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
- DEQUANTIZE
- 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
- QUANTIZE
- RELU
- RELU6
- RESHAPE
- RESIZE_BILINEAR
- RESIZE_NEAREST_NEIGHBOR
- SLICE
- 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.