Release 18.05
diff --git a/NnapiSupport.txt b/NnapiSupport.txt
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+------ ArmNN for Android NNAPI supported operations ------
+
+This release of ArmNN for Android supports use as a driver for the Android Neural Networks API. It implements the android.hardware.neuralnetworks@1.0 interface.
+
+For more information on the Android Neural Networks API, see https://developer.android.com/ndk/guides/neuralnetworks/index.html
+
+For integration and usage documentation, please see README.md.
+
+--- Support for Android Neural Networks HAL operations ---
+
+The following AndroidNN operations are currently supported.
+
+AndroidNN operator           Tensor type supported
+ADD                          (FLOAT32)
+AVERAGE_POOL_2D              (FLOAT32,QUANT8_ASYMM)
+CONCATENATION                (FLOAT32)
+CONV_2D                      (FLOAT32,QUANT8_ASYMM)
+DEPTHWISE_CONV_2D*           (FLOAT32,QUANT8_ASYMM)
+FLOOR                        (FLOAT32)
+FULLY_CONNECTED              (FLOAT32)
+L2_NORMALIZATION             (FLOAT32)
+L2_POOL_2D                   (FLOAT32)
+LOCAL_RESPONSE_NORMALIZATION (FLOAT32)
+LOGISTIC                     (FLOAT32,QUANT8_ASYMM)
+MAX_POOL_2D                  (FLOAT32,QUANT8_ASYMM)
+MUL                          (FLOAT32)
+RELU                         (FLOAT32,QUANT8_ASYMM)
+RELU1                        (FLOAT32,QUANT8_ASYMM)
+RELU6                        (FLOAT32,QUANT8_ASYMM)
+RESHAPE                      (FLOAT32,QUANT8_ASYMM)
+RESIZE_BILINEAR              (FLOAT32)
+SOFTMAX                      (FLOAT32,QUANT8_ASYMM)
+TANH                         (FLOAT32)
+
+* Depthwise convolution only supports a value of 1 for the depth multiplier. In addition, the QUANT8_ASYMM version only supports 3x3 kernels.
+
+--- Unsupported operators ---
+
+The following AndroidNN operations are currently not supported.
+
+DEPTH_TO_SPACE
+DEQUANTIZE
+EMBEDDING_LOOKUP
+HASHTABLE_LOOKUP
+LSH_PROJECTION
+LSTM
+RNN
+SPACE_TO_DEPTH
+SVDF
+
+Where operations are not supported by the ArmNN Android NN Driver, the driver indicates this to the framework appropriately and the framework implements those operations using a CPU implementation.