Edge TPU Model Compiler

Compile your model for the Edge TPU

Compile your TensorFlow Lite model for compatibility with the Edge TPU by uploading your .tflite file below.

Requirements

To create a TensorFlow model that takes full advantage of the Edge TPU at runtime, it must meet the following requirements:

  • Tensor parameters are quantized (8-bit fixed-point numbers). You must use quantization-aware training (post-training quantization is not supported).
  • Tensor sizes are constant at compile-time (no dynamic sizes).
  • Model parameters (such as bias tensors) are constant at compile-time.
  • Tensors are either 1-, 2-, or 3-dimensional. If a tensor has more than 3 dimensions, then only the 3 innermost dimensions may have a size greater than 1.
  • The model uses only the operations supported by the Edge TPU (see the following link).

For more details about creating compatible models, read TensorFlow models on the Edge TPU.


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