dfdx is a Rust-based deep learning framework providing GPU-accelerated tensor operations with compile-time shape checking. It includes neural network building blocks like Linear, Conv2D, and Transformer layers, along with standard optimizers (SGD, Adam, AdamW, RMSprop). The library uses reverse-mode automatic differentiation for backpropagation and supports CUDA/cuDNN acceleration.