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
|
/*
* Copyright (c) 2021 Arm Limited. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* 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.
*/
#include "Wav2LetterPreprocess.hpp"
#include <limits>
#include <algorithm>
#include <catch.hpp>
constexpr uint32_t numMfccFeatures = 13;
constexpr uint32_t numMfccVectors = 10;
/* Test vector output: generated using test-asr-preprocessing.py. */
int8_t expectedResult[numMfccVectors][numMfccFeatures * 3] = {
/* Feature vec 0. */
-32, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11, /* MFCCs. */
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, /* Delta 1. */
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, /* Delta 2. */
/* Feature vec 1. */
-31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
/* Feature vec 2. */
-31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -12, -12, -12,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
/* Feature vec 3. */
-31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -11, -12, -12,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
/* Feature vec 4 : this should have valid delta 1 and delta 2. */
-31, 4, -9, -9, -10, -10, -11, -11, -11, -11, -11, -12, -12,
-38, -29, -9, 1, -2, -7, -8, -8, -12, -16, -14, -5, 5,
-68, -50, -13, 5, 0, -9, -9, -8, -13, -20, -19, -3, 15,
/* Feature vec 5 : this should have valid delta 1 and delta 2. */
-31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -11, -12, -12,
-62, -45, -11, 5, 0, -8, -9, -8, -12, -19, -17, -3, 13,
-27, -22, -13, -9, -11, -12, -12, -11, -11, -13, -13, -10, -6,
/* Feature vec 6. */
-31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
/* Feature vec 7. */
-32, 4, -9, -8, -10, -10, -11, -11, -11, -12, -12, -11, -11,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
/* Feature vec 8. */
-32, 4, -9, -8, -10, -10, -11, -11, -11, -12, -12, -11, -11,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10,
/* Feature vec 9. */
-31, 4, -9, -8, -10, -10, -11, -11, -11, -11, -12, -11, -11,
-11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11, -11,
-10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10, -10
};
void PopulateTestWavVector(std::vector<int16_t>& vec)
{
constexpr int int16max = std::numeric_limits<int16_t>::max();
int val = 0;
for (size_t i = 0; i < vec.size(); ++i, ++val) {
/* We want a differential filter response from both - order 1
* and 2 => Don't have a linear signal here - we use a signal
* using squares for example. Alternate sign flips might work
* just as well and will be computationally less work! */
int valsq = val * val;
if (valsq > int16max) {
val = 0;
valsq = 0;
}
vec[i] = valsq;
}
}
TEST_CASE("Preprocessing calculation INT8")
{
/* Initialise the HAL and platform. */
hal_platform platform;
data_acq_module data_acq;
data_psn_module data_psn;
platform_timer timer;
hal_init(&platform, &data_acq, &data_psn, &timer);
hal_platform_init(&platform);
/* Constants. */
const uint32_t windowLen = 512;
const uint32_t windowStride = 160;
const int dimArray[] = {3, 1, numMfccFeatures * 3, numMfccVectors};
const float quantScale = 0.1410219967365265;
const int quantOffset = -11;
/* Test wav memory. */
std::vector <int16_t> testWav((windowStride * numMfccVectors) +
(windowLen - windowStride));
/* Populate with dummy input. */
PopulateTestWavVector(testWav);
/* Allocate mem for tensor. */
std::vector<int8_t> tensorVec(dimArray[1]*dimArray[2]*dimArray[3]);
/* Initialise dimensions and the test tensor. */
TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
TfLiteTensor tensor = tflite::testing::CreateQuantizedTensor(
tensorVec.data(), dims, quantScale, quantOffset, "preprocessedInput");
/* Initialise pre-processing module. */
arm::app::audio::asr::Preprocess prep{
numMfccFeatures, windowLen, windowStride, numMfccVectors};
/* Invoke pre-processing. */
REQUIRE(prep.Invoke(testWav.data(), testWav.size(), &tensor));
/* Wrap the tensor with a std::vector for ease. */
int8_t * tensorData = tflite::GetTensorData<int8_t>(&tensor);
std::vector <int8_t> vecResults =
std::vector<int8_t>(tensorData, tensorData + tensor.bytes);
/* Check sizes. */
REQUIRE(vecResults.size() == sizeof(expectedResult));
/* Check that the elements have been calculated correctly. */
for (uint32_t j = 0; j < numMfccVectors; ++j) {
for (uint32_t i = 0; i < numMfccFeatures * 3; ++i) {
size_t tensorIdx = (j * numMfccFeatures * 3) + i;
CHECK(vecResults[tensorIdx] == expectedResult[j][i]);
}
}
}
|
