This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK currently supports.
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
DIV
EXP
FULLY_CONNECTED, Supported Fused Activation: RELU , RELU6 , TANH, NONE
LEAKY_RELU
LOGISTIC
L2_NORMALIZATION
MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
MAXIMUM
MEAN
MINIMUM
MUL
NEG
PACK
PAD
QUANTIZE
RELU
RELU6
RESHAPE
RESIZE_BILINEAR
RESIZE_NEAREST_NEIGHBOR
SLICE
SOFTMAX
SPACE_TO_BATCH
SPLIT
SPLIT_V
SQUEEZE
STRIDED_SLICE
SUB
TANH
TRANSPOSE
TRANSPOSE_CONV
UNPACK
Arm tested these operators with the following TensorFlow Lite neural network:
DeepSpeech v1 converted from TensorFlow model
DeepSpeaker
FSRCNN
EfficientNet-lite
RDN converted from TensorFlow model
Quantized RDN (CpuRef)
Quantized Inception v4 (CpuRef)
Quantized ResNet v2 50 (CpuRef)
Quantized Yolo v3 (CpuRef)
More machine learning operators will be supported in future releases.