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:

• Quantized MobileNet
• Quantized SSD MobileNet
• DeepSpeech v1 converted from TensorFlow model
• DeepSpeaker

More machine learning operators will be supported in future releases.