TensorFlow Lite operators that the Arm NN SDK supports

This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK currently supports.

Fully supported

The Arm NN SDK TensorFlow Lite parser currently supports the following operators:

  • ADD

  • AVERAGE_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE

  • BATCH_TO_SPACE

  • CONCATENATION, Supported Fused Activation: RELU , RELU6 , TANH, NONE

  • CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE

  • DEPTHWISE_CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE

  • FULLY_CONNECTED, Supported Fused Activation: RELU , RELU6 , TANH, NONE

  • LOGISTIC

  • L2_NORMALIZATION

  • MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE

  • MAXIMUM

  • MEAN

  • MINIMUM

  • MUL

  • PACK

  • PAD

  • RELU

  • RELU6

  • RESHAPE

  • RESIZE_BILINEAR

  • SOFTMAX

  • SPACE_TO_BATCH

  • SPLIT

  • SQUEEZE

  • STRIDED_SLICE

  • SUB

  • TANH

  • TRANSPOSE

  • TRANSPOSE_CONV

  • UNPACK

Custom Operator

  • TFLite_Detection_PostProcess

Tested networks

Arm tested these operators with the following TensorFlow Lite neural network:

More machine learning operators will be supported in future releases.