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# 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.
The Arm NN SDK TensorFlow Lite parser currently only supports uint8.
## 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
* MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
* MAXIMUM
* MEAN
* MINIMUM
* MUL
* PAD
* RELU
* RELU6
* RESHAPE
* RESIZE_BILINEAR
* SOFTMAX
* SPACE_TO_BATCH
* SQUEEZE
* STRIDED_SLICE
* SUB
## Custom Operator
* TFLite_Detection_PostProcess
## Tested networks
Arm tested these operators with the following TensorFlow Lite neural network:
* [Quantized MobileNet](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224_quant.tgz)
* [Quantized SSD MobileNet](http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_quantized_300x300_coco14_sync_2018_07_18.tar.gz)
More machine learning operators will be supported in future releases.
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