PyTorch - Fast Differentiable Dynamic Graphs in Python

PyTorch - Fast Differentiable Dynamic Graphs in Python

Strange Loop Conference via YouTube Direct link

Seamless GPU Tensors

10 of 18

10 of 18

Seamless GPU Tensors

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PyTorch - Fast Differentiable Dynamic Graphs in Python

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  1. 1 Intro
  2. 2 Overview of the talk
  3. 3 Machine Translation
  4. 4 Adversarial Networks
  5. 5 Adversarial Nets
  6. 6 Chained Together
  7. 7 Trained with Gradient Descent
  8. 8 Computation Graph Toolkits Declarative Toolkits
  9. 9 Imperative Toolkits
  10. 10 Seamless GPU Tensors
  11. 11 Neural Networks
  12. 12 Python is slow
  13. 13 Types of typical operators
  14. 14 Add - Mul A simple use-case
  15. 15 High-end GPUs have faster memory
  16. 16 GPUs like parallelizable problems
  17. 17 Compilation benefits
  18. 18 Tracing JIT

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