Rename ArmNN schema file to ArmnnSchema.fbs

This makes the header file change to ArmnnSchema_generated.h,
which is then unambiguous with respect to other generated schema files.

Change-Id: Id7785ed74cced4dcd4d6bcbab81e53c6aeba973c
Signed-off-by: Matthew Bentham <matthew.bentham@arm.com>

1 files changed, 0 insertions, 277 deletions

diff --git a/src/armnnSerializer/Schema.fbs b/src/armnnSerializer/Schema.fbs
deleted file mode 100644
index dc14069798..0000000000
--- a/src/armnnSerializer/Schema.fbs
+++ /dev/null
@@ -1,277 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-namespace armnnSerializer;
-
-file_identifier "ARMN";
-
-file_extension "armnn";
-
-enum ActivationFunction : byte {
-    Sigmoid = 0,
-    TanH = 1,
-    Linear = 2,
-    ReLu = 3,
-    BoundedReLu = 4,
-    SoftReLu = 5,
-    LeakyReLu = 6,
-    Abs = 7,
-    Sqrt = 8,
-    Square = 9
-}
-
-enum DataType : byte {
-    Float16 = 0,
-    Float32 = 1,
-    QuantisedAsymm8 = 2,
-    Signed32 = 3,
-    Boolean = 4
-}
-
-enum DataLayout : byte {
-    NHWC = 0,
-    NCHW = 1
-}
-
-table TensorInfo {
-    dimensions:[uint];
-    dataType:DataType;
-    quantizationScale:float = 1.0;
-    quantizationOffset:int = 0;
-}
-
-struct Connection {
-    sourceLayerIndex:uint;
-    outputSlotIndex:uint;
-}
-
-table ByteData {
-    data:[byte];
-}
-
-table ShortData {
-    data:[short];
-}
-
-table IntData {
-    data:[int];
-}
-
-table LongData {
-    data:[long];
-}
-
-union ConstTensorData { ByteData, ShortData, IntData, LongData }
-
-table ConstTensor {
-    info:TensorInfo;
-    data:ConstTensorData;
-}
-
-table InputSlot {
-    index:uint;
-    connection:Connection;
-}
-
-table OutputSlot {
-    index:uint;
-    tensorInfo:TensorInfo;
-}
-
-enum LayerType : uint {
-    Addition = 0,
-    Input = 1,
-    Multiplication = 2,
-    Output = 3,
-    Pooling2d = 4,
-    Reshape = 5,
-    Softmax = 6,
-    Convolution2d = 7,
-    DepthwiseConvolution2d = 8,
-    Activation = 9,
-    Permute = 10,
-    FullyConnected = 11
-}
-
-// Base layer table to be used as part of other layers
-table LayerBase {
-    index:uint;
-    layerName:string;
-    layerType:LayerType;
-    inputSlots:[InputSlot];
-    outputSlots:[OutputSlot];
-}
-
-table BindableLayerBase {
-    base:LayerBase;
-    layerBindingId:int;
-}
-
-// Table for each layer defined below
-table ActivationLayer {
-    base:LayerBase;
-    descriptor:ActivationDescriptor;
-}
-
-table ActivationDescriptor {
-    function:ActivationFunction = Sigmoid;
-    a:float;
-    b:float;
-}
-
-table AdditionLayer {
-    base:LayerBase;
-}
-
-table Convolution2dLayer {
-    base:LayerBase;
-    descriptor:Convolution2dDescriptor;
-    weights:ConstTensor;
-    biases:ConstTensor;
-}
-
-table Convolution2dDescriptor {
-    padLeft:uint;
-    padRight:uint;
-    padTop:uint;
-    padBottom:uint;
-    strideX:uint;
-    strideY:uint;
-    biasEnabled:bool = false;
-    dataLayout:DataLayout = NCHW;
-}
-
-table FullyConnectedLayer {
-    base:LayerBase;
-    descriptor:FullyConnectedDescriptor;
-    weights:ConstTensor;
-    biases:ConstTensor;
-}
-
-table FullyConnectedDescriptor {
-    biasEnabled:bool = false;
-    transposeWeightsMatrix:bool = false;
-}
-
-table InputLayer {
-    base:BindableLayerBase;
-}
-
-table MultiplicationLayer {
-    base:LayerBase;
-}
-
-table Pooling2dLayer {
-    base:LayerBase;
-    descriptor:Pooling2dDescriptor;
-}
-
-enum PoolingAlgorithm : byte {
-    Max = 0,
-    Average = 1,
-    L2 = 2
-}
-
-enum OutputShapeRounding : byte {
-    Floor = 0,
-    Ceiling = 1
-}
-
-enum PaddingMethod : byte {
-    IgnoreValue = 0,
-    Exclude = 1
-}
-
-table Pooling2dDescriptor {
-    poolType:PoolingAlgorithm;
-    padLeft:uint;
-    padRight:uint;
-    padTop:uint;
-    padBottom:uint;
-    poolWidth:uint;
-    poolHeight:uint;
-    strideX:uint;
-    strideY:uint;
-    outputShapeRounding:OutputShapeRounding;
-    paddingMethod:PaddingMethod;
-    dataLayout:DataLayout;
-}
-
-table SoftmaxLayer {
-    base:LayerBase;
-    descriptor:SoftmaxDescriptor;
-}
-
-table SoftmaxDescriptor {
-    beta:float;
-}
-
-table DepthwiseConvolution2dLayer {
-    base:LayerBase;
-    descriptor:DepthwiseConvolution2dDescriptor;
-    weights:ConstTensor;
-    biases:ConstTensor;
-}
-
-table DepthwiseConvolution2dDescriptor {
-    padLeft:uint;
-    padRight:uint;
-    padTop:uint;
-    padBottom:uint;
-    strideX:uint;
-    strideY:uint;
-    biasEnabled:bool = false;
-    dataLayout:DataLayout = NCHW;
-}
-
-table OutputLayer {
-    base:BindableLayerBase;
-}
-
-table ReshapeLayer {
-    base:LayerBase;
-    descriptor:ReshapeDescriptor;
-}
-
-table ReshapeDescriptor {
-  targetShape:[uint];
-}
-
-table PermuteLayer {
-    base:LayerBase;
-    descriptor:PermuteDescriptor;
-}
-
-table PermuteDescriptor {
-    dimMappings:[uint];
-}
-
-union Layer {
-    ActivationLayer,
-    AdditionLayer,
-    Convolution2dLayer,
-    DepthwiseConvolution2dLayer,
-    FullyConnectedLayer,
-    InputLayer,
-    MultiplicationLayer,
-    OutputLayer,
-    PermuteLayer,
-    Pooling2dLayer,
-    ReshapeLayer,
-    SoftmaxLayer
-}
-
-table AnyLayer {
-    layer:Layer;
-}
-
-// Root type for serialized data is the graph of the network
-table SerializedGraph {
-    layers:[AnyLayer];
-    inputIds:[uint];
-    outputIds:[uint];
-}
-
-root_type SerializedGraph;