einstein.cpp
1 /*
2  * This file is part of CasADi.
3  *
4  * CasADi -- A symbolic framework for dynamic optimization.
5  * Copyright (C) 2010-2023 Joel Andersson, Joris Gillis, Moritz Diehl,
6  * KU Leuven. All rights reserved.
7  * Copyright (C) 2011-2014 Greg Horn
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24 
25 
26 #ifndef CASADI_EINSTEIN_CPP
27 #define CASADI_EINSTEIN_CPP
28 
29 #include "einstein.hpp"
30 #include "casadi_misc.hpp"
31 #include "function_internal.hpp"
32 #include "runtime/shared.hpp"
33 
34 namespace casadi {
35 
36  Einstein::Einstein(const MX& C, const MX& A, const MX& B,
37  const std::vector<casadi_int>& dim_c, const std::vector<casadi_int>& dim_a,
38  const std::vector<casadi_int>& dim_b,
39  const std::vector<casadi_int>& c, const std::vector<casadi_int>& a,
40  const std::vector<casadi_int>& b):
41  dim_c_(dim_c), dim_a_(dim_a), dim_b_(dim_b), c_(c), a_(a), b_(b) {
42 
43  set_dep(C, A, B);
44  set_sparsity(C.sparsity());
45 
46  n_iter_ = einstein_process(A, B, C, dim_a, dim_b, dim_c, a, b, c,
48 
49  }
50 
51  std::string Einstein::disp(const std::vector<std::string>& arg) const {
52  return "einstein(" + arg.at(0) + "," + arg.at(1) + "," + arg.at(2) + ")";
53  }
54 
55  int Einstein::eval(const double** arg, double** res, casadi_int* iw, double* w) const {
56  return eval_gen<double>(arg, res, iw, w);
57  }
58 
59  int Einstein::eval_sx(const SXElem** arg, SXElem** res, casadi_int* iw, SXElem* w) const {
60  return eval_gen<SXElem>(arg, res, iw, w);
61  }
62 
63  template<typename T>
64  int Einstein::eval_gen(const T** arg, T** res, casadi_int* iw, T* w) const {
65  if (arg[0]!=res[0]) std::copy(arg[0], arg[0]+dep(0).nnz(), res[0]);
66 
67  einstein_eval(n_iter_, iter_dims_, strides_a_, strides_b_, strides_c_, arg[1], arg[2], res[0]);
68  return 0;
69  }
70 
71  void Einstein::ad_forward(const std::vector<std::vector<MX> >& fseed,
72  std::vector<std::vector<MX> >& fsens) const {
73  for (casadi_int d=0; d<fsens.size(); ++d) {
74  fsens[d][0] = fseed[d][0]
75  + MX::einstein(dep(1), fseed[d][2], dim_a_, dim_b_, dim_c_, a_, b_, c_)
76  + MX::einstein(fseed[d][1], dep(2), dim_a_, dim_b_, dim_c_, a_, b_, c_);
77  }
78  }
79 
80  void Einstein::ad_reverse(const std::vector<std::vector<MX> >& aseed,
81  std::vector<std::vector<MX> >& asens) const {
82  for (casadi_int d=0; d<aseed.size(); ++d) {
83  asens[d][1] += MX::einstein(aseed[d][0], dep(2), dim_c_, dim_b_, dim_a_, c_, b_, a_);
84  asens[d][2] += MX::einstein(dep(1), aseed[d][0], dim_a_, dim_c_, dim_b_, a_, c_, b_);
85  asens[d][0] += aseed[d][0];
86  }
87  }
88 
89 
90 
91  int Einstein::sp_forward(const bvec_t** arg, bvec_t** res, casadi_int* iw, bvec_t* w) const {
92  return eval_gen<bvec_t>(arg, res, iw, w);
93  }
94 
95  int Einstein::sp_reverse(bvec_t** arg, bvec_t** res, casadi_int* iw, bvec_t* w) const {
96  //casadi_int* ind = iw;
97  //casadi_int cumprod;
98 
99  // Main loop
100  for (casadi_int i=0;i<n_iter_;++i) {
101 
102  // Data pointers
103  bvec_t* a = arg[1]+strides_a_[0];
104  bvec_t* b = arg[2]+strides_b_[0];
105  bvec_t* c = res[0]+strides_c_[0];
106 
107  // Construct indices
108  casadi_int sub = i;
109  for (casadi_int j=0;j<iter_dims_.size();++j) {
110  casadi_int ind = sub % iter_dims_[j];
111  sub/= iter_dims_[j];
112  a+= strides_a_[1+j]*ind;
113  b+= strides_b_[1+j]*ind;
114  c+= strides_c_[1+j]*ind;
115  }
116 
117  // Perform the actual multiplication
118  Contraction<bvec_t>(*c, 0, *a);
119  Contraction<bvec_t>(0, *c, *b);
120  }
121  copy_rev(arg[0], res[0], nnz());
122  return 0;
123  }
124 
125  void Einstein::eval_mx(const std::vector<MX>& arg, std::vector<MX>& res) const {
126  res[0] = einstein(arg[1], arg[2], arg[0], dim_a_, dim_b_, dim_c_, a_, b_, c_);
127  }
128 
130  const std::vector<casadi_int>& arg,
131  const std::vector<casadi_int>& res,
132  const std::vector<bool>& arg_is_ref,
133  std::vector<bool>& res_is_ref) const {
134 
135  // Copy first argument if not inplace
136  if (arg[0]!=res[0] || arg_is_ref[0]) {
137  g << g.copy(g.work(arg[0], nnz(), arg_is_ref[0]), nnz(), g.work(res[0], nnz(), false));
138  }
139 
140  // main loop
141  g.local("i", "casadi_int");
142  g << "for (i=0; i<" << n_iter_ << "; ++i) {\n";
143 
144  // Data pointers
145  g.local("cr", "const casadi_real", "*");
146  g.local("cs", "const casadi_real", "*");
147  g.local("rr", "casadi_real", "*");
148  g << "cr = " << g.work(arg[1], dep(1).nnz(), arg_is_ref[1]) << "+" << strides_a_[0] << ";\n";
149  g << "cs = " << g.work(arg[2], dep(2).nnz(), arg_is_ref[2]) << "+" << strides_b_[0] << ";\n";
150  g << "rr = " << g.work(res[0], dep(0).nnz(), false) << "+" << strides_c_[0] << ";\n";
151 
152  // Construct indices
153  for (casadi_int j=0; j<iter_dims_.size(); ++j) {
154  if (j==0) {
155  g.local("k", "casadi_int");
156  g << "k = i;\n";
157  g.local("j", "casadi_int");
158  }
159  g << "j = k % " << iter_dims_[j] << ";\n";
160  if (j+1<iter_dims_.size()) g << "k /= " << iter_dims_[j] << ";\n";
161  if (strides_a_[1+j]) g << "cr += j*" << strides_a_[1+j] << ";\n";
162  if (strides_b_[1+j]) g << "cs += j*" << strides_b_[1+j] << ";\n";
163  if (strides_c_[1+j]) g << "rr += j*" << strides_c_[1+j] << ";\n";
164  }
165 
166  // Perform the actual multiplication
167  g << "*rr += *cr**cs;\n";
168 
169  g << "}\n";
170  }
171 
172 } // namespace casadi
173 
174 #endif // CASADI_EINSTEIN_CPP
Helper class for C code generation.
std::string work(casadi_int n, casadi_int sz, bool is_ref) const
std::string copy(const std::string &arg, std::size_t n, const std::string &res)
Create a copy operation.
void local(const std::string &name, const std::string &type, const std::string &ref="")
Declare a local variable.
void generate(CodeGenerator &g, const std::vector< casadi_int > &arg, const std::vector< casadi_int > &res, const std::vector< bool > &arg_is_ref, std::vector< bool > &res_is_ref) const override
Generate code for the operation.
Definition: einstein.cpp:129
casadi_int n_iter_
Definition: einstein.hpp:148
int eval(const double **arg, double **res, casadi_int *iw, double *w) const override
Evaluate the function numerically.
Definition: einstein.cpp:55
void ad_reverse(const std::vector< std::vector< MX > > &aseed, std::vector< std::vector< MX > > &asens) const override
Calculate reverse mode directional derivatives.
Definition: einstein.cpp:80
int sp_reverse(bvec_t **arg, bvec_t **res, casadi_int *iw, bvec_t *w) const override
Propagate sparsity backwards.
Definition: einstein.cpp:95
std::vector< casadi_int > dim_c_
Dimensions of tensors A B C.
Definition: einstein.hpp:138
int sp_forward(const bvec_t **arg, bvec_t **res, casadi_int *iw, bvec_t *w) const override
Propagate sparsity forward.
Definition: einstein.cpp:91
std::vector< casadi_int > dim_a_
Definition: einstein.hpp:138
std::string disp(const std::vector< std::string > &arg) const override
Print expression.
Definition: einstein.cpp:51
std::vector< casadi_int > dim_b_
Definition: einstein.hpp:138
void ad_forward(const std::vector< std::vector< MX > > &fseed, std::vector< std::vector< MX > > &fsens) const override
Calculate forward mode directional derivatives.
Definition: einstein.cpp:71
std::vector< casadi_int > strides_a_
Definition: einstein.hpp:144
Einstein(const MX &C, const MX &A, const MX &B, const std::vector< casadi_int > &dim_c, const std::vector< casadi_int > &dim_a, const std::vector< casadi_int > &dim_b, const std::vector< casadi_int > &c, const std::vector< casadi_int > &a, const std::vector< casadi_int > &b)
Constructor.
Definition: einstein.cpp:36
std::vector< casadi_int > iter_dims_
Definition: einstein.hpp:142
std::vector< casadi_int > b_
Definition: einstein.hpp:140
std::vector< casadi_int > c_
Einstein indices.
Definition: einstein.hpp:140
std::vector< casadi_int > strides_c_
Definition: einstein.hpp:146
int eval_sx(const SXElem **arg, SXElem **res, casadi_int *iw, SXElem *w) const override
Evaluate the function symbolically (SX)
Definition: einstein.cpp:59
int eval_gen(const T **arg, T **res, casadi_int *iw, T *w) const
Evaluate the function (template)
Definition: einstein.cpp:64
std::vector< casadi_int > a_
Definition: einstein.hpp:140
std::vector< casadi_int > strides_b_
Definition: einstein.hpp:145
void eval_mx(const std::vector< MX > &arg, std::vector< MX > &res) const override
Evaluate symbolically (MX)
Definition: einstein.cpp:125
virtual casadi_int ind() const
Definition: mx_node.cpp:210
static void copy_rev(bvec_t *arg, bvec_t *res, casadi_int len)
Propagate sparsities backwards through a copy operation.
Definition: mx_node.cpp:1247
casadi_int nnz(casadi_int i=0) const
Definition: mx_node.hpp:389
const MX & dep(casadi_int ind=0) const
dependencies - functions that have to be evaluated before this one
Definition: mx_node.hpp:354
void set_sparsity(const Sparsity &sparsity)
Set the sparsity.
Definition: mx_node.cpp:222
void set_dep(const MX &dep)
Set unary dependency.
Definition: mx_node.cpp:226
MX - Matrix expression.
Definition: mx.hpp:92
static MX einstein(const MX &A, const MX &B, const MX &C, const std::vector< casadi_int > &dim_a, const std::vector< casadi_int > &dim_b, const std::vector< casadi_int > &dim_c, const std::vector< casadi_int > &a, const std::vector< casadi_int > &b, const std::vector< casadi_int > &c)
Computes an einstein dense tensor contraction.
Definition: mx.cpp:662
The basic scalar symbolic class of CasADi.
Definition: sx_elem.hpp:75
The casadi namespace.
Definition: archiver.cpp:28
void einstein_eval(casadi_int n_iter, const std::vector< casadi_int > &iter_dims, const std::vector< casadi_int > &strides_a, const std::vector< casadi_int > &strides_b, const std::vector< casadi_int > &strides_c, const T *a_in, const T *b_in, T *c_in)
Definition: shared.hpp:161
casadi_int einstein_process(const T &A, const T &B, const T &C, const std::vector< casadi_int > &dim_a, const std::vector< casadi_int > &dim_b, const std::vector< casadi_int > &dim_c, const std::vector< casadi_int > &a, const std::vector< casadi_int > &b, const std::vector< casadi_int > &c, std::vector< casadi_int > &iter_dims, std::vector< casadi_int > &strides_a, std::vector< casadi_int > &strides_b, std::vector< casadi_int > &strides_c)
Definition: shared.hpp:35
unsigned long long bvec_t