1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
|
//
// Copyright © 2020-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <armnn_delegate.hpp>
#include <armnn/ArmNN.hpp>
#include <armnn/BackendHelper.hpp>
#include <armnn/utility/Assert.hpp>
#include <armnn/utility/NumericCast.hpp>
#include <armnnUtils/Permute.hpp>
#include <armnnUtils/TensorUtils.hpp>
#include <tensorflow/lite/builtin_ops.h>
#include <tensorflow/lite/c/builtin_op_data.h>
#include <tensorflow/lite/c/common.h>
#include <tensorflow/lite/minimal_logging.h>
#include <tensorflow/lite/kernels/kernel_util.h>
namespace
{
uint32_t NonNegative(int32_t value, int nodeIndex)
{
if (value < 0)
{
throw armnn::Exception(
"TfLiteArmnnDelegate: Non-negative value in node " + std::to_string(static_cast<int>(nodeIndex)));
}
else
{
return static_cast<uint32_t>(value);
}
}
void ExpandTensorRankToEqual(armnn::TensorInfo& inputInfo0,
armnn::TensorInfo& inputInfo1)
{
unsigned int inputDimensions0 = inputInfo0.GetNumDimensions();
unsigned int inputDimensions1 = inputInfo1.GetNumDimensions();
if (inputDimensions0 == inputDimensions1)
{
return;
}
unsigned int biggerInputDimensions = std::max(inputDimensions0, inputDimensions1);
bool input0IsSmaller = inputDimensions0 < inputDimensions1;
armnn::TensorInfo& smallInfo = input0IsSmaller ? inputInfo0 : inputInfo1;
const armnn::TensorShape& newShape = armnnUtils::ExpandDimsToRank(smallInfo.GetShape(), biggerInputDimensions);
smallInfo.SetShape(newShape);
}
void CalcPadding(uint32_t inputSize,
uint32_t filterSize,
uint32_t stride,
uint32_t dilation,
uint32_t& paddingFront,
uint32_t& paddingBack,
TfLitePadding padding)
{
paddingFront = 0;
paddingBack = 0;
if (padding == kTfLitePaddingSame)
{
uint32_t outputSize = (inputSize + stride - 1) / stride;
uint32_t dilatedSize = filterSize + (dilation - 1) * (filterSize - 1);
uint32_t temp = (outputSize - 1) * stride + dilatedSize;
if (temp > inputSize)
{
paddingFront = (temp - inputSize) / 2;
paddingBack = (temp - inputSize) - paddingFront;
}
}
}
unsigned int ComputeWrappedIndex(int index, unsigned int numDimensions)
{
int numDims = armnn::numeric_cast<int>(numDimensions);
int wrappedIndex = index < 0 ? numDims + index : index;
ARMNN_ASSERT(wrappedIndex >= 0);
ARMNN_ASSERT(wrappedIndex < numDims);
return static_cast<unsigned int>(wrappedIndex);
};
bool AreAllSigned32(const armnn::TensorInfo& inputInfo1,
const armnn::TensorInfo& inputInfo2,
const armnn::TensorInfo& outputInfo)
{
return (armnn::DataType::Signed32 == inputInfo1.GetDataType()) &&
(armnn::DataType::Signed32 == inputInfo2.GetDataType()) &&
(armnn::DataType::Signed32 == outputInfo.GetDataType());
}
void UpdateConstantTensorOutputs(const armnn::TensorInfo& inputInfo, armnn::TensorInfo& outputInfo)
{
// If input tensor info is constant and output tensor info shape is not specified
// set the output shape from input shape
if (inputInfo.IsConstant() && outputInfo.GetShape().GetDimensionality() == armnn::Dimensionality::NotSpecified)
{
outputInfo.SetShape(inputInfo.GetShape());
}
}
void SetupConcatViewOrigin(const armnn::TensorInfo& inputTensorInfo,
armnn::OriginsDescriptor& concatDescriptor,
const unsigned int concatAxis,
unsigned int inputIndex,
unsigned int& mergeDimOrigin)
{
const uint32_t inputRank = concatDescriptor.GetNumDimensions();
// double check dimensions of the tensors
if (inputTensorInfo.GetNumDimensions() != inputRank)
{
throw armnn::ParseException("The number of dimensions for input tensors "
"of the concatenation operator should be: " + std::to_string(inputRank));
}
for (unsigned int j = 0; j < concatAxis; ++j)
{
concatDescriptor.SetViewOriginCoord(inputIndex, j, 0);
}
concatDescriptor.SetViewOriginCoord(inputIndex, concatAxis, mergeDimOrigin);
mergeDimOrigin += inputTensorInfo.GetShape()[concatAxis];
for (unsigned int j = concatAxis + 1; j < inputRank; ++j)
{
concatDescriptor.SetViewOriginCoord(inputIndex, j, 0);
}
}
} // namespace anonymous
|
