1/* Part of SWI-Prolog 2 3 Author: Jan Wielemaker 4 E-mail: J.Wielemaker@vu.nl 5 WWW: http://www.swi-prolog.org 6 Copyright (c) 2004-2016, University of Amsterdam 7 VU University Amsterdam 8 All rights reserved. 9 10 Redistribution and use in source and binary forms, with or without 11 modification, are permitted provided that the following conditions 12 are met: 13 14 1. Redistributions of source code must retain the above copyright 15 notice, this list of conditions and the following disclaimer. 16 17 2. Redistributions in binary form must reproduce the above copyright 18 notice, this list of conditions and the following disclaimer in 19 the documentation and/or other materials provided with the 20 distribution. 21 22 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 23 "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 24 LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 25 FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 26 COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 27 INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 28 BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 29 LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 30 CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 31 LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 32 ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 33 POSSIBILITY OF SUCH DAMAGE. 34*/ 35 36:- module('$attvar', 37 [ '$wakeup'/1, % +Wakeup list 38 freeze/2, % +Var, :Goal 39 frozen/2, % @Var, -Goal 40 call_residue_vars/2, % :Goal, -Vars 41 copy_term/3 % +Term, -Copy, -Residue 42 ]). 43 44/** <module> Attributed variable handling 45 46Attributed variable and coroutining support based on attributed 47variables. This module is complemented with C-defined predicates defined 48in pl-attvar.c 49*/ 50 51%! '$wakeup'(+List) 52% 53% Called from the kernel if assignments have been made to 54% attributed variables. 55 56'$wakeup'([]). 57'$wakeup'(wakeup(Attribute, Value, Rest)) :- 58 call_all_attr_uhooks(Attribute, Value), 59 '$wakeup'(Rest). 60 61call_all_attr_uhooks([], _). 62call_all_attr_uhooks(att(Module, AttVal, Rest), Value) :- 63 uhook(Module, AttVal, Value), 64 call_all_attr_uhooks(Rest, Value). 65 66 67%! uhook(+AttributeName, +AttributeValue, +Value) 68% 69% Run the unify hook for attributed named AttributeName after 70% assigning an attvar with attribute AttributeValue the value 71% Value. 72% 73% This predicate deals with reserved attribute names to avoid 74% the meta-call overhead. 75 76uhook(freeze, Goal, Y) :- 77 !, 78 ( attvar(Y) 79 -> ( get_attr(Y, freeze, G2) 80 -> put_attr(Y, freeze, '$and'(G2, Goal)) 81 ; put_attr(Y, freeze, Goal) 82 ) 83 ; unfreeze(Goal) 84 ). 85uhook(Module, AttVal, Value) :- 86 Module:attr_unify_hook(AttVal, Value). 87 88 89%! unfreeze(+ConjunctionOrGoal) 90% 91% Handle unfreezing of conjunctions. As meta-calling control 92% structures is slower than meta-interpreting them we do this in 93% Prolog. Another advantage is that having unfreeze/1 in between 94% makes the stacktrace and profiling easier to intepret. Please 95% note that we cannot use a direct conjunction as this would break 96% freeze(X, (a, !, b)). 97 98unfreeze('$and'(A,B)) :- 99 !, 100 unfreeze(A), 101 unfreeze(B). 102unfreeze(Goal) :- 103 . 104 105%! freeze(@Var, :Goal) 106% 107% Suspend execution of Goal until Var is unbound. 108 109:- meta_predicate 110 freeze(, ). 111 112freeze(Var, Goal) :- 113 '$freeze'(Var, Goal), 114 !. % Succeeds if delayed 115freeze(_, Goal) :- 116 . 117 118%! frozen(@Var, -Goals) 119% 120% Unify Goals with the goals frozen on Var or true if no 121% goals are grozen on Var. 122 123frozen(Var, Goals) :- 124 get_attr(Var, freeze, Goals0), 125 !, 126 make_conjunction(Goals0, Goals). 127frozen(_, true). 128 129make_conjunction('$and'(A0, B0), (A, B)) :- 130 !, 131 make_conjunction(A0, A), 132 make_conjunction(B0, B). 133make_conjunction(G, G). 134 135 136 /******************************* 137 * PORTRAY * 138 *******************************/ 139 140%! portray_attvar(@Var) 141% 142% Called from write_term/3 using the option attributes(portray) or 143% when the prolog flag write_attributes equals portray. Its task 144% is the write the attributes in a human readable format. 145 146:- public 147 portray_attvar/1. 148 149portray_attvar(Var) :- 150 write('{'), 151 get_attrs(Var, Attr), 152 portray_attrs(Attr, Var), 153 write('}'). 154 155portray_attrs([], _). 156portray_attrs(att(Name, Value, Rest), Var) :- 157 portray_attr(Name, Value, Var), 158 ( Rest == [] 159 -> true 160 ; write(', '), 161 portray_attrs(Rest, Var) 162 ). 163 164portray_attr(freeze, Goal, Var) :- 165 !, 166 format('freeze(~w, ~W)', [ Var, Goal, 167 [ portray(true), 168 quoted(true), 169 attributes(ignore) 170 ] 171 ]). 172portray_attr(Name, Value, Var) :- 173 G = Name:attr_portray_hook(Value, Var), 174 ( '$c_current_predicate'(_, G), 175 176 -> true 177 ; format('~w = ...', [Name]) 178 ). 179 180 181 /******************************* 182 * CALL RESIDUE * 183 *******************************/ 184 185%! call_residue_vars(:Goal, -Vars) 186% 187% If Goal is true, Vars is the set of residual attributed 188% variables created by Goal. Goal is called as in call/1. This 189% predicate is for debugging constraint programs. Assume a 190% constraint program that creates conflicting constraints on a 191% variable that is not part of the result variables of Goal. If 192% the solver is powerful enough it will detect the conflict and 193% fail. If the solver is too weak however it will succeed and 194% residual attributed variables holding the conflicting constraint 195% form a witness of this problem. 196 197:- meta_predicate 198 call_residue_vars(, ). 199 200call_residue_vars(Goal, Vars) :- 201 prolog_current_choice(Chp), 202 setup_call_cleanup( 203 '$call_residue_vars_start', 204 run_crv(Goal, Chp, Vars, Det), 205 '$call_residue_vars_end'), 206 ( Det == true 207 -> ! 208 ; true 209 ). 210call_residue_vars(_, _) :- 211 fail. 212 213run_crv(Goal, Chp, Vars, Det) :- 214 call(Goal), 215 deterministic(Det), 216 '$attvars_after_choicepoint'(Chp, Vars). 217 218%! copy_term(+Term, -Copy, -Gs) is det. 219% 220% Creates a regular term Copy as a copy of Term (without any 221% attributes), and a list Gs of goals that when executed reinstate 222% all attributes onto Copy. The nonterminal attribute_goals//1, as 223% defined in the modules the attributes stem from, is used to 224% convert attributes to lists of goals. 225 226copy_term(Term, Copy, Gs) :- 227 term_attvars(Term, Vs), 228 ( Vs == [] 229 -> Gs = [], 230 copy_term(Term, Copy) 231 ; findall(Term-Gs, 232 ( phrase(attvars_residuals(Vs), Gs), 233 delete_attributes(Term) 234 ), 235 [Copy-Gs]) 236 ). 237 238attvars_residuals([]) --> []. 239attvars_residuals([V|Vs]) --> 240 ( { get_attrs(V, As) } 241 -> attvar_residuals(As, V) 242 ; [] 243 ), 244 attvars_residuals(Vs). 245 246attvar_residuals([], _) --> []. 247attvar_residuals(att(Module,Value,As), V) --> 248 ( { nonvar(V) } 249 -> % a previous projection predicate could have instantiated 250 % this variable, for example, to avoid redundant goals 251 [] 252 ; ( { Module == freeze } 253 -> frozen_residuals(Value, V) 254 ; { current_predicate(Module:attribute_goals//1), 255 phrase(Module:attribute_goals(V), Goals) 256 } 257 -> list(Goals) 258 ; [put_attr(V, Module, Value)] 259 ) 260 ), 261 attvar_residuals(As, V). 262 263list([]) --> []. 264list([L|Ls]) --> [L], list(Ls). 265 266delete_attributes(Term) :- 267 term_attvars(Term, Vs), 268 delete_attributes_(Vs). 269 270delete_attributes_([]). 271delete_attributes_([V|Vs]) :- 272 del_attrs(V), 273 delete_attributes_(Vs). 274 275 276%! frozen_residuals(+FreezeAttr, +Var)// is det. 277% 278% Instantiate a freeze goal for each member of the $and 279% conjunction. Note that we cannot map this into a conjunction 280% because freeze(X, a), freeze(X, !) would create freeze(X, 281% (a,!)), which is fundamentally different. We could create 282% freeze(X, (call(a), call(!))) or preform a more eleborate 283% analysis to validate the semantics are not changed. 284 285frozen_residuals('$and'(X,Y), V) --> 286 !, 287 frozen_residuals(X, V), 288 frozen_residuals(Y, V). 289frozen_residuals(X, V) --> 290 [ freeze(V, X) ].