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