IVGCVSW-5695 Update supported operators
* Update supported operators for the delegate, parsers,
serializer and deserializer
Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: I33ac99a29d894eec055cd05411014075d78b3168
diff --git a/README.md b/README.md
index d602861..d645bff 100644
--- a/README.md
+++ b/README.md
@@ -36,7 +36,7 @@
Depending on what kind of framework (Tensorflow, Caffe, ONNX) you've been using to create your model there are multiple
software tools available within Arm NN that can serve your needs.
-Generally, there is a **parser** available **for each supported framework**. Each parser allows you to run a models from
+Generally, there is a **parser** available **for each supported framework**. Each parser allows you to run models from
one framework e.g. the TfLite-Parser lets you run TfLite models. You can integrate these parsers into your own
application to load, optimize and execute your model. We also provide **python bindings** for our parsers and the Arm NN core.
We call the result **PyArmNN**. Therefore your application can be conveniently written in either C++ using the "original"
diff --git a/docs/01_01_parsers.dox b/docs/01_01_parsers.dox
index 025858e..ae49303 100644
--- a/docs/01_01_parsers.dox
+++ b/docs/01_01_parsers.dox
@@ -127,8 +127,7 @@
### Partially supported
- Conv
- - The parser only supports 2D convolutions with a dilation rate of [1, 1] and group = 1 or group = #Nb_of_channel (depthwise convolution)
- See the ONNX [Conv documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Conv) for more information.
+ - The parser only supports 2D convolutions with a group = 1 or group = #Nb_of_channel (depthwise convolution)
- BatchNormalization
- The parser does not support training mode. See the ONNX [BatchNormalization documentation](https://github.com/onnx/onnx/blob/master/docs/Operators.md#BatchNormalization) for more information.
- MatMul
@@ -179,13 +178,15 @@
- MAXIMUM
- MEAN
- MINIMUM
-- MU
+- MUL
- NEG
- PACK
- PAD
- QUANTIZE
- RELU
- RELU6
+- REDUCE_MAX
+- REDUCE_MIN
- RESHAPE
- RESIZE_BILINEAR
- RESIZE_NEAREST_NEIGHBOR
@@ -197,6 +198,7 @@
- SQUEEZE
- STRIDED_SLICE
- SUB
+- SUM
- TANH
- TRANSPOSE
- TRANSPOSE_CONV
diff --git a/docs/01_02_deserializer_serializer.dox b/docs/01_02_deserializer_serializer.dox
index 047cb5d..6884b93 100644
--- a/docs/01_02_deserializer_serializer.dox
+++ b/docs/01_02_deserializer_serializer.dox
@@ -59,6 +59,7 @@
- Quantize
- QuantizedLstm
- Rank
+- Reduce
- Reshape
- Resize
- Slice
@@ -143,10 +144,10 @@
- QLstm
- QuantizedLstm
- Rank
+- Reduce
- Reshape
- Resize
- ResizeBilinear
-- Rsqrt
- Slice
- Softmax
- SpaceToBatchNd
@@ -157,6 +158,7 @@
- StridedSlice
- Subtraction
- Switch
+- Transpose
- TransposeConvolution2d
More machine learning layers will be supported in future releases.
diff --git a/docs/01_03_delegate.dox b/docs/01_03_delegate.dox
index 9063f05..f6d8e76 100644
--- a/docs/01_03_delegate.dox
+++ b/docs/01_03_delegate.dox
@@ -82,15 +82,17 @@
- LOCAL_RESPONSE_NORMALIZATION
- LOGICAL_AND
--
+
- LOGICAL_NOT
--
+
- LOGICAL_OR
- LOGISTIC
- LOG_SOFTMAX
+- LSTM
+
- L2_NORMALIZATION
- L2_POOL_2D
@@ -111,8 +113,16 @@
- PAD
+- PRELU
+
- QUANTIZE
+- RANK
+
+- REDUCE_MAX
+
+- REDUCE_MIN
+
- RESHAPE
- RESIZE_BILINEAR
@@ -137,8 +147,12 @@
- SQRT
+- STRIDED_SLICE
+
- SUB
+- SUM
+
- TANH
- TRANSPOSE