STT-tensorflow/tensorflow/lite/builtin_ops.h
Thai Nguyen ac8f6785d3 Add Conv3D reference kernel to TFLite
This kernel currently only supports float type and has filter with the same data format as TensorFlow Conv3D op.
The conversion change will be added in a follow-up cl.

PiperOrigin-RevId: 351726918
Change-Id: Id2cc805cb89a1da1fda656a2260516eda8bd9119
2021-01-13 21:36:14 -08:00

169 lines
5.3 KiB
C

/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_LITE_BUILTIN_OPS_H_
#define TENSORFLOW_LITE_BUILTIN_OPS_H_
// DO NOT EDIT MANUALLY: This file is automatically generated by
// `schema/builtin_ops_header/generator.cc`.
#ifdef __cplusplus
extern "C" {
#endif // __cplusplus
// The enum for builtin operators.
// Note: CUSTOM, DELEGATE, and PLACEHOLDER_FOR_GREATER_OP_CODES are 3 special
// ops which are not real built-in ops.
typedef enum {
kTfLiteBuiltinAdd = 0,
kTfLiteBuiltinAveragePool2d = 1,
kTfLiteBuiltinConcatenation = 2,
kTfLiteBuiltinConv2d = 3,
kTfLiteBuiltinDepthwiseConv2d = 4,
kTfLiteBuiltinDepthToSpace = 5,
kTfLiteBuiltinDequantize = 6,
kTfLiteBuiltinEmbeddingLookup = 7,
kTfLiteBuiltinFloor = 8,
kTfLiteBuiltinFullyConnected = 9,
kTfLiteBuiltinHashtableLookup = 10,
kTfLiteBuiltinL2Normalization = 11,
kTfLiteBuiltinL2Pool2d = 12,
kTfLiteBuiltinLocalResponseNormalization = 13,
kTfLiteBuiltinLogistic = 14,
kTfLiteBuiltinLshProjection = 15,
kTfLiteBuiltinLstm = 16,
kTfLiteBuiltinMaxPool2d = 17,
kTfLiteBuiltinMul = 18,
kTfLiteBuiltinRelu = 19,
kTfLiteBuiltinReluN1To1 = 20,
kTfLiteBuiltinRelu6 = 21,
kTfLiteBuiltinReshape = 22,
kTfLiteBuiltinResizeBilinear = 23,
kTfLiteBuiltinRnn = 24,
kTfLiteBuiltinSoftmax = 25,
kTfLiteBuiltinSpaceToDepth = 26,
kTfLiteBuiltinSvdf = 27,
kTfLiteBuiltinTanh = 28,
kTfLiteBuiltinConcatEmbeddings = 29,
kTfLiteBuiltinSkipGram = 30,
kTfLiteBuiltinCall = 31,
kTfLiteBuiltinCustom = 32,
kTfLiteBuiltinEmbeddingLookupSparse = 33,
kTfLiteBuiltinPad = 34,
kTfLiteBuiltinUnidirectionalSequenceRnn = 35,
kTfLiteBuiltinGather = 36,
kTfLiteBuiltinBatchToSpaceNd = 37,
kTfLiteBuiltinSpaceToBatchNd = 38,
kTfLiteBuiltinTranspose = 39,
kTfLiteBuiltinMean = 40,
kTfLiteBuiltinSub = 41,
kTfLiteBuiltinDiv = 42,
kTfLiteBuiltinSqueeze = 43,
kTfLiteBuiltinUnidirectionalSequenceLstm = 44,
kTfLiteBuiltinStridedSlice = 45,
kTfLiteBuiltinBidirectionalSequenceRnn = 46,
kTfLiteBuiltinExp = 47,
kTfLiteBuiltinTopkV2 = 48,
kTfLiteBuiltinSplit = 49,
kTfLiteBuiltinLogSoftmax = 50,
kTfLiteBuiltinDelegate = 51,
kTfLiteBuiltinBidirectionalSequenceLstm = 52,
kTfLiteBuiltinCast = 53,
kTfLiteBuiltinPrelu = 54,
kTfLiteBuiltinMaximum = 55,
kTfLiteBuiltinArgMax = 56,
kTfLiteBuiltinMinimum = 57,
kTfLiteBuiltinLess = 58,
kTfLiteBuiltinNeg = 59,
kTfLiteBuiltinPadv2 = 60,
kTfLiteBuiltinGreater = 61,
kTfLiteBuiltinGreaterEqual = 62,
kTfLiteBuiltinLessEqual = 63,
kTfLiteBuiltinSelect = 64,
kTfLiteBuiltinSlice = 65,
kTfLiteBuiltinSin = 66,
kTfLiteBuiltinTransposeConv = 67,
kTfLiteBuiltinSparseToDense = 68,
kTfLiteBuiltinTile = 69,
kTfLiteBuiltinExpandDims = 70,
kTfLiteBuiltinEqual = 71,
kTfLiteBuiltinNotEqual = 72,
kTfLiteBuiltinLog = 73,
kTfLiteBuiltinSum = 74,
kTfLiteBuiltinSqrt = 75,
kTfLiteBuiltinRsqrt = 76,
kTfLiteBuiltinShape = 77,
kTfLiteBuiltinPow = 78,
kTfLiteBuiltinArgMin = 79,
kTfLiteBuiltinFakeQuant = 80,
kTfLiteBuiltinReduceProd = 81,
kTfLiteBuiltinReduceMax = 82,
kTfLiteBuiltinPack = 83,
kTfLiteBuiltinLogicalOr = 84,
kTfLiteBuiltinOneHot = 85,
kTfLiteBuiltinLogicalAnd = 86,
kTfLiteBuiltinLogicalNot = 87,
kTfLiteBuiltinUnpack = 88,
kTfLiteBuiltinReduceMin = 89,
kTfLiteBuiltinFloorDiv = 90,
kTfLiteBuiltinReduceAny = 91,
kTfLiteBuiltinSquare = 92,
kTfLiteBuiltinZerosLike = 93,
kTfLiteBuiltinFill = 94,
kTfLiteBuiltinFloorMod = 95,
kTfLiteBuiltinRange = 96,
kTfLiteBuiltinResizeNearestNeighbor = 97,
kTfLiteBuiltinLeakyRelu = 98,
kTfLiteBuiltinSquaredDifference = 99,
kTfLiteBuiltinMirrorPad = 100,
kTfLiteBuiltinAbs = 101,
kTfLiteBuiltinSplitV = 102,
kTfLiteBuiltinUnique = 103,
kTfLiteBuiltinCeil = 104,
kTfLiteBuiltinReverseV2 = 105,
kTfLiteBuiltinAddN = 106,
kTfLiteBuiltinGatherNd = 107,
kTfLiteBuiltinCos = 108,
kTfLiteBuiltinWhere = 109,
kTfLiteBuiltinRank = 110,
kTfLiteBuiltinElu = 111,
kTfLiteBuiltinReverseSequence = 112,
kTfLiteBuiltinMatrixDiag = 113,
kTfLiteBuiltinQuantize = 114,
kTfLiteBuiltinMatrixSetDiag = 115,
kTfLiteBuiltinRound = 116,
kTfLiteBuiltinHardSwish = 117,
kTfLiteBuiltinIf = 118,
kTfLiteBuiltinWhile = 119,
kTfLiteBuiltinNonMaxSuppressionV4 = 120,
kTfLiteBuiltinNonMaxSuppressionV5 = 121,
kTfLiteBuiltinScatterNd = 122,
kTfLiteBuiltinSelectV2 = 123,
kTfLiteBuiltinDensify = 124,
kTfLiteBuiltinSegmentSum = 125,
kTfLiteBuiltinBatchMatmul = 126,
kTfLiteBuiltinPlaceholderForGreaterOpCodes = 127,
kTfLiteBuiltinCumsum = 128,
kTfLiteBuiltinCallOnce = 129,
kTfLiteBuiltinBroadcastTo = 130,
kTfLiteBuiltinRfft2d = 131,
kTfLiteBuiltinConv3d = 132,
} TfLiteBuiltinOperator;
#ifdef __cplusplus
} // extern "C"
#endif // __cplusplus
#endif // TENSORFLOW_LITE_BUILTIN_OPS_H_