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Porting TensorFlow 2 Models Quick Start
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  • 1. Import the TensorFlow IPU module
  • 2. IPU Config
  • 3. Model
    • 3.1. Single IPU models
      • 3.1.1. Specify IPU strategy
      • 3.1.2. Wrap the model within the IPU strategy scope
    • 3.2. Model parallelism
      • 3.2.1. Sequential model
      • 3.2.2. Functional model
        • Pipelining a model you are writing
        • Pipelining an existing functional model
  • 4. Training process
    • 4.1. Using model.fit
    • 4.2. Customized training loop
      • 4.2.1. Training loops, data sets and feed queues
      • 4.2.2. Accessing outfeed queue results during execution
  • 5. Optimization
    • 5.1. Memory optimization
      • 5.1.1. IPU specific/optimized layers
      • 5.1.2. Reduce available_memory_proportion
      • 5.1.3. Enable Replicated Tensor Sharding
      • 5.1.4. Variable Offloading
      • 5.1.5. Recomputation
    • 5.2. Throughput
      • 5.2.1. Using steps_per_execution
      • 5.2.2. Replication
      • 5.2.3. Increase the gradient accumulation count
  • 6. Trademarks & copyright
Porting TensorFlow 2 Models Quick Start

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6. Trademarks & copyright

Graphcloud®, Graphcore®, Poplar® and PopVision® are registered trademarks of Graphcore Ltd.

Bow™, Bow-2000™, Bow Pod™, Colossus™, In-Processor-Memory™, IPU-Core™, IPU-Exchange™, IPU-Fabric™, IPU-Link™, IPU-M2000™, IPU-Machine™, IPU-POD™, IPU-Tile™, PopART™, PopDist™, PopLibs™, PopRun™, PopTorch™, Streaming Memory™ and Virtual-IPU™ are trademarks of Graphcore Ltd.

All other trademarks are the property of their respective owners.

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