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Ryan OShea2bbfaa72020-02-12 16:15:27 +00001/// Copyright (c) 2020 ARM Limited.
Ryan OSheaf3a43232020-02-12 16:15:27 +00002///
3/// SPDX-License-Identifier: MIT
4///
5/// Permission is hereby granted, free of charge, to any person obtaining a copy
6/// of this software and associated documentation files (the "Software"), to deal
7/// in the Software without restriction, including without limitation the rights
8/// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9/// copies of the Software, and to permit persons to whom the Software is
10/// furnished to do so, subject to the following conditions:
11///
12/// The above copyright notice and this permission notice shall be included in all
13/// copies or substantial portions of the Software.
14///
15/// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16/// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17/// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18/// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19/// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20/// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21/// SOFTWARE.
22///
23
24namespace armnn
25{
26/**
27@page serializers The ArmNN Serializer and Deserializer
28@tableofcontents
29
30@section S8_serializer The ArmNN Serializer
31
32The `armnnSerializer` is a library for serializing an Arm NN network to a stream.
33
34## The layers that ArmNN SDK Serializer currently supports.
35
36This reference guide provides a list of layers which can be serialized currently by the Arm NN SDK.
37
38## Fully supported
39
40The Arm NN SDK Serializer currently supports the following layers:
41
42- Activation
43- Addition
44- ArgMinMax
45- BatchToSpaceNd
46- BatchNormalization
47- Comparison
48- Concat
49- Constant
50- Convolution2d
51- DepthToSpace
52- DepthwiseConvolution2d
53- Dequantize
54- DetectionPostProcess
55- Division
56- ElementwiseUnary
57- Floor
58- FullyConnected
59- Gather
60- Input
61- InstanceNormalization
62- L2Normalization
63- LogSoftmax
64- Lstm
65- Maximum
66- Mean
67- Merge
68- Minimum
69- Multiplication
70- Normalization
71- Output
72- Pad
73- Permute
74- Pooling2d
75- Prelu
76- Quantize
77- QuantizedLstm
78- Reshape
79- Resize
80- Slice
81- Softmax
82- SpaceToBatchNd
83- SpaceToDepth
84- Splitter
85- Stack
86- StandIn
87- StridedSlice
88- Subtraction
89- Switch
90- TransposeConvolution2d
91
92More machine learning layers will be supported in future releases.
93
94## Deprecated layers
95
96Some layers have been deprecated and replaced by others layers. In order to maintain backward compatibility, serializations of these deprecated layers will deserialize to the layers that have replaced them, as follows:
97
98- Equal will deserialize as Comparison
99- Merger will deserialize as Concat
100- Greater will deserialize as Comparison
101- ResizeBilinear will deserialize as Resize
102- Abs will deserialize as ElementwiseUnary
103- Rsqrt will deserialize as ElementwiseUnary
104<br/><br/><br/><br/>
105
106@section S9_deserializer The ArmNN Deserializer
107
108The `armnnDeserializer` is a library for loading neural networks defined by Arm NN FlatBuffers files
109into the Arm NN runtime.
110
111## The layers that ArmNN SDK Deserializer currently supports.
112
113This reference guide provides a list of layers which can be deserialized currently by the Arm NN SDK.
114
115## Fully supported
116
117The Arm NN SDK Deserialize parser currently supports the following layers:
118
119- Abs
120- Activation
121- Addition
122- ArgMinMax
123- BatchToSpaceNd
124- BatchNormalization
125- Concat
126- Comparison
127- Constant
128- Convolution2d
129- DepthToSpace
130- DepthwiseConvolution2d
131- Dequantize
132- DetectionPostProcess
133- Division
134- Floor
135- FullyConnected
136- Gather
137- Input
138- InstanceNormalization
139- L2Normalization
140- LogSoftmax
141- Lstm
142- Maximum
143- Mean
144- Merge
145- Minimum
146- Multiplication
147- Normalization
148- Output
149- Pad
150- Permute
151- Pooling2d
152- Prelu
153- Quantize
154- QuantizedLstm
155- Reshape
156- Rsqrt
157- Slice
158- Softmax
159- SpaceToBatchNd
160- SpaceToDepth
161- Splitter
162- Stack
163- StandIn
164- StridedSlice
165- Subtraction
166- Switch
167- TransposeConvolution2d
168- Resize
169
170More machine learning layers will be supported in future releases.
171
172## Deprecated layers
173
174Some layers have been deprecated and replaced by others layers. In order to maintain backward compatibility, serializations of these deprecated layers will deserialize to the layers that have replaced them, as follows:
175
176- Equal will deserialize as Comparison
177- Merger will deserialize as Concat
178- Greater will deserialize as Comparison
179- ResizeBilinear will deserialize as Resize
180
181**/
182}