Files
mercury/compiler/ml_code_gen.m
Zoltan Somogyi 8a28e40c9b Add the predicates sorry, unexpected and expect to library/error.m.
Estimated hours taken: 2
Branches: main

Add the predicates sorry, unexpected and expect to library/error.m.

compiler/compiler_util.m:
library/error.m:
	Move the predicates sorry, unexpected and expect from compiler_util
	to error.

	Put the predicates in error.m into the same order as their
	declarations.

compiler/*.m:
	Change imports as needed.

compiler/lp.m:
compiler/lp_rational.m:
	Change imports as needed, and some minor cleanups.

deep_profiler/*.m:
	Switch to using the new library predicates, instead of calling error
	directly. Some other minor cleanups.

NEWS:
	Mention the new predicates in the standard library.
2010-12-15 06:30:36 +00:00

1196 lines
44 KiB
Mathematica

%-----------------------------------------------------------------------------%
% vim: ft=mercury ts=4 sw=4 et
%-----------------------------------------------------------------------------%
% Copyright (C) 1999-2010 The University of Melbourne.
% This file may only be copied under the terms of the GNU General
% Public License - see the file COPYING in the Mercury distribution.
%-----------------------------------------------------------------------------%
%
% File: ml_code_gen.m.
% Main author: fjh.
%
% MLDS code generation -- convert from HLDS to MLDS.
%
% This module is an alternative to the original code generator.
% The original code generator compiles from HLDS to LLDS, generating
% very low-level code. This code generator instead compiles to MLDS,
% generating much higher-level code than the original code generator.
%
% One of the aims of the MLDS is to be able to generated human-readable
% code in languages like C or Java. This means that unlike the LLDS back-end,
% we do not want to rely on macros or conditional compilation. If the
% final code is going to depend on the setting of some compilation option,
% our philosophy is to reflect that change in the generated MLDS and C code
% where possible, rather than generating C code which calls macros that do
% different things in different grades. This is important both for
% readability of the generated code, and to make sure that we can easily
% adapt the MLDS code generator to target languages like Java that don't
% support macros or conditional compilation.
%
% A big challenge in generating MLDS code is handling nondeterminism.
% For nondeterministic procedures, we generate code using an explicit
% continuation passing style. Each nondeterministic procedures gets
% translated into a function which takes an extra parameter which is a
% function pointer that points to the success continuation. On success,
% the function calls its success continuation, and on failure it returns.
%
% To keep things easy, this pass generates code which may contain nested
% functions; if the target language doesn't support nested functions (or
% doesn't support them _efficiently_) then a later MLDS->MLDS simplification
% pass will convert it to a form that does not use nested functions.
%
% Note that when we take the address of a nested function, we only ever
% do two things with it: pass it as a continuation argument, or call it.
% The continuations are never returned and never stored inside heap objects
% or global variables. These conditions are sufficient to ensure that
% we never keep the address of a nested function after the containing
% functions has returned, so we won't get any dangling continuations.
%
%-----------------------------------------------------------------------------%
% CODE GENERATION SUMMARY
%-----------------------------------------------------------------------------%
%
% In each procedure, we declare a local variable `MR_bool succeeded'.
% This is used to hold the success status of semidet sub-goals.
% Note that the comments below show local declarations for the
% `succeeded' variable in all the places where they would be
% needed if we were generating them locally, but currently
% we actually just generate a single `succeeded' variable for
% each procedure.
%
% The calling convention for sub-goals is as follows.
%
% model_det goal:
% On success, fall through.
% (May clobber `succeeded'.)
% model_semi goal:
% On success, set `succeeded' to MR_TRUE and fall through.
% On failure, set `succeeded' to MR_FALSE and fall through.
% multi/nondet goal:
% On success, call the current success continuation.
% On failure, fall through.
% (May clobber `succeeded' in either case.)
%
% In comments, we use the following notation to distinguish between
% these three.
%
% model_det goal:
% <do Goal>
% This means execute Goal (which must be model_det).
% model_semi goal:
% <succeeded = Goal>
% This means execute Goal, and set `succeeded' to
% MR_TRUE if the goal succeeds and MR_FALSE if it fails.
% model_non goal:
% <Goal && CONT()>
% This means execute Goal, calling the success
% continuation function CONT() if it succeeds,
% and falling through if it fails.
%
% The notation
%
% [situation]:
% <[construct]>
% ===>
% [code]
%
% means that in the situation described by [situation],
% for the the specified [construct] we will generate the specified [code].
%
% There is one other important thing which can be considered part of the
% calling convention for the code that we generate for each goal.
% If static ground term optimization is enabled, then for the terms
% marked as static by mark_static_terms.m, we will generate static consts.
% These static consts can refer to other static consts defined earlier.
% We need to be careful about the scopes of variables to ensure that
% for any term that mark_static_terms.m marks as static, the C constants
% representing the arguments of that term are in scope at the point
% where that term is constructed. Basically this means that
% all the static consts generated inside a goal must be hoist out to
% the top level scope for that goal, except for goal types where
% goal_expr_mark_static_terms (in mark_static_terms.m) returns the
% same static_info unchanged, i.e. branched goals and negations.
%
% Handling static constants also requires that the calls to ml_gen_goal
% for each subgoal must be done in the right order, so that the
% const_num_map in the ml_gen_info holds the right sequence numbers
% for the constants in scope.
%
%-----------------------------------------------------------------------------%
%
% Code for wrapping goals
%
% If a model_foo goal occurs in a model_bar context, where foo != bar,
% then we need to modify the code that we emit for the goal so that
% it conforms to the calling convenion expected for model_bar.
%
% det goal in semidet context:
% <succeeded = Goal>
% ===>
% <do Goal>
% succeeded = MR_TRUE;
%
% det goal in nondet context:
% <Goal && SUCCEED()>
% ===>
% <do Goal>
% SUCCEED();
%
% semi goal in nondet context:
% <Goal && SUCCEED()>
% ===>
% MR_bool succeeded;
%
% <succeeded = Goal>
% if (succeeded) SUCCEED();
%
%-----------------------------------------------------------------------------%
%
% Code for empty conjunctions (`true')
%
%
% model_det goal:
% <do true>
% ===>
% /* fall through */
%
% model_semi goal:
% <succeeded = true>
% ===>
% succceeded = MR_TRUE;
%
% model_non goal
% <true && CONT()>
% ===>
% CONT();
%
%-----------------------------------------------------------------------------%
%
% Code for non-empty conjunctions
%
%
% We need to handle the case where the first goal cannot succeed
% specially:
%
% at_most_zero Goal:
% <Goal, Goals>
% ===>
% <Goal>
%
% The remaining cases for conjunction all assume that the first
% goal's determinism is not `erroneous' or `failure'.
%
% If the first goal is model_det, it is straight-forward:
%
% model_det Goal:
% <Goal, Goals>
% ===>
% <do Goal>
% <Goals>
%
% If the first goal is model_semidet, then there are two cases:
% if the conj as a whole is semidet, things are simple, and
% if the conj as a whole is model_non, then we do the same as
% for the semidet case, except that we also (ought to) declare
% a local `succeeded' variable.
%
% model_semi Goal in model_semi conj:
% <succeeded = (Goal, Goals)>
% ===>
% <succeeded = Goal>;
% if (succeeded) {
% <Goals>;
% }
%
% model_semi Goal in model_non conj:
% <Goal && Goals>
% ===>
% MR_bool succeeded;
%
% <succeeded = Goal>;
% if (succeeded) {
% <Goals>;
% }
%
% The actual code generation scheme we use is slightly different to that:
% we hoist any declarations generated for <Goals> to the outer scope,
% rather than keeping them inside the `if', so that they remain in scope
% for any later goals which follow this. This is needed for declarations
% of static consts.
%
% For model_non goals, there are a couple of different ways that we could
% generate code, depending on whether we are aiming to maximize readability,
% or whether we prefer to generate code that may be more efficient but is
% a little less readable. The more readable method puts the generated goals
% in the same order that they occur in the source code:
%
% model_non Goal (optimized for readability)
% <Goal, Goals>
% ===>
% entry_func() {
% <Goal && succ_func()>;
% }
% succ_func() {
% <Goals && SUCCEED()>;
% }
%
% entry_func();
%
% The more efficient method generates the goals in reverse order, so it's less
% readable, but it has fewer function calls and can make it easier for the C
% compiler to inline things:
%
% model_non Goal (optimized for efficiency):
% <Goal, Goals>
% ===>
% succ_func() {
% <Goals && SUCCEED()>;
% }
%
% <Goal && succ_func()>;
%
% The more efficient method is the one we actually use.
%
% Here's how those two methods look on longer conjunctions of nondet goals:
%
% model_non goals (optimized for readability):
% <Goal1, Goal2, Goal3, Goals>
% ===>
% label0_func() {
% <Goal1 && label1_func()>;
% }
% label1_func() {
% <Goal2 && label2_func()>;
% }
% label2_func() {
% <Goal3 && label3_func()>;
% }
% label3_func() {
% <Goals && SUCCEED()>;
% }
%
% label0_func();
%
% model_non goals (optimized for efficiency):
% <Goal1, Goal2, Goal3, Goals>
% ===>
% label1_func() {
% label2_func() {
% label3_func() {
% <Goals && SUCCEED()>;
% }
% <Goal3 && label3_func()>;
% }
% <Goal2 && label2_func()>;
% }
% <Goal1 && label1_func()>;
%
% Note that it might actually make more sense to generate conjunctions
% of nondet goals like this:
%
% model_non goals (optimized for efficiency, alternative version):
% <Goal1, Goal2, Goal3, Goals>
% ===>
% label3_func() {
% <Goals && SUCCEED()>;
% }
% label2_func() {
% <Goal3 && label3_func()>;
% }
% label1_func() {
% <Goal2 && label2_func()>;
% }
%
% <Goal1 && label1_func()>;
%
% This would avoid the undesirable deep nesting that we sometimes get with
% our current scheme. However, if we're eliminating nested functions, as is
% normally the case, then after the ml_elim_nested transformation all the
% functions and variables have been hoisted to the top level, so there is
% no difference between these two.
%
% As with semidet conjunctions, we hoist declarations out so that they remain
% in scope for any following goals. This is needed for declarations of static
% consts. However, we want to keep the declarations of non-static variables
% local, since accessing local variables is more efficient that accessing
% variables in the environment from a nested function. So we only hoist
% declarations of static constants.
%
%-----------------------------------------------------------------------------%
%
% Code for if-then-else
%
%
% model_det Cond:
% <(Cond -> Then ; Else)>
% ===>
% <Cond>
% <Then>
%
% model_semi Cond:
% <(Cond -> Then ; Else)>
% ===>
% MR_bool succeeded;
%
% <succeeded = Cond>
% if (succeeded) {
% <Then>
% } else {
% <Else>
% }
%
% XXX The following transformation does not do as good a job of GC as it could.
% Ideally we ought to ensure that stuff used only in the `Else' part will be
% reclaimed if a GC occurs during the `Then' part. But that is a bit tricky
% to achieve.
%
% model_non Cond:
% <(Cond -> Then ; Else)>
% ===>
% MR_bool cond_<N>;
%
% void then_func() {
% cond_<N> = MR_TRUE;
% <Then>
% }
%
% cond_<N> = MR_FALSE;
% <Cond && then_func()>
% if (!cond_<N>) {
% <Else>
% }
%
% except that we hoist any declarations generated for <Cond> to the top
% of the scope, so that they are in scope for the <Then> goal
% (this is needed for declarations of static consts).
%
%-----------------------------------------------------------------------------%
%
% Code for negation
%
%
% model_det negation
% <not(Goal)>
% ===>
% MR_bool succeeded;
% <succeeded = Goal>
% /* now ignore the value of succeeded,
% which we know will be MR_FALSE */
%
% model_semi negation, model_det Goal:
% <succeeded = not(Goal)>
% ===>
% <do Goal>
% succeeded = MR_FALSE;
%
% model_semi negation, model_semi Goal:
% <succeeded = not(Goal)>
% ===>
% <succeeded = Goal>
% succeeded = !succeeded;
%
%-----------------------------------------------------------------------------%
%
% This back-end is still not yet 100% complete.
%
% Done:
% - function prototypes
% - code generation for det, semidet, and nondet predicates/functions:
% - conjunctions
% - disjunctions
% - negation
% - if-then-else
% - predicate/function calls
% - higher-order calls
% - unifications
% - assignment
% - simple tests
% - constructions
% - deconstructions
% - switches
% - commits
% - `pragma c_code'
% - RTTI
% - high level data representation
% (i.e. generate MLDS type declarations for user-defined types)
% - support trailing
%
% TODO:
% - XXX define compare & unify preds for RTTI types
% - XXX need to generate correct layout information for closures
% so that tests/hard_coded/copy_pred works.
% - XXX fix ANSI/ISO C conformance of the generated code (i.e. port to lcc)
%
% UNIMPLEMENTED FEATURES:
% - test --det-copy-out
% - fix --gcc-nested-functions (need forward declarations for
% nested functions)
% - support debugging (with mdb)
% - support genuine parallel conjunction
% - support fact tables
% - support accurate GC
%
% POTENTIAL EFFICIENCY IMPROVEMENTS:
% - optimize unboxed float on DEC Alphas.
% - generate better code for switches:
% - optimize switches so that the recursive case comes first
% (see switch_gen.m).
% - apply the reverse tag test optimization
% for types with two functors (see unify_gen.m)
% - binary search switches
% - generate local declarations for the `succeeded' variable;
% this would help in nondet code, because it would avoid
% the need to access the outermost function's `succeeded'
% variable via the environment pointer
% (be careful about the interaction with setjmp(), though)
%
%-----------------------------------------------------------------------------%
:- module ml_backend.ml_code_gen.
:- interface.
:- import_module hlds.code_model.
:- import_module hlds.hlds_goal.
:- import_module ml_backend.mlds.
:- import_module ml_backend.ml_gen_info.
:- import_module parse_tree.prog_data.
:- import_module list.
%-----------------------------------------------------------------------------%
%-----------------------------------------------------------------------------%
% Generate MLDS code for the specified goal in the specified code model.
% Return the result as a single statement (which may be a block statement
% containing nested declarations).
%
:- pred ml_gen_goal_as_block(code_model::in, hlds_goal::in, statement::out,
ml_gen_info::in, ml_gen_info::out) is det.
% Generate MLDS code for the specified goal in the specified code model.
% Return the result as two lists, one containing the necessary declarations
% and the other containing the generated statements.
%
:- pred ml_gen_goal(code_model::in, hlds_goal::in,
list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
% Generate code for a goal that is one branch of a branched control
% structure. At the end of the branch, we need to forget what we learned
% during the branch about which variables are bound to constants,
% since those variables may not be bound to constants (at least not the
% same constants) in parallel branches, or in code after the branched
% control if control did not go through this branch.
%
:- pred ml_gen_goal_as_branch(code_model::in, hlds_goal::in,
list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
:- pred ml_gen_goal_as_branch_block(code_model::in, hlds_goal::in,
statement::out, ml_gen_info::in, ml_gen_info::out) is det.
% ml_gen_maybe_convert_goal_code_model(OuterCodeModel, InnerCodeModel,
% Context, Statements0, Statements, !Info):
%
% OuterCodeModel is the code model expected by the context in which a goal
% is called. InnerCodeModel is the code model which the goal actually has.
% This predicate converts the code generated for the goal using
% InnerCodeModel into code that uses the calling convention appropriate
% for OuterCodeModel.
%
:- pred ml_gen_maybe_convert_goal_code_model(code_model::in, code_model::in,
prog_context::in, list(statement)::in, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
% Generate declarations for a list of local variables.
%
:- pred ml_gen_local_var_decls(prog_varset::in, vartypes::in,
prog_context::in, prog_vars::in, list(mlds_defn)::out,
ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
%-----------------------------------------------------------------------------%
:- implementation.
:- import_module backend_libs.builtin_ops.
:- import_module backend_libs.c_util.
:- import_module backend_libs.foreign. % XXX needed for pragma foreign code
:- import_module check_hlds.mode_util.
:- import_module check_hlds.type_util.
:- import_module hlds.goal_form.
:- import_module hlds.hlds_module.
:- import_module hlds.hlds_pred.
:- import_module libs.globals.
:- import_module libs.options.
:- import_module ml_backend.ml_call_gen.
:- import_module ml_backend.ml_code_util.
:- import_module ml_backend.ml_commit_gen.
:- import_module ml_backend.ml_disj_gen.
:- import_module ml_backend.ml_foreign_proc_gen.
:- import_module ml_backend.ml_gen_info.
:- import_module ml_backend.ml_global_data.
:- import_module ml_backend.ml_switch_gen.
:- import_module ml_backend.ml_type_gen.
:- import_module ml_backend.ml_unify_gen.
:- import_module ml_backend.ml_util.
:- import_module parse_tree.builtin_lib_types.
:- import_module parse_tree.prog_type.
:- import_module bool.
:- import_module map.
:- import_module maybe.
:- import_module pair.
:- import_module require.
:- import_module set.
:- import_module string.
%-----------------------------------------------------------------------------%
%-----------------------------------------------------------------------------%
%
% Generate code for goals.
%
ml_gen_goal_as_branch(CodeModel, Goal, Decls, Statements, !Info) :-
ml_gen_info_get_const_var_map(!.Info, InitConstVarMap),
ml_gen_goal(CodeModel, Goal, Decls, Statements, !Info),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info).
% Generate MLDS code for the specified goal in the specified code model.
% Return the result as a single statement (which may be a block statement
% containing nested declarations).
%
ml_gen_goal_as_block(CodeModel, Goal, Statement, !Info) :-
ml_gen_goal(CodeModel, Goal, Decls, Statements, !Info),
Goal = hlds_goal(_, GoalInfo),
Context = goal_info_get_context(GoalInfo),
Statement = ml_gen_block(Decls, Statements, Context).
ml_gen_goal_as_branch_block(CodeModel, Goal, Statement, !Info) :-
ml_gen_info_get_const_var_map(!.Info, InitConstVarMap),
ml_gen_goal_as_block(CodeModel, Goal, Statement, !Info),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info).
% Generate MLDS code for the specified goal in the specified code model.
% Return the result as two lists, one containing the necessary declarations
% and the other containing the generated statements.
%
ml_gen_goal(CodeModel, Goal, Decls, Statements, !Info) :-
Goal = hlds_goal(GoalExpr, GoalInfo),
Context = goal_info_get_context(GoalInfo),
% Generate the local variables for this goal.
ml_gen_info_get_var_types(!.Info, VarTypes),
find_vars_to_declare(VarTypes, GoalExpr, GoalInfo, VarsToDeclare),
ml_gen_info_get_varset(!.Info, VarSet),
ml_gen_local_var_decls(VarSet, VarTypes, Context, VarsToDeclare, VarDecls,
!Info),
% Generate code for the goal in its own code model.
GoalCodeModel = goal_info_get_code_model(GoalInfo),
ml_gen_goal_expr(GoalExpr, GoalCodeModel, Context, GoalInfo,
GoalDecls, GoalStatements0, !Info),
% Add whatever wrapper is needed to convert the goal's code model
% to the desired code model.
ml_gen_maybe_convert_goal_code_model(CodeModel, GoalCodeModel, Context,
GoalStatements0, GoalStatements, !Info),
Decls = VarDecls ++ GoalDecls,
Statements = GoalStatements.
%-----------------------------------------------------------------------------%
% Generate MLDS code for the different kinds of HLDS goals.
%
:- pred ml_gen_goal_expr(hlds_goal_expr::in, code_model::in, prog_context::in,
hlds_goal_info::in, list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
ml_gen_goal_expr(GoalExpr, CodeModel, Context, GoalInfo, Decls, Statements,
!Info) :-
(
GoalExpr = unify(_LHS, _RHS, _Mode, Unification, _UnifyContext),
ml_gen_unification(Unification, CodeModel, Context, Statements, !Info),
Decls = []
;
GoalExpr = plain_call(PredId, ProcId, ArgVars, BuiltinState, _, _),
(
BuiltinState = not_builtin,
ml_gen_var_list(!.Info, ArgVars, ArgLvals),
ml_gen_info_get_varset(!.Info, VarSet),
ArgNames = ml_gen_var_names(VarSet, ArgVars),
ml_variable_types(!.Info, ArgVars, ActualArgTypes),
ml_gen_call(PredId, ProcId, ArgNames, ArgLvals, ActualArgTypes,
CodeModel, Context, no, Decls, Statements, !Info)
;
( BuiltinState = inline_builtin
; BuiltinState = out_of_line_builtin
),
ml_gen_builtin(PredId, ProcId, ArgVars, CodeModel, Context,
Decls, Statements, !Info)
)
;
GoalExpr = generic_call(GenericCall, Vars, Modes, Detism),
determinism_to_code_model(Detism, CallCodeModel),
expect(unify(CodeModel, CallCodeModel), this_file,
"ml_gen_generic_call: code model mismatch"),
ml_gen_generic_call(GenericCall, Vars, Modes, Detism, Context,
Decls, Statements, !Info)
;
GoalExpr = call_foreign_proc(Attributes, PredId, ProcId,
Args, ExtraArgs, MaybeTraceRuntimeCond, PragmaImpl),
PragmaImpl = fc_impl_ordinary(ForeignCode, MaybeContext),
(
MaybeContext = yes(ContextToUse)
;
MaybeContext = no,
ContextToUse = Context
),
(
MaybeTraceRuntimeCond = no,
ml_gen_ordinary_pragma_foreign_proc(CodeModel, Attributes,
PredId, ProcId, Args, ExtraArgs, ForeignCode,
ContextToUse, Decls, Statements, !Info)
;
MaybeTraceRuntimeCond = yes(TraceRuntimeCond),
ml_gen_trace_runtime_cond(TraceRuntimeCond, ContextToUse,
Decls, Statements, !Info)
)
;
GoalExpr = conj(_ConjType, Goals),
% XXX Currently we treat parallel conjunction the same as
% sequential conjunction -- parallelism is not yet implemented.
ml_gen_conj(Goals, CodeModel, Context, Decls, Statements, !Info)
;
GoalExpr = disj(Goals),
ml_gen_disj(Goals, GoalInfo, CodeModel, Context, Statements, !Info),
Decls = []
;
GoalExpr = switch(Var, CanFail, CasesList),
ml_gen_switch(Var, CanFail, CasesList, CodeModel, Context, GoalInfo,
Decls, Statements, !Info)
;
GoalExpr = if_then_else(_Vars, Cond, Then, Else),
ml_gen_ite(CodeModel, Cond, Then, Else, Context, Decls, Statements,
!Info)
;
GoalExpr = negation(SubGoal),
ml_gen_negation(SubGoal, CodeModel, Context, Decls, Statements, !Info)
;
GoalExpr = scope(Reason, SubGoal),
( Reason = from_ground_term(TermVar, from_ground_term_construct) ->
ml_gen_ground_term(TermVar, SubGoal, Statements, !Info),
Decls = []
;
ml_gen_commit(SubGoal, CodeModel, Context, Decls, Statements,
!Info)
)
;
GoalExpr = shorthand(_),
% these should have been expanded out by now
unexpected(this_file, "ml_gen_goal_expr: unexpected shorthand")
).
%-----------------------------------------------------------------------------%
% For any given goal, we need to declare any variables which are local
% to this goal (including its subgoals), but which are not local to
% a subgoal. If they're local to a subgoal, they will be declared when
% we generate code for that subgoal.
%
% We need to make sure that we declare any type_info or type_classinfo
% variables *before* any other variables, since the GC tracing code
% for the other variables may refer to the type_info variables, so they
% need to be in scope.
%
% However, in the common case that the number of variables to declare is
% zero or one, such reordering is guaranteed to be a no-op, so avoid the
% expense.
%
:- pred find_vars_to_declare(vartypes::in,
hlds_goal_expr::in, hlds_goal_info::in, list(prog_var)::out) is det.
find_vars_to_declare(VarTypes, GoalExpr, GoalInfo, VarsToDeclare) :-
goal_expr_find_subgoal_nonlocals(GoalExpr, SubGoalNonLocals),
NonLocals = goal_info_get_nonlocals(GoalInfo),
set.difference(SubGoalNonLocals, NonLocals, VarsToDeclareSet),
set.to_sorted_list(VarsToDeclareSet, VarsToDeclare0),
(
( VarsToDeclare0 = []
; VarsToDeclare0 = [_]
),
VarsToDeclare = VarsToDeclare0
;
VarsToDeclare0 = [_, _ | _],
VarsToDeclare = put_typeinfo_vars_first(VarsToDeclare0, VarTypes)
).
% The task of this predicate is to help compute the set of MLDS variables
% that should be declared at the scope of GoalExpr. This should be the
% set of variables that
%
% - do not occur outside GoalExpr, since if they did, they would have to be
% declared in a larger scope containing GoalExpr; and
%
% - need to be declared at the scope of GoalExpr, since they cannot be
% declared in a scope inside GoalExpr.
%
% Our caller will take care of the first point by deleting the nonlocals
% set of GoalExpr from the SubGoalNonLocals we return, which means that
% we can include any variable from GoalExpr's nonlocals set in
% SubGoalNonLocals without affecting the final outcome.
%
% If GoalExpr is a compound goal, a variable that occurs in GoalExpr
% can be declared in a smaller scope that GoalExpr if it occurs inside
% a single one of GoalExpr's subgoals. In this case, we therefore return
% the union of the nonlocals sets of GoalExpr's direct subgoals.
%
% If GoalExpr is an atomic goal, there is no smaller scope, but we do have
% to declare at GoalExpr's scope any MLDS variables that GoalExpr refers to
% but are not visible GoalExpr. This can happen e.g. with ignored output
% arguments from calls and unifications.
%
:- pred goal_expr_find_subgoal_nonlocals(hlds_goal_expr::in,
set(prog_var)::out) is det.
goal_expr_find_subgoal_nonlocals(GoalExpr, SubGoalNonLocals) :-
(
GoalExpr = unify(_LHS, _RHS, _Mode, Unification, _UnifyContext),
(
Unification = construct(LHSVar, _ConsId, ArgVars, _ArgModes,
_HowToConstruct, _Unique, _SubInfo),
% _HowToConstruct can contain a var specifying to a cell to reuse
% or a region to construct the term in, but both of those require
% that variable to be nonlocal to GoalExpr, which means that they
% would be subtracted from SubGoalNonLocals by our caller anyway.
SubGoalNonLocals = set.list_to_set([LHSVar | ArgVars])
;
Unification = deconstruct(LHSVar, _ConsId, ArgVars, _ArgModes,
_CanFail, _CanCGC),
SubGoalNonLocals = set.list_to_set([LHSVar | ArgVars])
;
Unification = assign(LHSVar, RHSVar),
SubGoalNonLocals = set.list_to_set([LHSVar, RHSVar])
;
Unification = simple_test(LHSVar, RHSVar),
SubGoalNonLocals = set.list_to_set([LHSVar, RHSVar])
;
Unification = complicated_unify(_, _, _),
unexpected(this_file, "goal_expr_find_subgoal_nonlocals")
)
;
GoalExpr = plain_call(_PredId, _ProcId, ArgVars, _Builtin,
_Unify_context, _SymName),
SubGoalNonLocals = set.list_to_set(ArgVars)
;
GoalExpr = generic_call(GenericCall, ArgVars, _Modes, _Detism),
(
GenericCall = higher_order(HOVar, _Purity, _Kind, _Arity),
SubGoalNonLocals = set.list_to_set([HOVar | ArgVars])
;
GenericCall = class_method(MethodVar, _MethodNum, _MethodClassId,
_Name),
SubGoalNonLocals = set.list_to_set([MethodVar | ArgVars])
;
GenericCall = event_call(_Eventname),
SubGoalNonLocals = set.list_to_set(ArgVars)
;
GenericCall = cast(_CastKind),
SubGoalNonLocals = set.list_to_set(ArgVars)
)
;
GoalExpr = call_foreign_proc(_Attr, _PredId, _ProcId, Args, ExtraArgs,
_TraceCond, _Impl),
ArgVars = list.map(foreign_arg_var, Args),
ExtraVars = list.map(foreign_arg_var, ExtraArgs),
SubGoalNonLocals = set.list_to_set(ExtraVars ++ ArgVars)
;
( GoalExpr = negation(SubGoal)
; GoalExpr = scope(_Reason, SubGoal)
),
% If _Reason = from_ground_term, the TermVar in it is guaranteed by
% construction to be nonlocal, so there is no need to add it
% separately.
% If _Reason = exist_quant(Vars), the variables in Vars are ignored by
% the code generator.
SubGoalNonLocals = goal_get_nonlocals(SubGoal)
;
( GoalExpr = conj(_, SubGoals)
; GoalExpr = disj(SubGoals)
),
goals_find_subgoal_nonlocals(SubGoals, set.init, SubGoalNonLocals)
;
GoalExpr = if_then_else(_Vars, Cond, Then, Else),
% The value of _Vars is not guaranteed to contain the set of variables
% shared between only Cond and Then.
goals_find_subgoal_nonlocals([Cond, Then, Else],
set.init, SubGoalNonLocals)
;
GoalExpr = switch(_Var, _CanFail, Cases),
% _Var must be nonlocal; if it weren't, there would have been a mode
% error (no producer for _Var before a consumer, namely this switch).
cases_find_subgoal_nonlocals(Cases, set.init, SubGoalNonLocals)
;
GoalExpr = shorthand(_),
unexpected(this_file, "goal_expr_find_subgoal_nonlocals: shorthand")
).
:- pred goals_find_subgoal_nonlocals(list(hlds_goal)::in,
set(prog_var)::in, set(prog_var)::out) is det.
goals_find_subgoal_nonlocals([], !SubGoalNonLocals).
goals_find_subgoal_nonlocals([SubGoal | SubGoals], !SubGoalNonLocals) :-
NonLocals = goal_get_nonlocals(SubGoal),
set.union(!.SubGoalNonLocals, NonLocals, !:SubGoalNonLocals),
goals_find_subgoal_nonlocals(SubGoals, !SubGoalNonLocals).
:- pred cases_find_subgoal_nonlocals(list(case)::in,
set(prog_var)::in, set(prog_var)::out) is det.
cases_find_subgoal_nonlocals([], !SubGoalNonLocals).
cases_find_subgoal_nonlocals([Case | Cases], !SubGoalNonLocals) :-
Case = case(_, _, SubGoal),
NonLocals = goal_get_nonlocals(SubGoal),
set.union(!.SubGoalNonLocals, NonLocals, !:SubGoalNonLocals),
cases_find_subgoal_nonlocals(Cases, !SubGoalNonLocals).
%-----------------------------------------------------------------------------%
ml_gen_maybe_convert_goal_code_model(OuterCodeModel, InnerCodeModel, Context,
!Statements, !Info) :-
(
% If the inner and outer code models are equal, we don't need to do
% anything.
%
(
OuterCodeModel = model_det,
InnerCodeModel = model_det
;
OuterCodeModel = model_semi,
InnerCodeModel = model_semi
;
OuterCodeModel = model_non,
InnerCodeModel = model_non
)
;
% If the inner code model is less precise than the outer code model,
% then that is either a determinism error, or a situation in which
% simplify.m is supposed to wrap the goal inside a `some' to indicate
% that a commit is needed.
(
OuterCodeModel = model_det,
InnerCodeModel = model_semi,
unexpected(this_file,
"ml_gen_maybe_convert_goal_code_model: semi in det")
;
OuterCodeModel = model_det,
InnerCodeModel = model_non,
unexpected(this_file,
"ml_gen_maybe_convert_goal_code_model: nondet in det")
;
OuterCodeModel = model_semi,
InnerCodeModel = model_non,
unexpected(this_file,
"ml_gen_maybe_convert_goal_code_model: nondet in semi")
)
;
% If the inner code model is more precise than the outer code model,
% then we need to append some statements to convert the calling
% convention for the inner code model to that of the outer code model.
(
OuterCodeModel = model_semi,
InnerCodeModel = model_det,
% det goal in semidet context:
% <succeeded = Goal>
% ===>
% <do Goal>
% succeeded = MR_TRUE
ml_gen_set_success(!.Info, ml_const(mlconst_true), Context,
SetSuccessTrue),
!:Statements = !.Statements ++ [SetSuccessTrue]
;
OuterCodeModel = model_non,
InnerCodeModel = model_det,
% det goal in nondet context:
% <Goal && SUCCEED()>
% ===>
% <do Goal>
% SUCCEED()
ml_gen_call_current_success_cont(Context, CallCont, !Info),
!:Statements = !.Statements ++ [CallCont]
;
OuterCodeModel = model_non,
InnerCodeModel = model_semi,
% semi goal in nondet context:
% <Goal && SUCCEED()>
% ===>
% MR_bool succeeded;
%
% <succeeded = Goal>
% if (succeeded) SUCCEED()
ml_gen_test_success(!.Info, Succeeded),
ml_gen_call_current_success_cont(Context, CallCont, !Info),
IfStmt = ml_stmt_if_then_else(Succeeded, CallCont, no),
IfStatement = statement(IfStmt, mlds_make_context(Context)),
!:Statements = !.Statements ++ [IfStatement]
)
).
%-----------------------------------------------------------------------------%
ml_gen_local_var_decls(_VarSet, _VarTypes, _Context, [], [], !Info).
ml_gen_local_var_decls(VarSet, VarTypes, Context, [Var | Vars], Defns,
!Info) :-
map.lookup(VarTypes, Var, Type),
ml_gen_info_get_module_info(!.Info, ModuleInfo),
IsDummy = check_dummy_type(ModuleInfo, Type),
(
IsDummy = is_dummy_type,
% No declaration needed for this variable.
ml_gen_local_var_decls(VarSet, VarTypes, Context, Vars, Defns, !Info)
;
IsDummy = is_not_dummy_type,
VarName = ml_gen_var_name(VarSet, Var),
ml_gen_var_decl(VarName, Type, Context, Defn, !Info),
ml_gen_local_var_decls(VarSet, VarTypes, Context, Vars, Defns0, !Info),
Defns = [Defn | Defns0]
).
%-----------------------------------------------------------------------------%
%
% Code for if-then-else.
%
:- pred ml_gen_ite(code_model::in, hlds_goal::in, hlds_goal::in, hlds_goal::in,
prog_context::in, list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
ml_gen_ite(CodeModel, Cond, Then, Else, Context, Decls, Statements, !Info) :-
Cond = hlds_goal(_, CondGoalInfo),
CondCodeModel = goal_info_get_code_model(CondGoalInfo),
(
% model_det Cond:
% <(Cond -> Then ; Else)>
% ===>
% <Cond>
% <Then>
CondCodeModel = model_det,
ml_gen_goal_as_block(model_det, Cond, CondStatement, !Info),
ml_gen_goal_as_block(CodeModel, Then, ThenStatement, !Info),
Decls = [],
Statements = [CondStatement, ThenStatement]
;
% model_semi cond:
% <(Cond -> Then ; Else)>
% ===>
% MR_bool succeeded;
%
% <succeeded = Cond>
% if (succeeded) {
% <Then>
% } else {
% <Else>
% }
CondCodeModel = model_semi,
ml_gen_info_get_const_var_map(!.Info, InitConstVarMap),
ml_gen_goal(model_semi, Cond, CondDecls, CondStatements, !Info),
ml_gen_test_success(!.Info, Succeeded),
ml_gen_goal_as_block(CodeModel, Then, ThenStatement, !Info),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info),
ml_gen_goal_as_block(CodeModel, Else, ElseStatement, !Info),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info),
IfStmt = ml_stmt_if_then_else(Succeeded, ThenStatement,
yes(ElseStatement)),
IfStatement = statement(IfStmt, mlds_make_context(Context)),
Decls = CondDecls,
Statements = CondStatements ++ [IfStatement]
;
% XXX The following transformation does not do as good a job of GC
% as it could. Ideally we ought to ensure that stuff used only
% in the `Else' part will be reclaimed if a GC occurs during the `Then'
% part. But that is a bit tricky to achieve.
%
% model_non cond:
% <(Cond -> Then ; Else)>
% ===>
% MR_bool cond_<N>;
%
% void then_func() {
% cond_<N> = MR_TRUE;
% <Then>
% }
%
% cond_<N> = MR_FALSE;
% <Cond && then_func()>
% if (!cond_<N>) {
% <Else>
% }
%
% except that we hoist any declarations generated for <Cond> to the top
% of the scope, so that they are in scope for the <Then> goal (this
% is needed for declarations of static consts)
CondCodeModel = model_non,
ml_gen_info_get_const_var_map(!.Info, InitConstVarMap),
% Generate the `cond_<N>' var and the code to initialize it to false.
ml_gen_info_new_cond_var(CondVar, !Info),
MLDS_Context = mlds_make_context(Context),
CondVarDecl = ml_gen_cond_var_decl(CondVar, MLDS_Context),
ml_gen_set_cond_var(!.Info, CondVar, ml_const(mlconst_false), Context,
SetCondFalse),
% Allocate a name for the `then_func'.
ml_gen_new_func_label(no, ThenFuncLabel, ThenFuncLabelRval, !Info),
% Generate <Cond && then_func()>.
ml_get_env_ptr(!.Info, EnvPtrRval),
SuccessCont = success_cont(ThenFuncLabelRval, EnvPtrRval, [], []),
ml_gen_info_push_success_cont(SuccessCont, !Info),
ml_gen_goal(model_non, Cond, CondDecls, CondStatements, !Info),
ml_gen_info_pop_success_cont(!Info),
% Generate the `then_func'.
% push nesting level
Then = hlds_goal(_, ThenGoalInfo),
ThenContext = goal_info_get_context(ThenGoalInfo),
ml_gen_set_cond_var(!.Info, CondVar, ml_const(mlconst_true),
ThenContext, SetCondTrue),
ml_gen_goal_as_block(CodeModel, Then, ThenStatement, !Info),
ThenFuncBody = statement(
ml_stmt_block([], [SetCondTrue, ThenStatement]),
mlds_make_context(ThenContext)),
% pop nesting level
ml_gen_nondet_label_func(!.Info, ThenFuncLabel, ThenContext,
ThenFuncBody, ThenFunc),
% Generate `if (!cond_<N>) { <Else> }'.
ml_gen_test_cond_var(!.Info, CondVar, CondSucceeded),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info),
ml_gen_goal_as_block(CodeModel, Else, ElseStatement, !Info),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info),
IfStmt = ml_stmt_if_then_else(
ml_unop(std_unop(logical_not), CondSucceeded),
ElseStatement, no),
IfStatement = statement(IfStmt, MLDS_Context),
% Package it all up in the right order.
Decls = [CondVarDecl | CondDecls] ++ [ThenFunc],
Statements = [SetCondFalse | CondStatements] ++ [IfStatement]
).
%-----------------------------------------------------------------------------%
%
% Code for negation.
%
:- pred ml_gen_negation(hlds_goal::in, code_model::in, prog_context::in,
list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
ml_gen_negation(Cond, CodeModel, Context, Decls, Statements, !Info) :-
Cond = hlds_goal(_, CondGoalInfo),
CondCodeModel = goal_info_get_code_model(CondGoalInfo),
(
% model_det negation:
% <not(Goal)>
% ===>
% {
% MR_bool succeeded;
% <succeeded = Goal>
% /* now ignore the value of succeeded,
% which we know will be MR_FALSE */
% }
CodeModel = model_det,
ml_gen_goal_as_branch(model_semi, Cond, Decls, Statements, !Info)
;
% model_semi negation, model_det goal:
% <succeeded = not(Goal)>
% ===>
% <do Goal>
% succeeded = MR_FALSE;
CodeModel = model_semi, CondCodeModel = model_det,
ml_gen_goal_as_branch(model_det, Cond, CondDecls, CondStatements,
!Info),
ml_gen_set_success(!.Info, ml_const(mlconst_false), Context,
SetSuccessFalse),
Decls = CondDecls,
Statements = CondStatements ++ [SetSuccessFalse]
;
% model_semi negation, model_semi goal:
% <succeeded = not(Goal)>
% ===>
% <succeeded = Goal>
% succeeded = !succeeded;
CodeModel = model_semi, CondCodeModel = model_semi,
ml_gen_goal_as_branch(model_semi, Cond, CondDecls, CondStatements,
!Info),
ml_gen_test_success(!.Info, Succeeded),
ml_gen_set_success(!.Info, ml_unop(std_unop(logical_not), Succeeded),
Context, InvertSuccess),
Decls = CondDecls,
Statements = CondStatements ++ [InvertSuccess]
;
CodeModel = model_semi, CondCodeModel = model_non,
unexpected(this_file, "ml_gen_negation: nondet cond")
;
CodeModel = model_non,
unexpected(this_file, "ml_gen_negation: nondet negation")
).
%-----------------------------------------------------------------------------%
%
% Code for conjunctions.
%
:- pred ml_gen_conj(hlds_goals::in, code_model::in, prog_context::in,
list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
ml_gen_conj(Conjuncts, CodeModel, Context, Decls, Statements, !Info) :-
(
Conjuncts = [],
ml_gen_success(CodeModel, Context, Statements, !Info),
Decls = []
;
Conjuncts = [SingleGoal],
ml_gen_goal(CodeModel, SingleGoal, Decls, Statements, !Info)
;
Conjuncts = [First | Rest],
Rest = [_ | _],
First = hlds_goal(_, FirstGoalInfo),
FirstDeterminism = goal_info_get_determinism(FirstGoalInfo),
( determinism_components(FirstDeterminism, _, at_most_zero) ->
% the `Rest' code is unreachable
ml_gen_goal(CodeModel, First, Decls, Statements, !Info)
;
determinism_to_code_model(FirstDeterminism, FirstCodeModel),
DoGenFirst = ml_gen_goal(FirstCodeModel, First),
DoGenRest = ml_gen_conj(Rest, CodeModel, Context),
ml_combine_conj(FirstCodeModel, Context, DoGenFirst, DoGenRest,
Decls, Statements, !Info)
)
).
%-----------------------------------------------------------------------------%
:- func this_file = string.
this_file = "ml_code_gen.m".
%-----------------------------------------------------------------------------%
:- end_module ml_code_gen.
%-----------------------------------------------------------------------------%