Hugging Face's logo

AXERA-TECH
/
FireRedASR-AED

Model card Files
xet
Community
FireRedASR-AED
File size: 7,157 Bytes 
90f0b29
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#include "main.h"
using namespace std;
template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
{
  typedef typename MatrixType::Scalar Scalar;
  enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
  typedef Matrix<Scalar, Rows, 1> VectorType;
  typedef Matrix<Scalar, 1, Cols> RowVectorType;
  typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
  typedef Matrix<Scalar, Dynamic, Dynamic> DynMatrixType;
  typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
  typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
  typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
  Index rows = m.rows();
  Index cols = m.cols();

  MatrixType m1 = MatrixType::Random(rows, cols),
             m2 = MatrixType::Random(rows, cols);
  VectorType v1 = VectorType::Random(rows),
             v2 = VectorType::Random(rows);
  RowVectorType rv1 = RowVectorType::Random(cols),
             rv2 = RowVectorType::Random(cols);

  LeftDiagonalMatrix ldm1(v1), ldm2(v2);
  RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
  
  Scalar s1 = internal::random<Scalar>();

  SquareMatrixType sq_m1 (v1.asDiagonal());
  VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
  sq_m1 = v1.asDiagonal();
  VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
  SquareMatrixType sq_m2 = v1.asDiagonal();
  VERIFY_IS_APPROX(sq_m1, sq_m2);
  
  ldm1 = v1.asDiagonal();
  LeftDiagonalMatrix ldm3(v1);
  VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal());
  LeftDiagonalMatrix ldm4 = v1.asDiagonal();
  VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal());
  
  sq_m1.block(0,0,rows,rows) = ldm1;
  VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
  sq_m1.transpose() = ldm1;
  VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
  
  Index i = internal::random<Index>(0, rows-1);
  Index j = internal::random<Index>(0, cols-1);
  
  VERIFY_IS_APPROX( ((ldm1 * m1)(i,j))  , ldm1.diagonal()(i) * m1(i,j) );
  VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j))  , ldm1.diagonal()(i) * (m1+m2)(i,j) );
  VERIFY_IS_APPROX( ((m1 * rdm1)(i,j))  , rdm1.diagonal()(j) * m1(i,j) );
  VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j))  , v1(i) * m1(i,j) );
  VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j))  , rv1(j) * m1(i,j) );
  VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j))  , (v1+v2)(i) * m1(i,j) );
  VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j))  , (v1+v2)(i) * (m1+m2)(i,j) );
  VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j))  , (rv1+rv2)(j) * m1(i,j) );
  VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j))  , (rv1+rv2)(j) * (m1+m2)(i,j) );
  
  if(rows>1)
  {
    DynMatrixType tmp = m1.topRows(rows/2), res;
    VERIFY_IS_APPROX( (res = m1.topRows(rows/2) * rv1.asDiagonal()), tmp * rv1.asDiagonal() );
    VERIFY_IS_APPROX( (res = v1.head(rows/2).asDiagonal()*m1.topRows(rows/2)), v1.head(rows/2).asDiagonal()*tmp );
  }

  BigMatrix big;
  big.setZero(2*rows, 2*cols);
  
  big.block(i,j,rows,cols) = m1;
  big.block(i,j,rows,cols) = v1.asDiagonal() * big.block(i,j,rows,cols);
  
  VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , v1.asDiagonal() * m1 );
  
  big.block(i,j,rows,cols) = m1;
  big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
  VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
  
  
  // scalar multiple
  VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1);
  VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal());
  
  VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
  VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);
  
  // Diagonal to dense
  sq_m1.setRandom();
  sq_m2 = sq_m1;
  VERIFY_IS_APPROX( (sq_m1 += (s1*v1).asDiagonal()), sq_m2 += (s1*v1).asDiagonal().toDenseMatrix() );
  VERIFY_IS_APPROX( (sq_m1 -= (s1*v1).asDiagonal()), sq_m2 -= (s1*v1).asDiagonal().toDenseMatrix() );
  VERIFY_IS_APPROX( (sq_m1 = (s1*v1).asDiagonal()), (s1*v1).asDiagonal().toDenseMatrix() );

  sq_m1.setRandom();
  sq_m2 = v1.asDiagonal();
  sq_m2 = sq_m1 * sq_m2;
  VERIFY_IS_APPROX( (sq_m1*v1.asDiagonal()).col(i), sq_m2.col(i) );
  VERIFY_IS_APPROX( (sq_m1*v1.asDiagonal()).row(i), sq_m2.row(i) );
}

template<typename MatrixType> void as_scalar_product(const MatrixType& m)
{
  typedef typename MatrixType::Scalar Scalar;
  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
  typedef Matrix<Scalar, Dynamic, Dynamic> DynMatrixType;
  typedef Matrix<Scalar, Dynamic, 1> DynVectorType;
  typedef Matrix<Scalar, 1, Dynamic> DynRowVectorType;

  Index rows = m.rows();
  Index depth = internal::random<Index>(1,EIGEN_TEST_MAX_SIZE);

  VectorType v1 = VectorType::Random(rows);  
  DynVectorType     dv1  = DynVectorType::Random(depth);
  DynRowVectorType  drv1 = DynRowVectorType::Random(depth);
  DynMatrixType     dm1  = dv1;
  DynMatrixType     drm1 = drv1;
  
  Scalar s = v1(0);

  VERIFY_IS_APPROX( v1.asDiagonal() * drv1, s*drv1 );
  VERIFY_IS_APPROX( dv1 * v1.asDiagonal(), dv1*s );

  VERIFY_IS_APPROX( v1.asDiagonal() * drm1, s*drm1 );
  VERIFY_IS_APPROX( dm1 * v1.asDiagonal(), dm1*s );
}

template<int>
void bug987()
{
  Matrix3Xd points = Matrix3Xd::Random(3, 3);
  Vector2d diag = Vector2d::Random();
  Matrix2Xd tmp1 = points.topRows<2>(), res1, res2;
  VERIFY_IS_APPROX( res1 = diag.asDiagonal() * points.topRows<2>(), res2 = diag.asDiagonal() * tmp1 );
  Matrix2d tmp2 = points.topLeftCorner<2,2>();
  VERIFY_IS_APPROX(( res1 = points.topLeftCorner<2,2>()*diag.asDiagonal()) , res2 = tmp2*diag.asDiagonal() );
}

void test_diagonalmatrices()
{
  for(int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_1( diagonalmatrices(Matrix<float, 1, 1>()) );
    CALL_SUBTEST_1( as_scalar_product(Matrix<float, 1, 1>()) );

    CALL_SUBTEST_2( diagonalmatrices(Matrix3f()) );
    CALL_SUBTEST_3( diagonalmatrices(Matrix<double,3,3,RowMajor>()) );
    CALL_SUBTEST_4( diagonalmatrices(Matrix4d()) );
    CALL_SUBTEST_5( diagonalmatrices(Matrix<float,4,4,RowMajor>()) );
    CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
    CALL_SUBTEST_6( as_scalar_product(MatrixXcf(1,1)) );
    CALL_SUBTEST_7( diagonalmatrices(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
    CALL_SUBTEST_8( diagonalmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
    CALL_SUBTEST_9( diagonalmatrices(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
    CALL_SUBTEST_9( diagonalmatrices(MatrixXf(1,1)) );
    CALL_SUBTEST_9( as_scalar_product(MatrixXf(1,1)) );
  }
  CALL_SUBTEST_10( bug987<0>() );
}