What is PyTorch leaf node? | B. Nikolic Software and Computing Blog
Understanding what a PyTorch leaf node is intuitive when you remember that PyTorch automatic differentiation is in the backward direction compared to the way the program is executed to compute its value – i.e., it is a backward-mode automatic differentiation.
Understanding what a PyTorch leaf node is intuitive when you remember that PyTorch automatic differentiation is in the backward direction compared to the way the program is executed to compute its value – i.e., it is a backward-mode automatic differentiation. Below are a couple of slides I’ve used before to illustrate backward mode autodiff: In PyTorch leaf nodes are therefore the values from which the computation begins . Here a simple program illustrating this: # The following two values are the leaf nodes x = T . ones ( 10 , requires_grad = True ) y = T . ones ( 10 , requires_grad = True )
Explore this link on the map →related reading
- PyTorch internals : ezyang's blogblog.ezyang.com
- Calculus on Computational Graphs: Backpropagation -- colah's blogcolah.github.io
- Circuit Tracing: Revealing Computational Graphs in Language Modelstransformer-circuits.pub
- Learning PyTorch with Examples — PyTorch Tutorials 2.12.0+cu130 documentationpytorch.org
- Tiny TPUtinytpu.com
- UW PLSE | How does torch.compile work?uwplse.org
- Redirecting…pytorch.org
- Differentiable Programming from Scratchthenumb.at
- Neuronpedianeuronpedia.org
- microgptkarpathy.github.io
- PiTorch: ML on Baremetal Raspberry Pis | projectsmasonjwang.com
- the bug that taught me more about PyTorch than years of using it | Elana Simonelanapearl.github.io