IVGCVSW-3512 Update NNAPISupport.txt for 19.08
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: Ie222e046f2fe832ad48d4b2279c8815f860f76d5
diff --git a/NnapiSupport.txt b/NnapiSupport.txt
index 6f74097..3310f0e 100644
--- a/NnapiSupport.txt
+++ b/NnapiSupport.txt
@@ -10,7 +10,7 @@
--- Support for Android Neural Networks HAL operations ---
-The following AndroidNN HAL 1.0 and 1.1 operations are currently supported:
+The following AndroidNN HAL 1.0, 1.1 and 1.2 operations are currently supported:
AndroidNN operator Tensor type supported
ADD (FLOAT32,QUANT8_ASYMM)
@@ -28,15 +28,22 @@
LOCAL_RESPONSE_NORMALIZATION (FLOAT32)
LOGISTIC (FLOAT32,QUANT8_ASYMM)
LSTM (FLOAT32)
+MAXIMUM (FLOAT32,QUANT8_ASYMM)
MAX_POOL_2D (FLOAT32,QUANT8_ASYMM)
MEAN (FLOAT32,QUANT8_ASYMM)
+MINIMUM (FLOAT32,QUANT8_ASYMM)
MUL (FLOAT32,QUANT8_ASYMM)
PAD (FLOAT32,QUANT8_ASYMM)
+PAD_V2 (FLOAT32,QUANT8_ASYMM)
+PRELU (FLOAT32,QUANT8_ASYMM)
+QUANTIZE (FLOAT32,QUANT8_ASYMM)
+QUANTIZED_16BIT_LSTM (QUANT8_ASYMM)
RELU (FLOAT32,QUANT8_ASYMM)
RELU1 (FLOAT32,QUANT8_ASYMM)
RELU6 (FLOAT32,QUANT8_ASYMM)
RESHAPE (FLOAT32,QUANT8_ASYMM)
RESIZE_BILINEAR (FLOAT32,QUANT8_ASYMM)
+RESIZE_NEAREST_NEIGHBOR (FLOAT32,QUANT8_ASYMM)
SOFTMAX (FLOAT32,QUANT8_ASYMM)
SPACE_TO_BATCH_ND (FLOAT32,QUANT8_ASYMM)
SPACE_TO_DEPTH_ND (FLOAT32,QUANT8_ASYMM)
@@ -45,19 +52,6 @@
SUB (FLOAT32,QUANT8_ASYMM)
TANH (FLOAT32,QUANT8_ASYMM)
TRANSPOSE (FLOAT32,QUANT8_ASYMM)
-
-The following AndroidNN HAL 1.2 operations are currently supported:
-
-CONV_2D (FLOAT32,QUANT8_ASYMM)
-DEPTHWISE_CONV_2D (FLOAT32,QUANT8_ASYMM)
-MAXIMUM (FLOAT32,QUANT8_ASYMM)
-MINIMUM (FLOAT32,QUANT8_ASYMM)
-PAD_V2 (FLOAT32,QUANT8_ASYMM)
-PRELU (FLOAT32,QUANT8_ASYMM)
-QUANTIZE (FLOAT32,QUANT8_ASYMM)
-QUANTIZED_16BIT_LSTM (QUANT8_ASYMM)
-RESIZE_NEAREST_NEIGHBOR (FLOAT32,QUANT8_ASYMM)
-SOFTMAX (FLOAT32,QUANT8_ASYMM)
TRANSPOSE_CONV_2D (FLOAT32,QUANT8_ASYMM)
--- Unsupported operators ---
@@ -74,7 +68,6 @@
The following AndroidNN HAL 1.2 operations are currently not supported:
CONCATENATION
-LSTM
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.