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// SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later
// SPDX-FileCopyrightText: Bradley M. Bell <bradbell@seanet.com>
// SPDX-FileContributor: 2003-24 Bradley M. Bell
// ----------------------------------------------------------------------------
/*
{xrst_begin subgraph_reverse.cpp}
{xrst_spell
subgraphs
}
Computing Reverse Mode on Subgraphs: Example and Test
#####################################################
{xrst_literal
// BEGIN C++
// END C++
}
{xrst_end subgraph_reverse.cpp}
*/
// BEGIN C++
# include <cppad/cppad.hpp>
bool subgraph_reverse(void)
{ bool ok = true;
//
using CppAD::AD;
using CppAD::NearEqual;
using CppAD::sparse_rc;
using CppAD::sparse_rcv;
//
typedef CPPAD_TESTVECTOR(AD<double>) a_vector;
typedef CPPAD_TESTVECTOR(double) d_vector;
typedef CPPAD_TESTVECTOR(bool) b_vector;
typedef CPPAD_TESTVECTOR(size_t) s_vector;
//
double eps99 = 99.0 * std::numeric_limits<double>::epsilon();
//
// domain space vector
size_t n = 4;
a_vector a_x(n);
for(size_t j = 0; j < n; j++)
a_x[j] = AD<double> (0);
//
// declare independent variables and starting recording
CppAD::Independent(a_x);
//
size_t m = 3;
a_vector a_y(m);
a_y[0] = a_x[0] + a_x[1];
a_y[1] = a_x[2] + a_x[3];
a_y[2] = a_x[0] + a_x[1] + a_x[2] + a_x[3] * a_x[3] / 2.;
//
// create f: x -> y and stop tape recording
CppAD::ADFun<double> f(a_x, a_y);
ok &= f.size_random() == 0;
//
// new value for the independent variable vector
d_vector x(n);
for(size_t j = 0; j < n; j++)
x[j] = double(j);
f.Forward(0, x);
/*
[ 1 1 0 0 ]
J(x) = [ 0 0 1 1 ]
[ 1 1 1 x_3]
*/
double J[] = {
1.0, 1.0, 0.0, 0.0,
0.0, 0.0, 1.0, 1.0,
1.0, 1.0, 1.0, 0.0
};
J[11] = x[3];
//
// exclude x[0] from the calculations
b_vector select_domain(n);
select_domain[0] = false;
for(size_t j = 1; j < n; j++)
select_domain[j] = true;
//
// initilaize for reverse mode derivatives computation on subgraphs
f.subgraph_reverse(select_domain);
//
// compute the derivative for each range component
for(size_t i = 0; i < m; i++)
{ d_vector dw;
s_vector col;
size_t q = 1; // derivative of one Taylor coefficient (zero order)
f.subgraph_reverse(q, i, col, dw);
//
// check order in col
for(size_t c = 1; c < size_t( col.size() ); c++)
ok &= col[c] > col[c-1];
//
// check that x[0] has been excluded by select_domain
if( size_t( col.size() ) > 0 )
ok &= col[0] != 0;
//
// check derivatives for i-th row of J(x)
// note that dw is only specified for j in col
size_t c = 0;
for(size_t j = 1; j < n; j++)
{ while( c < size_t( col.size() ) && col[c] < j )
++c;
if( c < size_t( col.size() ) && col[c] == j )
ok &= NearEqual(dw[j], J[i * n + j], eps99, eps99);
else
ok &= NearEqual(0.0, J[i * n + j], eps99, eps99);
}
}
ok &= f.size_random() > 0;
f.clear_subgraph();
ok &= f.size_random() == 0;
return ok;
}
// END C++
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