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
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
|
//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <Layer.hpp>
#include <tosaCommon/TosaMappings.hpp>
#include <tosaCommon/operatorMappings/TosaOperatorUtils.hpp>
#include <doctest/doctest.h>
#include <numeric>
using namespace armnn;
using namespace tosa;
inline void VerifyTosaAttribute(const BaseDescriptor& descriptor,
const TosaAttributeBase* attribute,
std::vector<int32_t> inputShape,
std::vector<int32_t> outputShape,
LayerType type,
uint32_t mappingOpNumber = 0)
{
switch (type)
{
case LayerType::Convolution2d:
{
auto conv2dDesc = PolymorphicDowncast<const Convolution2dDescriptor*>(&descriptor);
std::vector<int> pad = {static_cast<int>(conv2dDesc->m_PadTop),
static_cast<int>(conv2dDesc->m_PadBottom),
static_cast<int>(conv2dDesc->m_PadLeft),
static_cast<int>(conv2dDesc->m_PadRight)};
std::vector<int> dilation = {static_cast<int>(conv2dDesc->m_DilationY),
static_cast<int>(conv2dDesc->m_DilationX)};
std::vector<int> stride = {static_cast<int>(conv2dDesc->m_StrideY),
static_cast<int>(conv2dDesc->m_StrideX)};
TosaConvAttribute convAttribute(attribute);
CHECK(pad == convAttribute.pad());
CHECK(dilation == convAttribute.dilation());
CHECK(stride == convAttribute.stride());
break;
}
case LayerType::Pooling2d:
{
auto poolDesc = PolymorphicDowncast<const Pooling2dDescriptor*>(&descriptor);
std::vector<int> pad = {static_cast<int>(poolDesc->m_PadTop),
static_cast<int>(poolDesc->m_PadBottom),
static_cast<int>(poolDesc->m_PadLeft),
static_cast<int>(poolDesc->m_PadRight)};
bool avgPoolIgnoreValue =
(poolDesc->m_PoolType == PoolingAlgorithm::Average) &&
(poolDesc->m_PaddingMethod == PaddingMethod::IgnoreValue);
if (avgPoolIgnoreValue)
{
if (mappingOpNumber == 0)
{
if (poolDesc->m_DataLayout == DataLayout::NHWC)
{
pad = {0,
0,
static_cast<int>(poolDesc->m_PadTop),
static_cast<int>(poolDesc->m_PadBottom),
static_cast<int>(poolDesc->m_PadLeft),
static_cast<int>(poolDesc->m_PadRight),
0,
0
};
}
else
{
pad = {0,
0,
0,
0,
static_cast<int>(poolDesc->m_PadTop),
static_cast<int>(poolDesc->m_PadBottom),
static_cast<int>(poolDesc->m_PadLeft),
static_cast<int>(poolDesc->m_PadRight)
};
}
TosaPadAttribute padAttribute(attribute);
CHECK(pad == padAttribute.padding());
CHECK(0.0f == padAttribute.pad_const_fp());
CHECK(0 == padAttribute.pad_const_int());
break;
}
pad = {0, 0, 0, 0};
}
std::vector<int> kernel = {static_cast<int>(poolDesc->m_PoolHeight),
static_cast<int>(poolDesc->m_PoolWidth)};
std::vector<int> stride = {static_cast<int>(poolDesc->m_StrideY),
static_cast<int>(poolDesc->m_StrideX)};
TosaPoolAttribute poolAttribute(attribute);
CHECK(pad == poolAttribute.pad());
CHECK(kernel == poolAttribute.kernel());
CHECK(stride == poolAttribute.stride());
break;
}
case LayerType::Reshape:
{
auto reshapeDesc = PolymorphicDowncast<const ReshapeDescriptor*>(&descriptor);
TosaReshapeAttribute reshapeAttribute(attribute);
std::vector<int32_t> shapeAttrib = reshapeAttribute.new_shape();
CHECK(GetTosaTensorShape(reshapeDesc->m_TargetShape) == shapeAttrib);
CHECK(outputShape == shapeAttrib);
auto numInputElements = std::accumulate(std::begin(inputShape),
std::end(inputShape),
1,
std::multiplies<int32_t>());
auto numAttributeShapeElements = std::accumulate(std::begin(shapeAttrib),
std::end(shapeAttrib),
1,
std::multiplies<int32_t>());
CHECK(numInputElements == numAttributeShapeElements);
break;
}
case LayerType::Slice:
{
auto sliceDesc = PolymorphicDowncast<const SliceDescriptor*>(&descriptor);
TosaSliceAttribute reshapeAttribute(attribute);
std::vector<int32_t> begin(sliceDesc->m_Begin.begin(), sliceDesc->m_Begin.end());
std::vector<int32_t> size(sliceDesc->m_Size.begin(), sliceDesc->m_Size.end());
CHECK(begin == reshapeAttribute.start());
CHECK(size == reshapeAttribute.size());
CHECK(begin.size() == inputShape.size());
CHECK(size.size() == inputShape.size());
CHECK(begin.size() == outputShape.size());
CHECK(size.size() == outputShape.size());
break;
}
case LayerType::TransposeConvolution2d:
{
auto transposeConv2dDesc = PolymorphicDowncast<const TransposeConvolution2dDescriptor*>(&descriptor);
std::vector<int> outPad = {-static_cast<int>(transposeConv2dDesc->m_PadTop),
-static_cast<int>(transposeConv2dDesc->m_PadBottom),
-static_cast<int>(transposeConv2dDesc->m_PadLeft),
-static_cast<int>(transposeConv2dDesc->m_PadRight)};
std::vector<int> stride = {static_cast<int>(transposeConv2dDesc->m_StrideY),
static_cast<int>(transposeConv2dDesc->m_StrideX)};
TosaTransposeConvAttribute transposeConvAttribute(attribute);
CHECK(outPad == transposeConvAttribute.out_pad());
CHECK(stride == transposeConvAttribute.stride());
break;
}
default:
break;
}
return;
}
inline void AssertTosaOneToOneMappingBasicBlock(TosaSerializationBasicBlock* basicBlock,
std::vector<std::vector<int32_t>> inputShape,
std::vector<std::vector<int32_t>> outputShape,
Op tosaOp,
Attribute tosaAttribute,
const BaseDescriptor& descriptor,
LayerType type,
DType dataType = DType_FP32)
{
uint32_t numInputs = static_cast<uint32_t>(inputShape.size());
uint32_t numInputTensors = static_cast<uint32_t>(inputShape.size());
uint32_t numOutputs = static_cast<uint32_t>(outputShape.size());
std::string operatorString = TosaOpToString(tosaOp);
// The number of tensors in the block can be different if there are constant layers, as they are created separately.
if(type == LayerType::Convolution2d)
{
numInputTensors = PolymorphicDowncast<const Convolution2dDescriptor*>(&descriptor)->m_BiasEnabled ? 3 : 2;
}
std::string blockStr = operatorString + "_block_";
CHECK(basicBlock->GetName().find(blockStr) != std::string::npos);
CHECK(basicBlock->GetInputs().size() == numInputTensors);
CHECK(basicBlock->GetOutputs().size() == numOutputs);
CHECK(basicBlock->GetOperators().size() == 1);
CHECK(basicBlock->GetTensors().size() == (numInputs + numOutputs));
TosaSerializationOperator* op = basicBlock->GetOperators().at(0);
CHECK(op->GetInputTensorNames().size() == numInputTensors);
CHECK(op->GetOutputTensorNames().size() == numOutputs);
for (uint32_t i = 0; i < numInputs; i++)
{
std::basic_string<char> blockInputName = basicBlock->GetInputs()[i];
std::basic_string<char> operatorInputName = op->GetInputTensorNames()[i];
std::basic_string<char> tensorName = basicBlock->GetTensors()[i]->GetName();
std::string opStr = "input" + std::to_string(i) + "_";
CHECK(blockInputName == operatorInputName);
CHECK(tensorName == operatorInputName);
CHECK(blockInputName.find(opStr) != std::string::npos);
}
for (uint32_t i = 0; i < numOutputs; i++)
{
std::basic_string<char> blockOutputName = basicBlock->GetOutputs()[i];
std::basic_string<char> operatorOutputName = op->GetOutputTensorNames()[i];
std::basic_string<char> tensorName = basicBlock->GetTensors()[numInputs + i]->GetName();
std::string opStr = "output" + std::to_string(i) + "_";
if (tosaOp == Op_CONST)
{
opStr = "constant_";
}
CHECK(blockOutputName == operatorOutputName);
CHECK(tensorName == operatorOutputName);
CHECK(blockOutputName.find(opStr) != std::string::npos);
}
CHECK(op->GetAttributeType() == tosaAttribute);
CHECK(op->GetOp() == tosaOp);
for (uint32_t i = 0; i < numInputs; i++)
{
TosaSerializationTensor* tensor = basicBlock->GetTensors()[i];
CHECK(tensor->GetDtype() == dataType);
CHECK(tensor->GetData().size() == 0);
CHECK(tensor->GetShape() == inputShape[static_cast<unsigned long int>(i)]);
}
for (uint32_t i = 0; i < numOutputs; i++)
{
TosaSerializationTensor* tensor = basicBlock->GetTensors()[i + inputShape.size()];
CHECK(tensor->GetDtype() == dataType);
CHECK(tensor->GetShape() == outputShape[static_cast<unsigned long int>(i)]);
if (tosaOp != Op_CONST)
{
// Const tensors contain data.
CHECK(tensor->GetData().size() == 0);
}
}
std::vector<int32_t> input = {};
std::vector<int32_t> output = {};
if (!inputShape.empty())
{
input = inputShape[0];
}
if (!outputShape.empty())
{
output = outputShape[0];
}
VerifyTosaAttribute(descriptor,
op->GetAttribute(),
input,
output,
type);
}
|
