing and Absolute Value Operations for Tensors

Описание: In this episode of our MicroTorch series, we dive into tensor indexing and absolute value operations for deep learning! We'll implement the "get item" method to enable flexible tensor indexing, handle gradient computations for indexed tensors, and build the "abs" method to compute the absolute value of tensor elements. These operations are crucial for neural network development, ensuring proper forward and backward passes for autograd. Follow along with detailed code examples and tests to see how these methods work in practice.

MicroTorch Series Playlist:
   • Backpropagation: Building a PyTorch-Like L...  

Check the Jupyter Notebook:
https://github.com/nickovchinnikov/da...

Check my step-by-step MicroTorch tutorial:
https://datasanta.net/2025/04/03/micr...

Implement Tensor Indexing with "Get Item" Method
Handle Gradient Computations for Indexed Tensors
Build the "Abs" Method for Absolute Value Operations
Use "Where" for a Clean Abs Implementation

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Timestamps:
00:07 - Introduction to Tensor Indexing
00:15 - Implementing the "Get Item" Method
05:10 - Testing Indexing Operations
06:35 - Building the "Abs" Method
08:31 - Implementing Abs with "Where"

#MicroTorch #DeepLearning #TensorIndexing #AbsoluteValue #AI #Python #MachineLearning #Autograd #Backpropagation