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Targeting the IPU from TensorFlow 2
Version: 2.0.0-dc2
  • 1. Introduction
  • 2. Targeting the Poplar XLA device
  • 3. Compiling and pre-compiling executables
  • 4. Support for TensorFlow 2
  • 5. TensorFlow 2 examples
  • 6. Training a model
  • 7. Efficient IPU I/O
  • 8. Example using IPUEstimator
  • 9. Example using IPUPipelineEstimator
  • 10. Distributed training
  • 11. Half-precision floating point and stochastic rounding
  • 12. IPU-optimised operations
  • 13. IPU Outlined Functions
  • 14. Writing custom operations
  • 15. IPU host embeddings
  • 16. Retrieving information about compilation and execution
  • 17. API changes
  • 18. Python API
  • 19. TensorFlow operators supported by the IPU
  • 20. Resources
  • 21. Index
  • 22. Trademarks & copyright
Targeting the IPU from TensorFlow 2

22. Trademarks & copyright

Graphcore® and Poplar® are registered trademarks of Graphcore Ltd.

AI-Float™, Colossus™, Exchange Memory™, Graphcloud™, In-Processor-Memory™, IPU-Core™, IPU-Exchange™, IPU-Fabric™, IPU-Link™, IPU-M2000™, IPU-Machine™, IPU-POD™, IPU-Tile™, PopART™, PopLibs™, PopVision™, PopTorch™, Streaming Memory™ and Virtual-IPU™ are trademarks of Graphcore Ltd.

All other trademarks are the property of their respective owners.

Copyright © 2016-2021 Graphcore Ltd. All rights reserved.

This software is made available under the terms of the Graphcore End User License Agreement (EULA). Please ensure you have read and accept the terms of the license before using the software.

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