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295415090e79c32f73f83bd8b60bb32198d87206
mercury/compiler/ml_code_util.m
Zoltan Somogyi 295415090e Convert almost all remaining modules in the compiler to use 
Estimated hours taken: 6
Branches: main

compiler/*.m:
	Convert almost all remaining modules in the compiler to use
	"$module, $pred" instead of "this_file" in error messages.

	In a few cases, the old error message was misleading, since it
	contained an incorrect, out-of-date or cut-and-pasted predicate name.

tests/invalid/unresolved_overloading.err_exp:
	Update an expected output containing an updated error message.
2011-05-23 05:08:24 +00:00

2133 lines
82 KiB
Mathematica
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%-----------------------------------------------------------------------------%
% vim: ft=mercury ts=4 sw=4 et
%-----------------------------------------------------------------------------%
% Copyright (C) 1999-2011 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_util.m.
% Main author: fjh.
%
% This module is part of the MLDS code generator; it contains utility
% predicates.
%
%-----------------------------------------------------------------------------%
:- module ml_backend.ml_code_util.
:- interface.
:- import_module backend_libs.builtin_ops.
:- import_module hlds.code_model.
:- import_module hlds.hlds_goal.
:- import_module hlds.hlds_module.
:- import_module hlds.hlds_pred.
:- import_module hlds.hlds_rtti.
:- import_module libs.globals.
:- import_module mdbcomp.prim_data.
:- import_module ml_backend.ml_gen_info.
:- import_module ml_backend.ml_global_data.
:- import_module ml_backend.mlds.
:- import_module parse_tree.prog_data.
:- import_module bool.
:- import_module list.
:- import_module maybe.
%-----------------------------------------------------------------------------%
%
% Various utility routines used for MLDS code generation.
%
% Generate an MLDS assignment statement.
%
:- func ml_gen_assign(mlds_lval, mlds_rval, prog_context) = statement.
% Append an appropriate `return' statement for the given code_model
% and returning the given lvals, if needed.
%
:- pred ml_append_return_statement(ml_gen_info::in, code_model::in,
list(mlds_lval)::in, prog_context::in, list(statement)::in,
list(statement)::out) is det.
% Generate a block statement, i.e. `{ <Decls>; <Statements>; }'.
% But if the block consists only of a single statement with no
% declarations, then just return that statement.
%
:- func ml_gen_block(list(mlds_defn), list(statement), prog_context)
= statement.
:- func ml_gen_block_mlds(list(mlds_defn), list(statement), mlds_context)
= statement.
:- type gen_pred == pred(list(mlds_defn), list(statement),
ml_gen_info, ml_gen_info).
:- inst gen_pred == (pred(out, out, in, out) is det).
% Given closures to generate code for two conjuncts, generate code
% for their conjunction.
%
:- pred ml_combine_conj(code_model::in, prog_context::in,
gen_pred::in(gen_pred), gen_pred::in(gen_pred),
list(mlds_defn)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
% Given a function label and the statement which will comprise
% the function body for that function, generate an mlds_defn
% which defines that function.
%
:- pred ml_gen_nondet_label_func(ml_gen_info::in, ml_label_func::in,
prog_context::in, statement::in, mlds_defn::out) is det.
% Given a function label, the function parameters, and the statement
% which will comprise the function body for that function,
% generate an mlds_defn which defines that function.
%
:- pred ml_gen_label_func(ml_gen_info::in, ml_label_func::in,
mlds_func_params::in, prog_context::in, statement::in,
mlds_defn::out) is det.
% Test to see if the procedure is a model_det function whose function
% result has an output mode (whose type is not a dummy argument type
% like io.state), and if so, bind RetVar to the procedure's return value.
% These procedures need to handled specially: for such functions,
% we map the Mercury function result to an MLDS return value.
%
:- pred ml_is_output_det_function(module_info::in, pred_id::in, proc_id::in,
prog_var::out) is semidet.
%-----------------------------------------------------------------------------%
%
% Routines for generating expressions.
%
% conjunction: ml_gen_and(X,Y) = binop((and), X, Y),
% except that it does some constant folding on the result.
%
:- func ml_gen_and(mlds_rval, mlds_rval) = mlds_rval.
% negation: ml_gen_not(X) = unop(std_unop(not), X),
:- func ml_gen_not(mlds_rval) = mlds_rval.
%-----------------------------------------------------------------------------%
%
% Routines for generating types.
%
% Convert a Mercury type to an MLDS type.
%
:- pred ml_gen_type(ml_gen_info::in, mer_type::in, mlds_type::out) is det.
% Convert the element type for an array_index operator to an MLDS type.
%
:- func ml_gen_array_elem_type(array_elem_type) = mlds_type.
% Return the MLDS type corresponding to a Mercury string type.
%
:- func ml_string_type = mlds_type.
% Return the MLDS type corresponding to a Mercury int type.
%
:- func ml_int_type = mlds_type.
% Return the MLDS type corresponding to a Mercury char type.
%
:- func ml_char_type = mlds_type.
% Allocate some fresh type variables, with kind `star', to use as
% the Mercury types of boxed objects (e.g. to get the argument types
% for tuple constructors or closure constructors). Note that this
% should only be used in cases where the tvarset doesn't matter.
%
:- func ml_make_boxed_types(arity) = list(mer_type).
% Return the MLDS type corresponding to the `jmercury.runtime.MercuryType'
% interface.
%
:- func ml_java_mercury_type_interface = mlds_type.
% Return the MLDS type corresponding to the `jmercury.runtime.MercuryEnum'
% class.
%
:- func ml_java_mercury_enum_class = mlds_type.
%-----------------------------------------------------------------------------%
%
% Routines for generating function declarations (i.e. mlds_func_params).
%
% Note that when generating function *definitions*, the versions that take
% an ml_gen_info pair should be used, since those are the only ones that will
% generate the correct GC tracing code for the parameters.
% Generate the function prototype for a given procedure.
%
:- func ml_gen_proc_params(module_info, pred_id, proc_id) = mlds_func_params.
:- pred ml_gen_proc_params(pred_id::in, proc_id::in, mlds_func_params::out,
ml_gen_info::in, ml_gen_info::out) is det.
% As above, but from the rtti_proc_id rather than from the module_info,
% pred_id, and proc_id.
%
:- func ml_gen_proc_params_from_rtti(module_info, rtti_proc_label) =
mlds_func_params.
% Generate the function prototype for a procedure with the
% given argument types, modes, and code model.
%
:- func ml_gen_params(module_info, list(mlds_var_name), list(mer_type),
list(mer_mode), pred_or_func, code_model) = mlds_func_params.
:- pred ml_gen_params(list(mlds_var_name)::in, list(mer_type)::in,
list(mer_mode)::in, pred_or_func::in, code_model::in,
mlds_func_params::out, ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
%
% Routines for generating labels and entity names.
%
% Generate the mlds_entity_name and module name for the entry point
% function corresponding to a given procedure.
%
:- pred ml_gen_proc_label(module_info::in, pred_id::in, proc_id::in,
mlds_entity_name::out, mlds_module_name::out) is det.
% Generate an mlds_entity_name for a continuation function with the
% given sequence number. The pred_id and proc_id specify the procedure
% that this continuation function is part of.
%
:- func ml_gen_nondet_label(module_info, pred_id, proc_id, ml_label_func)
= mlds_entity_name.
% Allocate a new function label and return an rval containing the
% function's address. If parameters are not given, we assume it is
% a continuation function, and give it the appropriate arguments
% (depending on whether we are doing nested functions or not).
%
:- pred ml_gen_new_func_label(maybe(mlds_func_params)::in, ml_label_func::out,
mlds_rval::out, ml_gen_info::in, ml_gen_info::out) is det.
% Generate the mlds_pred_label and module name for a given procedure.
%
:- pred ml_gen_pred_label(module_info::in, pred_id::in, proc_id::in,
mlds_pred_label::out, mlds_module_name::out) is det.
:- pred ml_gen_pred_label_from_rtti(module_info::in, rtti_proc_label::in,
mlds_pred_label::out, mlds_module_name::out) is det.
% Allocate a new label name, for use in label statements.
%
:- pred ml_gen_new_label(mlds_label::out,
ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
%
% Routines for dealing with variables.
%
% Generate a list of the mlds_lvals corresponding to a given list
% of prog_vars.
%
:- pred ml_gen_var_list(ml_gen_info::in, list(prog_var)::in,
list(mlds_lval)::out) is det.
% Generate the mlds_lval corresponding to a given prog_var.
%
:- pred ml_gen_var(ml_gen_info::in, prog_var::in, mlds_lval::out) is det.
% Generate the mlds_lval corresponding to a given prog_var,
% with a given type.
%
:- pred ml_gen_var_with_type(ml_gen_info::in, prog_var::in, mer_type::in,
mlds_lval::out) is det.
% Lookup the types of a list of variables.
%
:- pred ml_variable_types(ml_gen_info::in, list(prog_var)::in,
list(mer_type)::out) is det.
% Lookup the type of a variable.
%
:- pred ml_variable_type(ml_gen_info::in, prog_var::in, mer_type::out) is det.
% Generate the MLDS variable names for a list of variables.
%
:- func ml_gen_var_names(prog_varset, list(prog_var)) = list(mlds_var_name).
% Generate the MLDS variable name for a variable.
%
:- func ml_gen_var_name(prog_varset, prog_var) = mlds_var_name.
% Generate an lval from the variable name and type. The variable
% name will be qualified with the current module name.
%
:- pred ml_gen_var_lval(ml_gen_info::in, mlds_var_name::in, mlds_type::in,
mlds_lval::out) is det.
% Generate a declaration for an MLDS variable, given its HLDS type.
%
:- pred ml_gen_var_decl(mlds_var_name::in, mer_type::in, prog_context::in,
mlds_defn::out, ml_gen_info::in, ml_gen_info::out) is det.
% Generate a declaration for an MLDS variable, given its MLDS type
% and the code to trace it for accurate GC (if needed).
%
:- func ml_gen_mlds_var_decl(mlds_data_name, mlds_type,
mlds_gc_statement, mlds_context) = mlds_defn.
% Generate a declaration for an MLDS variable, given its MLDS type
% and initializer, and given the code to trace it for accurate GC
% (if needed).
%
:- func ml_gen_mlds_var_decl_init(mlds_data_name, mlds_type, mlds_initializer,
mlds_gc_statement, mlds_context) = mlds_defn.
% Generate declaration flags for a local variable.
%
:- func ml_gen_local_var_decl_flags = mlds_decl_flags.
% Return the declaration flags appropriate for a public field
% in the derived constructor class of a discriminated union.
%
:- func ml_gen_public_field_decl_flags = mlds_decl_flags.
% Apply the usual %s_%d formatting to a MLDS variable name.
%
:- func ml_var_name_to_string(mlds_var_name) = string.
%-----------------------------------------------------------------------------%
%
% Routines for dealing with static constants.
%
% ml_format_reserved_object_name(CtorName, CtorArity, ReservedObjName):
%
% Generate a name for a specially reserved global variable
% (or static member variable) whose address is used to represent
% the specified constructor.
%
:- func ml_format_reserved_object_name(string, arity) = mlds_var_name.
%-----------------------------------------------------------------------------%
%
% Routines for dealing with fields.
%
% Given the user-specified field name, if any, and the argument number
% (starting from one), generate an MLDS field name.
%
:- func ml_gen_field_name(maybe(ctor_field_name), int) = mlds_field_name.
% Succeeds iff the specified type must be boxed when used as a field.
% For the MLDS->C and MLDS->asm back-ends, we need to box types that
% are not word-sized, because the code for `arg' etc. in std_util.m
% relies on all arguments being word-sized.
%
:- pred ml_must_box_field_type(module_info::in, mer_type::in) is semidet.
:- pred ml_gen_box_const_rval(module_info::in, prog_context::in,
mlds_type::in, mlds_rval::in, mlds_rval::out,
ml_global_data::in, ml_global_data::out) is det.
% Given a source type and a destination type, and given an source rval
% holding a value of the source type, produce an rval that converts
% the source rval to the destination type.
%
:- pred ml_gen_box_or_unbox_rval(module_info::in, mer_type::in, mer_type::in,
box_policy::in, mlds_rval::in, mlds_rval::out) is det.
% ml_gen_box_or_unbox_lval(CallerType, CalleeType, VarLval, VarName,
% Context, ForClosureWrapper, ArgNum,
% ArgLval, ConvDecls, ConvInputStatements, ConvOutputStatements):
%
% This is like `ml_gen_box_or_unbox_rval', except that it works on lvals
% rather than rvals. Given a source type and a destination type,
% a source lval holding a value of the source type, and a name to base
% the name of the local temporary variable on, this procedure produces
% an lval of the destination type, the declaration for the local temporary
% used (if any), code to assign from the source lval (suitable converted)
% to the destination lval, and code to assign from the destination lval
% (suitable converted) to the source lval.
%
% If ForClosureWrapper = yes, then the type_info for type variables
% in CallerType may not be available in the current procedure, so the GC
% tracing code for the ConvDecls (if any) should obtain the type_info
% from the ArgNum-th entry in the `type_params' local.
% (If ForClosureWrapper = no, then ArgNum is unused.)
%
:- pred ml_gen_box_or_unbox_lval(mer_type::in, mer_type::in, box_policy::in,
mlds_lval::in, mlds_var_name::in, prog_context::in, bool::in, int::in,
mlds_lval::out, list(mlds_defn)::out,
list(statement)::out, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
% ml_gen_local_for_output_arg(VarName, Type, ArgNum, Context,
% LocalVarDefn):
%
% Generate a declaration for a local variable with the specified
% VarName and Type. However, don't use the normal GC tracing code;
% instead, generate GC tracing code that gets the typeinfo from
% the ArgNum-th entry in `type_params'.
%
:- pred ml_gen_local_for_output_arg(mlds_var_name::in, mer_type::in, int::in,
prog_context::in, mlds_defn::out,
ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
%
% Routines for handling success and failure.
%
% Generate code to succeed in the given code_model.
%
:- pred ml_gen_success(code_model::in, prog_context::in, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
% Generate code to fail in the given code_model.
%
:- pred ml_gen_failure(code_model::in, prog_context::in, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
% Generate the declaration for the built-in `succeeded' flag.
% (`succeeded' is a boolean variable used to record
% the success or failure of model_semi procedures.)
%
:- func ml_gen_succeeded_var_decl(mlds_context) = mlds_defn.
% Return the lval for the `succeeded' flag.
% (`succeeded' is a boolean variable used to record
% the success or failure of model_semi procedures.)
%
:- pred ml_success_lval(ml_gen_info::in, mlds_lval::out) is det.
% Return an rval which will test the value of the `succeeded' flag.
% (`succeeded' is a boolean variable used to record
% the success or failure of model_semi procedures.)
%
:- pred ml_gen_test_success(ml_gen_info::in, mlds_rval::out) is det.
% Generate code to set the `succeeded' flag to the specified truth value.
%
:- pred ml_gen_set_success(ml_gen_info::in, mlds_rval::in, prog_context::in,
statement::out) is det.
% Generate the declaration for the specified `cond' variable.
% (`cond' variables are boolean variables used to record
% the success or failure of model_non conditions of if-then-elses.)
%
:- func ml_gen_cond_var_decl(cond_seq, mlds_context) = mlds_defn.
% Return the lval for the specified `cond' flag.
% (`cond' variables are boolean variables used to record
% the success or failure of model_non conditions of if-then-elses.)
%
:- pred ml_cond_var_lval(ml_gen_info::in, cond_seq::in, mlds_lval::out) is det.
% Return an rval which will test the value of the specified `cond'
% variable. (`cond' variables are boolean variables used to record
% the success or failure of model_non conditions of if-then-elses.)
%
:- pred ml_gen_test_cond_var(ml_gen_info::in, cond_seq::in, mlds_rval::out)
is det.
% Generate code to set the specified `cond' variable to the
% specified truth value.
%
:- pred ml_gen_set_cond_var(ml_gen_info::in, cond_seq::in, mlds_rval::in,
prog_context::in, statement::out) is det.
% Return the success continuation that was passed as the current function's
% argument(s). The success continuation consists of two parts, the `cont'
% argument, and the `cont_env' argument. The `cont' argument is a
% continuation function that will be called when a model_non goal succeeds.
% The `cont_env' argument is a pointer to the environment (set of local
% variables in the containing procedure) for the continuation function.
% (If we're using gcc nested function, the `cont_env' is not used.)
% The output variable lvals and types need to be supplied when generating
% a continuation using --nondet-copy-out, otherwise they should be empty.
%
:- pred ml_initial_cont(ml_gen_info::in, list(mlds_lval)::in,
list(mer_type)::in, success_cont::out) is det.
% Generate code to call the current success continuation.
% This is used for generating success when in a model_non context.
%
:- pred ml_gen_call_current_success_cont(prog_context::in,
statement::out, ml_gen_info::in, ml_gen_info::out) is det.
% Generate code to call the current success continuation, using
% a local function as a proxy.
% This is used for generating success when in a model_non context
% from within pragma C code (currently only in IL).
%
:- pred ml_gen_call_current_success_cont_indirectly(prog_context::in,
statement::out, ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
%
% Routines for dealing with the environment pointer used for nested functions.
%
% Return an rval for a pointer to the current environment (the set of local
% variables in the containing procedure). Note that we generate this
% as a dangling reference. The ml_elim_nested pass will insert the
% declaration of the env_ptr variable. At this point, the type of these
% rvals is `mlds_unknown_type'.
%
:- pred ml_get_env_ptr(ml_gen_info::in, mlds_rval::out) is det.
% Return an mlds_argument for a pointer to the current environment
% (the set of local variables in the containing procedure).
%
:- pred ml_declare_env_ptr_arg(mlds_argument::out) is det.
%-----------------------------------------------------------------------------%
%
% Magic numbers relating to the representation of
% typeclass_infos, base_typeclass_infos, and closures.
%
% This function returns the offset to add to the argument number
% of a closure arg to get its field number.
%
:- func ml_closure_arg_offset = int.
% This function returns the offset to add to the argument number
% of a typeclass_info arg to get its field number.
%
:- func ml_typeclass_info_arg_offset = int.
% This function returns the offset to add to the method number for a type
% class method to get its field number within the base_typeclass_info.
%
:- func ml_base_typeclass_info_method_offset = int.
%-----------------------------------------------------------------------------%
%
% Routines for dealing with lookup tables.
%
:- pred ml_generate_constants_for_arms(list(prog_var)::in, list(hlds_goal)::in,
list(list(mlds_rval))::out, ml_gen_info::in, ml_gen_info::out) is det.
:- pred ml_generate_constants_for_arm(list(prog_var)::in, hlds_goal::in,
list(mlds_rval)::out, ml_gen_info::in, ml_gen_info::out) is det.
:- pred ml_generate_field_assign(mlds_lval::in, mlds_type::in,
mlds_field_id::in, mlds_vector_common::in, mlds_type::in,
mlds_rval::in, mlds_context::in, statement::out,
ml_gen_info::in, ml_gen_info::out) is det.
:- pred ml_generate_field_assigns(list(prog_var)::in, list(mlds_type)::in,
list(mlds_field_id)::in, mlds_vector_common::in, mlds_type::in,
mlds_rval::in, mlds_context::in, list(statement)::out,
ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
%
% Miscellaneous routines.
%
% Get the value of the appropriate --det-copy-out or --nondet-copy-out
% option, depending on the code model.
%
:- func get_copy_out_option(globals, code_model) = bool.
% Add the qualifier `builtin' to any unqualified name.
% Although the builtin types `int', `float', etc. are treated as part
% of the `builtin' module, for historical reasons they don't have
% any qualifiers in the HLDS, so we need to add the `builtin'
% qualifier before converting such names to MLDS.
%
:- func fixup_builtin_module(module_name) = module_name.
:- pred ml_gen_box_const_rvals(module_info::in, prog_context::in,
list(mlds_type)::in, list(mlds_rval)::in, list(mlds_rval)::out,
ml_global_data::in, ml_global_data::out) is det.
%-----------------------------------------------------------------------------%
%-----------------------------------------------------------------------------%
:- implementation.
:- import_module backend_libs.foreign.
:- import_module check_hlds.mode_util.
:- import_module check_hlds.type_util.
:- import_module libs.globals.
:- import_module libs.options.
:- import_module mdbcomp.program_representation.
:- import_module ml_backend.ml_accurate_gc.
:- import_module ml_backend.ml_call_gen.
:- import_module ml_backend.ml_code_gen.
:- import_module parse_tree.builtin_lib_types.
:- import_module parse_tree.java_names.
:- import_module parse_tree.prog_data.
:- import_module parse_tree.prog_type.
:- import_module parse_tree.prog_util.
:- import_module map.
:- import_module pair.
:- import_module require.
:- import_module set.
:- import_module string.
:- import_module term.
:- import_module varset.
%-----------------------------------------------------------------------------%
%
% Code for various utility routines.
%
ml_gen_assign(Lval, Rval, Context) = Statement :-
Assign = assign(Lval, Rval),
Stmt = ml_stmt_atomic(Assign),
Statement = statement(Stmt, mlds_make_context(Context)).
ml_append_return_statement(Info, CodeModel, CopiedOutputVarLvals, Context,
!Statements) :-
(
CodeModel = model_semi,
ml_gen_test_success(Info, Succeeded),
CopiedOutputVarRvals = list.map(func(Lval) = ml_lval(Lval),
CopiedOutputVarLvals),
ReturnStmt = ml_stmt_return([Succeeded | CopiedOutputVarRvals]),
ReturnStatement = statement(ReturnStmt,
mlds_make_context(Context)),
!:Statements = !.Statements ++ [ReturnStatement]
;
CodeModel = model_det,
(
CopiedOutputVarLvals = [_ | _],
CopiedOutputVarRvals = list.map(func(Lval) = ml_lval(Lval),
CopiedOutputVarLvals),
ReturnStmt = ml_stmt_return(CopiedOutputVarRvals),
ReturnStatement = statement(ReturnStmt,
mlds_make_context(Context)),
!:Statements = !.Statements ++ [ReturnStatement]
;
CopiedOutputVarLvals = []
)
;
CodeModel = model_non
).
ml_gen_block(VarDecls, Statements, Context) = Block :-
(
VarDecls = [],
Statements = [SingleStatement]
->
Block = SingleStatement
;
Block = statement(ml_stmt_block(VarDecls, Statements),
mlds_make_context(Context))
).
ml_gen_block_mlds(VarDecls, Statements, Context) = Block :-
(
VarDecls = [],
Statements = [SingleStatement]
->
Block = SingleStatement
;
Block = statement(ml_stmt_block(VarDecls, Statements), Context)
).
ml_combine_conj(FirstCodeModel, Context, DoGenFirst, DoGenRest,
Decls, Statements, !Info) :-
(
% model_det goal:
% <First, Rest>
% ===>
% <do First>
% <Rest>
%
FirstCodeModel = model_det,
DoGenFirst(FirstDecls, FirstStatements, !Info),
DoGenRest(RestDecls, RestStatements, !Info),
Decls = FirstDecls ++ RestDecls,
Statements = FirstStatements ++ RestStatements
;
% model_semi goal:
% <Goal, Goals>
% ===>
% MR_bool succeeded;
%
% <succeeded = Goal>;
% if (succeeded) {
% <Goals>;
% }
% except that we hoist any declarations generated for <Goals>
% to the outer scope, rather than inside the `if', so that they remain
% in scope for any later goals which follow this (this is needed for
% declarations of static consts).
FirstCodeModel = model_semi,
DoGenFirst(FirstDecls, FirstStatements, !Info),
ml_gen_test_success(!.Info, Succeeded),
DoGenRest(RestDecls, RestStatements, !Info),
IfBody = ml_gen_block([], RestStatements, Context),
IfStmt = ml_stmt_if_then_else(Succeeded, IfBody, no),
IfStatement = statement(IfStmt, mlds_make_context(Context)),
Decls = FirstDecls ++ RestDecls,
Statements = FirstStatements ++ [IfStatement]
;
% model_non goal:
% <First, Rest>
% ===>
% succ_func() {
% <Rest && SUCCEED()>;
% }
%
% <First && succ_func()>;
%
% except that we hoist any declarations generated for <First> and
% any _static_ declarations generated for <Rest> to the top of the
% scope, rather than inside or after the succ_func(), so that they
% remain in scope for any code following them (this is needed for
% declarations of static consts).
%
% We take care to only hoist _static_ declarations outside nested
% functions, since access to non-local variables is less efficient.
%
% XXX The pattern above leads to deep nesting for long conjunctions;
% we should avoid that.
%
FirstCodeModel = model_non,
% allocate a name for the `succ_func'
ml_gen_new_func_label(no, RestFuncLabel, RestFuncLabelRval, !Info),
% generate <First && succ_func()>
ml_get_env_ptr(!.Info, EnvPtrRval),
SuccessCont = success_cont(RestFuncLabelRval, EnvPtrRval, [], []),
ml_gen_info_push_success_cont(SuccessCont, !Info),
DoGenFirst(FirstDecls, FirstStatements, !Info),
ml_gen_info_pop_success_cont(!Info),
% generate the `succ_func'
% push nesting level
DoGenRest(RestDecls, RestStatements, !Info),
RestStatement = ml_gen_block(RestDecls, RestStatements, Context),
% pop nesting level
ml_gen_nondet_label_func(!.Info, RestFuncLabel, Context,
RestStatement, RestFunc),
Decls = FirstDecls ++ [RestFunc],
Statements = FirstStatements
).
ml_gen_nondet_label_func(Info, FuncLabel, Context, Statement, Func) :-
ml_gen_info_use_gcc_nested_functions(Info, UseNested),
(
UseNested = yes,
FuncParams = mlds_func_params([], [])
;
UseNested = no,
ml_declare_env_ptr_arg(EnvPtrArg),
FuncParams = mlds_func_params([EnvPtrArg], [])
),
ml_gen_label_func(Info, FuncLabel, FuncParams, Context, Statement, Func).
ml_gen_label_func(Info, FuncLabel, FuncParams, Context, Statement, Func) :-
% Compute the function name.
ml_gen_info_get_module_info(Info, ModuleInfo),
ml_gen_info_get_pred_id(Info, PredId),
ml_gen_info_get_proc_id(Info, ProcId),
FuncName = ml_gen_nondet_label(ModuleInfo, PredId, ProcId, FuncLabel),
% Compute the function definition.
DeclFlags = ml_gen_label_func_decl_flags,
MaybePredProcId = no,
Attributes = [],
EnvVarNames = set.init,
FuncDefn = mlds_function(MaybePredProcId, FuncParams,
body_defined_here(Statement), Attributes, EnvVarNames),
Func = mlds_defn(FuncName, mlds_make_context(Context), DeclFlags,
FuncDefn).
% Return the declaration flags appropriate for a label func (a label func
% is a function used as a continuation when generating nondet code).
%
:- func ml_gen_label_func_decl_flags = mlds_decl_flags.
ml_gen_label_func_decl_flags = DeclFlags :-
Access = acc_local,
PerInstance = per_instance,
Virtuality = non_virtual,
Overridability = overridable,
Constness = modifiable,
Abstractness = concrete,
DeclFlags = init_decl_flags(Access, PerInstance, Virtuality,
Overridability, Constness, Abstractness).
%-----------------------------------------------------------------------------%
%
% Code for generating expressions.
%
ml_gen_and(X, Y) =
( X = ml_const(mlconst_true) ->
Y
; Y = ml_const(mlconst_true) ->
X
;
ml_binop(logical_and, X, Y)
).
ml_gen_not(X) = ml_unop(std_unop(logical_not), X).
%-----------------------------------------------------------------------------%
%
% Code for generating types.
%
ml_gen_type(Info, Type, MLDS_Type) :-
ml_gen_info_get_module_info(Info, ModuleInfo),
MLDS_Type = mercury_type_to_mlds_type(ModuleInfo, Type).
ml_gen_array_elem_type(ElemType) = MLDS_Type :-
(
ElemType = array_elem_scalar(ScalarElem),
MLDS_Type = ml_gen_scalar_array_elem_type(ScalarElem)
;
ElemType = array_elem_struct(_ScalarElems),
unexpected($module, $pred, "struct")
).
:- func ml_gen_scalar_array_elem_type(scalar_array_elem_type) = mlds_type.
ml_gen_scalar_array_elem_type(scalar_elem_string) = ml_string_type.
ml_gen_scalar_array_elem_type(scalar_elem_int) = mlds_native_int_type.
ml_gen_scalar_array_elem_type(scalar_elem_generic) = mlds_generic_type.
ml_string_type =
mercury_type(string_type, ctor_cat_builtin(cat_builtin_string),
non_foreign_type(string_type)).
ml_int_type =
mercury_type(int_type, ctor_cat_builtin(cat_builtin_int),
non_foreign_type(int_type)).
ml_char_type =
mercury_type(char_type, ctor_cat_builtin(cat_builtin_char),
non_foreign_type(char_type)).
ml_make_boxed_types(Arity) = BoxedTypes :-
varset.init(TypeVarSet0),
varset.new_vars(Arity, BoxedTypeVars, TypeVarSet0, _TypeVarSet),
prog_type.var_list_to_type_list(map.init, BoxedTypeVars, BoxedTypes).
ml_java_mercury_type_interface = TypeInterfaceDefn :-
InterfaceModuleName = mercury_module_name_to_mlds(
java_mercury_runtime_package_name),
TypeInterface = qual(InterfaceModuleName, module_qual, "MercuryType"),
TypeInterfaceDefn = mlds_class_type(TypeInterface, 0, mlds_interface).
ml_java_mercury_enum_class = EnumClassDefn :-
InterfaceModuleName = mercury_module_name_to_mlds(
java_mercury_runtime_package_name),
EnumClass = qual(InterfaceModuleName, module_qual, "MercuryEnum"),
EnumClassDefn = mlds_class_type(EnumClass, 0, mlds_class).
%-----------------------------------------------------------------------------%
%
% Code for generating function declarations (i.e. mlds_func_params).
%
ml_gen_proc_params(ModuleInfo, PredId, ProcId) = FuncParams :-
module_info_pred_proc_info(ModuleInfo, PredId, ProcId, PredInfo, ProcInfo),
proc_info_get_varset(ProcInfo, VarSet),
proc_info_get_headvars(ProcInfo, HeadVars),
PredOrFunc = pred_info_is_pred_or_func(PredInfo),
pred_info_get_arg_types(PredInfo, HeadTypes),
proc_info_get_argmodes(ProcInfo, HeadModes),
CodeModel = proc_info_interface_code_model(ProcInfo),
HeadVarNames = ml_gen_var_names(VarSet, HeadVars),
FuncParams = ml_gen_params(ModuleInfo, HeadVarNames, HeadTypes,
HeadModes, PredOrFunc, CodeModel).
ml_gen_proc_params(PredId, ProcId, FuncParams, !Info) :-
ml_gen_info_get_module_info(!.Info, ModuleInfo),
module_info_pred_proc_info(ModuleInfo, PredId, ProcId, PredInfo, ProcInfo),
proc_info_get_varset(ProcInfo, VarSet),
proc_info_get_headvars(ProcInfo, HeadVars),
PredOrFunc = pred_info_is_pred_or_func(PredInfo),
pred_info_get_arg_types(PredInfo, HeadTypes),
proc_info_get_argmodes(ProcInfo, HeadModes),
CodeModel = proc_info_interface_code_model(ProcInfo),
HeadVarNames = ml_gen_var_names(VarSet, HeadVars),
% We must not generate GC tracing code for no_type_info_builtin
% procedures, because the generated GC tracing code would refer
% to type_infos that don't get passed.
PredModule = pred_info_module(PredInfo),
PredName = pred_info_name(PredInfo),
PredArity = pred_info_orig_arity(PredInfo),
( no_type_info_builtin(PredModule, PredName, PredArity) ->
FuncParams = ml_gen_params(ModuleInfo, HeadVarNames, HeadTypes,
HeadModes, PredOrFunc, CodeModel)
;
ml_gen_params(HeadVarNames, HeadTypes, HeadModes, PredOrFunc,
CodeModel, FuncParams, !Info)
).
ml_gen_proc_params_from_rtti(ModuleInfo, RttiProcId) = FuncParams :-
HeadVars = RttiProcId ^ rpl_proc_headvars,
ArgTypes = RttiProcId ^ rpl_proc_arg_types,
ArgModes = RttiProcId ^ rpl_proc_arg_modes,
PredOrFunc = RttiProcId ^ rpl_pred_or_func,
Detism = RttiProcId ^ rpl_proc_interface_detism,
determinism_to_code_model(Detism, CodeModel),
HeadVarNames = list.map(
(func(Var - Name) = Result :-
term.var_to_int(Var, N),
Result = mlds_var_name(Name, yes(N))
), HeadVars),
ml_gen_params_base(ModuleInfo, HeadVarNames, ArgTypes, ArgModes,
PredOrFunc, CodeModel, FuncParams, no, _).
ml_gen_params(ModuleInfo, HeadVarNames, HeadTypes, HeadModes, PredOrFunc,
CodeModel) = FuncParams :-
modes_to_arg_modes(ModuleInfo, HeadModes, HeadTypes, ArgModes),
ml_gen_params_base(ModuleInfo, HeadVarNames, HeadTypes, ArgModes,
PredOrFunc, CodeModel, FuncParams, no, _).
ml_gen_params(HeadVarNames, HeadTypes, HeadModes, PredOrFunc,
CodeModel, FuncParams, !Info) :-
ml_gen_info_get_module_info(!.Info, ModuleInfo),
modes_to_arg_modes(ModuleInfo, HeadModes, HeadTypes, ArgModes),
ml_gen_params_base(ModuleInfo, HeadVarNames,
HeadTypes, ArgModes, PredOrFunc, CodeModel, FuncParams,
yes(!.Info), MaybeInfo),
(
MaybeInfo = yes(Info),
!:Info = Info
;
MaybeInfo = no,
unexpected($module, $pred, "missing ml_gen_info")
).
:- pred ml_gen_params_base(module_info::in, list(mlds_var_name)::in,
list(mer_type)::in, list(arg_mode)::in, pred_or_func::in,
code_model::in, mlds_func_params::out,
maybe(ml_gen_info)::in, maybe(ml_gen_info)::out) is det.
ml_gen_params_base(ModuleInfo, HeadVarNames, HeadTypes, HeadModes, PredOrFunc,
CodeModel, FuncParams, !MaybeInfo) :-
module_info_get_globals(ModuleInfo, Globals),
CopyOut = get_copy_out_option(Globals, CodeModel),
ml_gen_arg_decls(ModuleInfo, HeadVarNames, HeadTypes, HeadModes,
CopyOut, FuncArgs0, RetTypes0, !MaybeInfo),
(
CodeModel = model_det,
% For model_det Mercury functions whose result argument has an
% output mode, make the result into the MLDS return type.
(
RetTypes0 = [],
PredOrFunc = pf_function,
pred_args_to_func_args(HeadModes, _, ResultMode),
ResultMode = top_out,
pred_args_to_func_args(HeadTypes, _, ResultType),
check_dummy_type(ModuleInfo, ResultType) = is_not_dummy_type
->
pred_args_to_func_args(FuncArgs0, FuncArgs, RetArg),
RetArg = mlds_argument(_RetArgName, RetTypePtr, _GCStatement),
( RetTypePtr = mlds_ptr_type(RetType) ->
RetTypes = [RetType]
;
unexpected($module, $pred,
"output mode function result doesn't have pointer type")
)
;
FuncArgs = FuncArgs0,
RetTypes = RetTypes0
)
;
CodeModel = model_semi,
% For model_semi procedures, return a bool.
FuncArgs = FuncArgs0,
RetTypes = [mlds_native_bool_type | RetTypes0]
;
CodeModel = model_non,
% For model_non procedures, we return values by passing them
% to the continuation.
(
CopyOut = yes,
ContType = mlds_cont_type(RetTypes0),
RetTypes = []
;
CopyOut = no,
ContType = mlds_cont_type([]),
RetTypes = RetTypes0
),
ContName = entity_data(mlds_data_var(mlds_var_name("cont", no))),
% The cont variable always points to code, not to the heap,
% so the GC never needs to trace it.
ContGCStatement = gc_no_stmt,
ContArg = mlds_argument(ContName, ContType, ContGCStatement),
ContEnvType = mlds_generic_env_ptr_type,
ContEnvName = entity_data(
mlds_data_var(mlds_var_name("cont_env_ptr", no))),
% The cont_env_ptr always points to the stack, since continuation
% environments are always allocated on the stack (unless
% put_nondet_env_on_heap is true, which won't be the case when doing
% our own GC -- this is enforced in handle_options.m).
% So the GC doesn't need to trace it.
ContEnvGCStatement = gc_no_stmt,
ContEnvArg = mlds_argument(ContEnvName, ContEnvType,
ContEnvGCStatement),
globals.lookup_bool_option(Globals, gcc_nested_functions,
NestedFunctions),
(
NestedFunctions = yes,
FuncArgs = FuncArgs0 ++ [ContArg]
;
NestedFunctions = no,
FuncArgs = FuncArgs0 ++ [ContArg, ContEnvArg]
)
),
FuncParams = mlds_func_params(FuncArgs, RetTypes).
% Given the argument variable names, and corresponding lists of their
% types and modes, generate the MLDS argument declarations
% and return types.
%
:- pred ml_gen_arg_decls(module_info::in, list(mlds_var_name)::in,
list(mer_type)::in, list(arg_mode)::in, bool::in,
mlds_arguments::out, mlds_return_types::out,
maybe(ml_gen_info)::in, maybe(ml_gen_info)::out) is det.
ml_gen_arg_decls(ModuleInfo, HeadVars, HeadTypes, HeadModes, CopyOut,
FuncArgs, RetTypes, !MaybeInfo) :-
(
HeadVars = [],
HeadTypes = [],
HeadModes = []
->
FuncArgs = [],
RetTypes = []
;
HeadVars = [Var | Vars],
HeadTypes = [Type | Types],
HeadModes = [Mode | Modes]
->
ml_gen_arg_decls(ModuleInfo, Vars, Types, Modes, CopyOut,
FuncArgs0, RetTypes0, !MaybeInfo),
(
% Exclude types such as io.state, etc.
% Also exclude values with arg_mode `top_unused'.
( check_dummy_type(ModuleInfo, Type) = is_dummy_type
; Mode = top_unused
)
->
FuncArgs = FuncArgs0,
RetTypes = RetTypes0
;
% For by-value outputs, generate a return type.
Mode = top_out,
CopyOut = yes
->
RetType = mercury_type_to_mlds_type(ModuleInfo, Type),
RetTypes = [RetType | RetTypes0],
FuncArgs = FuncArgs0
;
% For inputs and by-reference outputs, generate argument.
ml_gen_arg_decl(ModuleInfo, Var, Type, Mode, FuncArg, !MaybeInfo),
FuncArgs = [FuncArg | FuncArgs0],
RetTypes = RetTypes0
)
;
unexpected($module, $pred, "length mismatch")
).
% Given an argument variable, and its type and mode,
% generate an MLDS argument declaration for it.
%
:- pred ml_gen_arg_decl(module_info::in, mlds_var_name::in, mer_type::in,
arg_mode::in, mlds_argument::out,
maybe(ml_gen_info)::in, maybe(ml_gen_info)::out) is det.
ml_gen_arg_decl(ModuleInfo, Var, Type, ArgMode, FuncArg, !MaybeInfo) :-
MLDS_Type = mercury_type_to_mlds_type(ModuleInfo, Type),
(
ArgMode = top_in,
MLDS_ArgType = MLDS_Type
;
( ArgMode = top_out
; ArgMode = top_unused
),
MLDS_ArgType = mlds_ptr_type(MLDS_Type)
),
Name = entity_data(mlds_data_var(Var)),
(
!.MaybeInfo = yes(Info0),
% XXX We should fill in this Context properly.
term.context_init(Context),
ml_gen_gc_statement(Var, Type, Context, GCStatement, Info0, Info),
!:MaybeInfo = yes(Info)
;
!.MaybeInfo = no,
GCStatement = gc_no_stmt,
!:MaybeInfo = no
),
FuncArg = mlds_argument(Name, MLDS_ArgType, GCStatement).
ml_is_output_det_function(ModuleInfo, PredId, ProcId, RetArgVar) :-
module_info_pred_proc_info(ModuleInfo, PredId, ProcId, PredInfo, ProcInfo),
pred_info_is_pred_or_func(PredInfo) = pf_function,
proc_info_interface_code_model(ProcInfo) = model_det,
proc_info_get_argmodes(ProcInfo, Modes),
pred_info_get_arg_types(PredInfo, ArgTypes),
proc_info_get_headvars(ProcInfo, ArgVars),
modes_to_arg_modes(ModuleInfo, Modes, ArgTypes, ArgModes),
pred_args_to_func_args(ArgModes, _InputArgModes, RetArgMode),
pred_args_to_func_args(ArgTypes, _InputArgTypes, RetArgType),
pred_args_to_func_args(ArgVars, _InputArgVars, RetArgVar),
RetArgMode = top_out,
check_dummy_type(ModuleInfo, RetArgType) = is_not_dummy_type.
%-----------------------------------------------------------------------------%
%
% Code for generating mlds_entity_names.
%
% Generate the mlds_entity_name and module name for the entry point
% function corresponding to a given procedure.
%
ml_gen_proc_label(ModuleInfo, PredId, ProcId, MLDS_Name, MLDS_ModuleName) :-
ml_gen_func_label(ModuleInfo, PredId, ProcId, no, MLDS_Name,
MLDS_ModuleName).
% Generate an mlds_entity_name for a continuation function with the given
% sequence number. The pred_id and proc_id specify the procedure that this
% continuation function is part of.
%
ml_gen_nondet_label(ModuleInfo, PredId, ProcId, SeqNum) = MLDS_Name :-
ml_gen_func_label(ModuleInfo, PredId, ProcId, yes(SeqNum),
MLDS_Name, _MLDS_ModuleName).
:- pred ml_gen_func_label(module_info::in, pred_id::in, proc_id::in,
maybe(ml_label_func)::in, mlds_entity_name::out,
mlds_module_name::out) is det.
ml_gen_func_label(ModuleInfo, PredId, ProcId, MaybeSeqNum,
MLDS_Name, MLDS_ModuleName) :-
ml_gen_pred_label(ModuleInfo, PredId, ProcId,
MLDS_PredLabel, MLDS_ModuleName),
MLDS_Name = entity_function(MLDS_PredLabel, ProcId, MaybeSeqNum, PredId).
% Allocate a new function label and return an rval containing
% the function's address.
%
ml_gen_new_func_label(MaybeParams, FuncLabel, FuncLabelRval, !Info) :-
ml_gen_info_new_func_label(FuncLabel, !Info),
ml_gen_info_get_module_info(!.Info, ModuleInfo),
ml_gen_info_get_pred_id(!.Info, PredId),
ml_gen_info_get_proc_id(!.Info, ProcId),
ml_gen_pred_label(ModuleInfo, PredId, ProcId,
PredLabel, PredModule),
ml_gen_info_use_gcc_nested_functions(!.Info, UseNestedFuncs),
(
MaybeParams = yes(Params),
Signature = mlds_get_func_signature(Params)
;
MaybeParams = no,
(
UseNestedFuncs = yes,
ArgTypes = []
;
UseNestedFuncs = no,
ArgTypes = [mlds_generic_env_ptr_type]
),
Signature = mlds_func_signature(ArgTypes, [])
),
ProcLabel = mlds_proc_label(PredLabel, ProcId),
QualProcLabel = qual(PredModule, module_qual, ProcLabel),
FuncLabelRval = ml_const(
mlconst_code_addr(code_addr_internal(QualProcLabel,
FuncLabel, Signature))).
% Generate the mlds_pred_label and module name for a given procedure.
%
ml_gen_pred_label(ModuleInfo, PredId, ProcId, MLDS_PredLabel, MLDS_Module) :-
RttiProcLabel = make_rtti_proc_label(ModuleInfo, PredId, ProcId),
ml_gen_pred_label_from_rtti(ModuleInfo, RttiProcLabel,
MLDS_PredLabel, MLDS_Module).
ml_gen_pred_label_from_rtti(ModuleInfo, RttiProcLabel, MLDS_PredLabel,
MLDS_Module) :-
RttiProcLabel = rtti_proc_label(PredOrFunc, ThisModule, PredModule,
PredName, PredArity, _ArgTypes, PredId, ProcId,
_HeadVarsWithNames, _ArgModes, Detism,
PredIsImported, _PredIsPseudoImported,
Origin, _ProcIsExported, _ProcIsImported),
( Origin = origin_special_pred(SpecialPred - TypeCtor) ->
(
% All type_ctors other than tuples here should be module qualified,
% since builtin types are handled separately in polymorphism.m.
TypeCtor = type_ctor(TypeCtorSymName, TypeArity),
(
TypeCtorSymName = unqualified(TypeName),
type_ctor_is_tuple(TypeCtor),
TypeModule = mercury_public_builtin_module
;
TypeCtorSymName = qualified(TypeModule, TypeName)
)
->
(
ThisModule \= TypeModule,
SpecialPred = spec_pred_unify,
\+ hlds_pred.in_in_unification_proc_id(ProcId)
->
% This is a locally-defined instance of a unification procedure
% for a type defined in some other module.
DefiningModule = ThisModule,
MaybeDeclaringModule = yes(TypeModule)
;
% The module declaring the type is the same as the module
% defining this special pred.
DefiningModule = TypeModule,
MaybeDeclaringModule = no
),
MLDS_PredLabel = mlds_special_pred_label(PredName,
MaybeDeclaringModule, TypeName, TypeArity)
;
unexpected($module, $pred,
"cannot make label for special pred `" ++ PredName ++ "'")
)
;
(
% Work out which module supplies the code for the predicate.
ThisModule \= PredModule,
PredIsImported = no
->
% This predicate is a specialized version of a pred from a
% `.opt' file.
DefiningModule = ThisModule,
MaybeDeclaringModule = yes(PredModule)
;
% The predicate was declared in the same module that it is
% defined in
DefiningModule = PredModule,
MaybeDeclaringModule = no
),
(
PredOrFunc = pf_function,
\+ ml_is_output_det_function(ModuleInfo, PredId, ProcId, _)
->
NonOutputFunc = yes
;
NonOutputFunc = no
),
determinism_to_code_model(Detism, CodeModel),
MLDS_PredLabel = mlds_user_pred_label(PredOrFunc, MaybeDeclaringModule,
PredName, PredArity, CodeModel, NonOutputFunc)
),
MLDS_Module = mercury_module_name_to_mlds(DefiningModule).
ml_gen_new_label(Label, !Info) :-
ml_gen_info_new_label(LabelNum, !Info),
Label = "label_" ++ string.int_to_string(LabelNum).
%-----------------------------------------------------------------------------%
%
% Code for dealing with variables.
%
ml_gen_var_list(_Info, [], []).
ml_gen_var_list(Info, [Var | Vars], [Lval | Lvals]) :-
ml_gen_var(Info, Var, Lval),
ml_gen_var_list(Info, Vars, Lvals).
ml_gen_var(Info, Var, Lval) :-
% First check the var_lvals override mapping; if an lval has been set
% for this variable, use it.
ml_gen_info_get_var_lvals(Info, VarLvals),
( map.search(VarLvals, Var, VarLval) ->
Lval = VarLval
;
% Otherwise just look up the variable's type and generate an lval
% for it using the ordinary algorithm.
ml_variable_type(Info, Var, Type),
ml_gen_var_with_type(Info, Var, Type, Lval)
).
ml_gen_var_with_type(Info, Var, Type, Lval) :-
ml_gen_info_get_module_info(Info, ModuleInfo),
IsDummy = check_dummy_type(ModuleInfo, Type),
(
IsDummy = is_dummy_type,
% The variable won't have been declared, so we need to generate
% a dummy lval for this variable.
PrivateBuiltin = mercury_private_builtin_module,
MLDS_Module = mercury_module_name_to_mlds(PrivateBuiltin),
ml_gen_type(Info, Type, MLDS_Type),
Lval = ml_var(qual(MLDS_Module, module_qual,
mlds_var_name("dummy_var", no)), MLDS_Type)
;
IsDummy = is_not_dummy_type,
ml_gen_info_get_varset(Info, VarSet),
VarName = ml_gen_var_name(VarSet, Var),
ml_gen_type(Info, Type, MLDS_Type),
ml_gen_var_lval(Info, VarName, MLDS_Type, VarLval),
% Output variables may be passed by reference...
ml_gen_info_get_byref_output_vars(Info, OutputVars),
( list.member(Var, OutputVars) ->
Lval = ml_mem_ref(ml_lval(VarLval), MLDS_Type)
;
Lval = VarLval
)
).
ml_variable_types(_Info, [], []).
ml_variable_types(Info, [Var | Vars], [Type | Types]) :-
ml_variable_type(Info, Var, Type),
ml_variable_types(Info, Vars, Types).
ml_variable_type(Info, Var, Type) :-
ml_gen_info_get_var_types(Info, VarTypes),
map.lookup(VarTypes, Var, Type).
ml_gen_var_names(VarSet, Vars) = list.map(ml_gen_var_name(VarSet), Vars).
ml_gen_var_name(VarSet, Var) = UniqueVarName :-
varset.lookup_name(VarSet, Var, VarName),
term.var_to_int(Var, VarNumber),
UniqueVarName = mlds_var_name(VarName, yes(VarNumber)).
ml_format_reserved_object_name(CtorName, CtorArity) = ReservedObjName :-
% We add the "obj_" prefix to avoid any potential name clashes.
Name = "obj_" ++ CtorName ++ "_" ++ string.int_to_string(CtorArity),
ReservedObjName = mlds_var_name(Name, no).
ml_gen_var_lval(Info, VarName, VarType, QualifiedVarLval) :-
ml_gen_info_get_module_name(Info, ModuleName),
MLDS_ModuleName = mercury_module_name_to_mlds(ModuleName),
MLDS_Var = qual(MLDS_ModuleName, module_qual, VarName),
QualifiedVarLval = ml_var(MLDS_Var, VarType).
ml_gen_var_decl(VarName, Type, Context, Defn, !Info) :-
ml_gen_info_get_module_info(!.Info, ModuleInfo),
ml_gen_gc_statement(VarName, Type, Context, GCStatement, !Info),
Defn = ml_gen_mlds_var_decl(mlds_data_var(VarName),
mercury_type_to_mlds_type(ModuleInfo, Type),
GCStatement, mlds_make_context(Context)).
ml_gen_mlds_var_decl(DataName, MLDS_Type, GCStatement, Context) =
ml_gen_mlds_var_decl_init(DataName, MLDS_Type, no_initializer, GCStatement,
Context).
ml_gen_mlds_var_decl_init(DataName, MLDS_Type, Initializer, GCStatement,
Context) = Defn :-
Name = entity_data(DataName),
EntityDefn = mlds_data(MLDS_Type, Initializer, GCStatement),
DeclFlags = ml_gen_local_var_decl_flags,
Defn = mlds_defn(Name, Context, DeclFlags, EntityDefn).
ml_gen_public_field_decl_flags = DeclFlags :-
Access = acc_public,
PerInstance = per_instance,
Virtuality = non_virtual,
Overridability = overridable,
Constness = modifiable,
Abstractness = concrete,
DeclFlags = init_decl_flags(Access, PerInstance,
Virtuality, Overridability, Constness, Abstractness).
ml_gen_local_var_decl_flags = DeclFlags :-
Access = acc_local,
PerInstance = per_instance,
Virtuality = non_virtual,
Overridability = overridable,
Constness = modifiable,
Abstractness = concrete,
DeclFlags = init_decl_flags(Access, PerInstance,
Virtuality, Overridability, Constness, Abstractness).
ml_var_name_to_string(mlds_var_name(Var, yes(Num))) =
Var ++ "_" ++ string.int_to_string(Num).
ml_var_name_to_string(mlds_var_name(Var, no)) = Var.
%-----------------------------------------------------------------------------%
%
% Code for dealing with fields.
%
% Given the user-specified field name, if any, and the argument number
% (starting from one), generate an MLDS field name.
%
ml_gen_field_name(MaybeFieldName, ArgNum) = FieldName :-
% If the programmer specified a field name, we use that,
% otherwise we just use `F' followed by the field number.
(
MaybeFieldName = yes(QualifiedFieldName),
FieldName = unqualify_name(QualifiedFieldName)
;
MaybeFieldName = no,
FieldName = "F" ++ string.int_to_string(ArgNum)
).
% Succeed iff the specified type must be boxed when used as a field.
% For the MLDS->C and MLDS->asm back-ends, we need to box types that are
% not word-sized, because the code for `arg' etc. in std_util.m rely
% on all arguments being word-sized.
% XXX Currently we box such types even for the other MLDS based back-ends
% that don't need it, e.g. the .NET back-end.
%
ml_must_box_field_type(ModuleInfo, Type) :-
module_info_get_globals(ModuleInfo, Globals),
globals.get_target(Globals, Target),
(
( Target = target_c
; Target = target_csharp
; Target = target_il
; Target = target_asm
; Target = target_x86_64
; Target = target_erlang
),
classify_type(ModuleInfo, Type) = Category,
MustBox = ml_must_box_field_type_category(Category)
;
Target = target_java,
MustBox = no
),
MustBox = yes.
:- func ml_must_box_field_type_category(type_ctor_category) = bool.
ml_must_box_field_type_category(CtorCat) = MustBox :-
(
( CtorCat = ctor_cat_builtin(cat_builtin_int)
; CtorCat = ctor_cat_builtin(cat_builtin_string)
; CtorCat = ctor_cat_builtin_dummy
; CtorCat = ctor_cat_higher_order
; CtorCat = ctor_cat_tuple
; CtorCat = ctor_cat_enum(_)
; CtorCat = ctor_cat_system(_)
; CtorCat = ctor_cat_variable
; CtorCat = ctor_cat_void
; CtorCat = ctor_cat_user(_)
),
MustBox = no
;
( CtorCat = ctor_cat_builtin(cat_builtin_char)
; CtorCat = ctor_cat_builtin(cat_builtin_float)
),
MustBox = yes
).
ml_gen_box_const_rvals(_, _, [], [], [], !GlobalData).
ml_gen_box_const_rvals(_, _, [], [_ | _], _, !GlobalData) :-
unexpected($module, $pred, "list length mismatch").
ml_gen_box_const_rvals(_, _, [_ | _], [], _, !GlobalData) :-
unexpected($module, $pred, "list length mismatch").
ml_gen_box_const_rvals(ModuleInfo, Context, [Type | Types], [Rval | Rvals],
[BoxedRval | BoxedRvals], !GlobalData) :-
ml_gen_box_const_rval(ModuleInfo, Context, Type, Rval, BoxedRval,
!GlobalData),
ml_gen_box_const_rvals(ModuleInfo, Context, Types, Rvals, BoxedRvals,
!GlobalData).
ml_gen_box_const_rval(ModuleInfo, Context, Type, Rval, BoxedRval,
!GlobalData) :-
(
( Type = mercury_type(type_variable(_, _), _, _)
; Type = mlds_generic_type
)
->
BoxedRval = Rval
;
% For the MLDS->C and MLDS->asm back-ends, we need to handle floats
% specially, since boxed floats normally get heap allocated, whereas
% for other types boxing is just a cast (casts are OK in static
% initializers, but calls to malloc() are not).
( Type = mercury_type(builtin_type(builtin_type_float), _, _)
; Type = mlds_native_float_type
),
module_info_get_globals(ModuleInfo, Globals),
globals.get_target(Globals, Target),
( Target = target_c
; Target = target_asm
; Target = target_x86_64
)
->
% Generate a local static constant for this float.
module_info_get_name(ModuleInfo, ModuleName),
MLDS_ModuleName = mercury_module_name_to_mlds(ModuleName),
Initializer = init_obj(Rval),
ml_gen_static_scalar_const_addr(MLDS_ModuleName, "float", Type,
Initializer, Context, ConstAddrRval, !GlobalData),
% Return as the boxed rval the address of that constant,
% cast to mlds_generic_type.
BoxedRval = ml_unop(cast(mlds_generic_type), ConstAddrRval)
;
BoxedRval = ml_unop(box(Type), Rval)
).
ml_gen_box_or_unbox_rval(ModuleInfo, SourceType, DestType, BoxPolicy, VarRval,
ArgRval) :-
% Convert VarRval, of type SourceType, to ArgRval, of type DestType.
(
BoxPolicy = always_boxed,
ArgRval = VarRval
;
BoxPolicy = native_if_possible,
(
% If converting from polymorphic type to concrete type, then unbox.
SourceType = type_variable(_, _),
DestType \= type_variable(_, _)
->
MLDS_DestType = mercury_type_to_mlds_type(ModuleInfo, DestType),
ArgRval = ml_unop(unbox(MLDS_DestType), VarRval)
;
% If converting from concrete type to polymorphic type, then box.
SourceType \= type_variable(_, _),
DestType = type_variable(_, _)
->
MLDS_SourceType =
mercury_type_to_mlds_type(ModuleInfo, SourceType),
ArgRval = ml_unop(box(MLDS_SourceType), VarRval)
;
% If converting to float, cast to mlds_generic_type and then unbox.
DestType = builtin_type(builtin_type_float),
SourceType \= builtin_type(builtin_type_float)
->
MLDS_DestType = mercury_type_to_mlds_type(ModuleInfo, DestType),
ArgRval = ml_unop(unbox(MLDS_DestType),
ml_unop(cast(mlds_generic_type), VarRval))
;
% If converting from float, box and then cast the result.
SourceType = builtin_type(builtin_type_float),
DestType \= builtin_type(builtin_type_float)
->
MLDS_SourceType =
mercury_type_to_mlds_type(ModuleInfo, SourceType),
MLDS_DestType = mercury_type_to_mlds_type(ModuleInfo, DestType),
ArgRval = ml_unop(cast(MLDS_DestType),
ml_unop(box(MLDS_SourceType), VarRval))
;
% If converting from an array(T) to array(X) where X is a concrete
% instance, we should insert a cast to the concrete instance.
% Also when converting to array(T) from array(X) we should cast
% to array(T).
type_to_ctor_and_args(SourceType, SourceTypeCtor, SourceTypeArgs),
type_to_ctor_and_args(DestType, DestTypeCtor, DestTypeArgs),
(
type_ctor_is_array(SourceTypeCtor),
SourceTypeArgs = [type_variable(_, _)]
;
type_ctor_is_array(DestTypeCtor),
DestTypeArgs = [type_variable(_, _)]
),
% Don't insert redundant casts if the types are the same, since
% the extra assignments introduced can inhibit tail call
% optimisation.
SourceType \= DestType
->
MLDS_DestType = mercury_type_to_mlds_type(ModuleInfo, DestType),
ArgRval = ml_unop(cast(MLDS_DestType), VarRval)
;
% If converting from one concrete type to a different one, then
% cast. This is needed to handle construction/deconstruction
% unifications for no_tag types.
%
\+ type_unify(SourceType, DestType, [], map.init, _)
->
MLDS_DestType = mercury_type_to_mlds_type(ModuleInfo, DestType),
ArgRval = ml_unop(cast(MLDS_DestType), VarRval)
;
% Otherwise leave unchanged.
ArgRval = VarRval
)
).
ml_gen_box_or_unbox_lval(CallerType, CalleeType, BoxPolicy, VarLval, VarName,
Context, ForClosureWrapper, ArgNum, ArgLval, ConvDecls,
ConvInputStatements, ConvOutputStatements, !Info) :-
% First see if we can just convert the lval as an rval;
% if no boxing/unboxing is required, then ml_box_or_unbox_rval
% will return its argument unchanged, and so we're done.
ml_gen_info_get_module_info(!.Info, ModuleInfo),
ml_gen_box_or_unbox_rval(ModuleInfo, CalleeType, CallerType, BoxPolicy,
ml_lval(VarLval), BoxedRval),
( BoxedRval = ml_lval(VarLval) ->
ArgLval = VarLval,
ConvDecls = [],
ConvInputStatements = [],
ConvOutputStatements = []
;
% If that didn't work, then we need to declare a fresh variable
% to use as the arg, and to generate statements to box/unbox
% that fresh arg variable and assign it to/from the output
% argument whose address we were passed.
% Generate a declaration for the fresh variable.
%
% Note that generating accurate GC tracing code for this
% variable requires some care, because CalleeType might be a
% type variable from the callee, not from the caller,
% and we can't generate type_infos for type variables
% from the callee. Hence we need to call the version of
% ml_gen_gc_statement which takes two types:
% the CalleeType is used to determine the type for the
% temporary variable declaration, but the CallerType is
% used to construct the type_info.
ml_gen_info_new_conv_var(ConvVarSeq, !Info),
VarName = mlds_var_name(VarNameStr, MaybeNum),
ConvVarSeq = conv_seq(ConvVarNum),
string.format("conv%d_%s", [i(ConvVarNum), s(VarNameStr)],
ConvVarName),
ArgVarName = mlds_var_name(ConvVarName, MaybeNum),
ml_gen_type(!.Info, CalleeType, MLDS_CalleeType),
(
ForClosureWrapper = yes,
% For closure wrappers, the argument type_infos are
% stored in the `type_params' local, so we need to
% handle the GC tracing code specially
( CallerType = type_variable(_, _) ->
ml_gen_local_for_output_arg(ArgVarName, CalleeType, ArgNum,
Context, ArgVarDecl, !Info)
;
unexpected($module, $pred,
"invalid CalleeType for closure wrapper")
)
;
ForClosureWrapper = no,
ml_gen_gc_statement_poly(ArgVarName, CalleeType, CallerType,
Context, GC_Statements, !Info),
ArgVarDecl = ml_gen_mlds_var_decl(mlds_data_var(ArgVarName),
MLDS_CalleeType, GC_Statements, mlds_make_context(Context))
),
ConvDecls = [ArgVarDecl],
% Create the lval for the variable and use it for the argument lval.
ml_gen_var_lval(!.Info, ArgVarName, MLDS_CalleeType, ArgLval),
CallerIsDummy = check_dummy_type(ModuleInfo, CallerType),
(
CallerIsDummy = is_dummy_type,
% If it is a dummy argument type (e.g. io.state),
% then we don't need to bother assigning it.
ConvInputStatements = [],
ConvOutputStatements = []
;
CallerIsDummy = is_not_dummy_type,
% Generate statements to box/unbox the fresh variable and assign it
% to/from the output argument whose address we were passed.
% Assign to the freshly generated arg variable.
ml_gen_box_or_unbox_rval(ModuleInfo, CallerType, CalleeType,
BoxPolicy, ml_lval(VarLval), ConvertedVarRval),
AssignInputStatement = ml_gen_assign(ArgLval, ConvertedVarRval,
Context),
ConvInputStatements = [AssignInputStatement],
% Assign from the freshly generated arg variable.
ml_gen_box_or_unbox_rval(ModuleInfo, CalleeType, CallerType,
BoxPolicy, ml_lval(ArgLval), ConvertedArgRval),
AssignOutputStatement = ml_gen_assign(VarLval, ConvertedArgRval,
Context),
ConvOutputStatements = [AssignOutputStatement]
)
).
ml_gen_local_for_output_arg(VarName, Type, ArgNum, Context, LocalVarDefn,
!Info) :-
% Generate a declaration for a corresponding local variable.
% However, don't use the normal GC tracing code; instead,
% we need to get the typeinfo from `type_params', using the following code:
%
% MR_TypeInfo type_info;
% MR_MemoryList allocated_memory_cells = NULL;
% type_info = MR_make_type_info_maybe_existq(type_params,
% closure_layout->MR_closure_arg_pseudo_type_info[<ArgNum> - 1],
% NULL, NULL, &allocated_memory_cells);
%
% private_builtin__gc_trace_1_0(type_info, &<VarName>);
%
% MR_deallocate(allocated_memory_cells);
%
MLDS_Context = mlds_make_context(Context),
ClosureLayoutPtrName = mlds_var_name("closure_layout_ptr", no),
% This type is really `const MR_Closure_Layout *', but there's no easy
% way to represent that in the MLDS; using MR_Box instead works fine.
ClosureLayoutPtrType = mlds_generic_type,
ml_gen_var_lval(!.Info, ClosureLayoutPtrName, ClosureLayoutPtrType,
ClosureLayoutPtrLval),
TypeParamsName = mlds_var_name("type_params", no),
% This type is really MR_TypeInfoParams, but there's no easy way to
% represent that in the MLDS; using MR_Box instead works fine.
TypeParamsType = mlds_generic_type,
ml_gen_var_lval(!.Info, TypeParamsName, TypeParamsType, TypeParamsLval),
TypeInfoName = mlds_var_name("type_info", no),
% The type for this should match the type of the first argument
% of private_builtin.gc_trace/1, i.e. `mutvar(T)', which is a no_tag type
% whose representation is c_pointer.
ml_gen_info_get_module_info(!.Info, ModuleInfo),
TypeInfoMercuryType = c_pointer_type,
TypeInfoType = mercury_type_to_mlds_type(ModuleInfo, TypeInfoMercuryType),
ml_gen_var_lval(!.Info, TypeInfoName, TypeInfoType, TypeInfoLval),
TypeInfoDecl = ml_gen_mlds_var_decl(mlds_data_var(TypeInfoName),
TypeInfoType, gc_no_stmt, MLDS_Context),
ml_gen_gc_statement_with_typeinfo(VarName, Type, ml_lval(TypeInfoLval),
Context, GCStatement0, !Info),
(
(
GCStatement0 = gc_trace_code(CallTraceFuncCode)
;
GCStatement0 = gc_initialiser(CallTraceFuncCode)
),
MakeTypeInfoCode = ml_stmt_atomic(inline_target_code(ml_target_c, [
raw_target_code("{\n", []),
raw_target_code("MR_MemoryList allocated_mem = NULL;\n", []),
target_code_output(TypeInfoLval),
raw_target_code(" = (MR_C_Pointer) " ++
"MR_make_type_info_maybe_existq(\n\t", []),
target_code_input(ml_lval(TypeParamsLval)),
raw_target_code(", ((MR_Closure_Layout *)\n\t", []),
target_code_input(ml_lval(ClosureLayoutPtrLval)),
raw_target_code(string.format(")->" ++
"MR_closure_arg_pseudo_type_info[%d - 1],\n\t" ++
"NULL, NULL, &allocated_mem);\n",
[i(ArgNum)]), [])
])),
DeallocateCode = ml_stmt_atomic(inline_target_code(ml_target_c, [
raw_target_code("MR_deallocate(allocated_mem);\n", []),
raw_target_code("}\n", [])
])),
GCTraceCode = ml_stmt_block([TypeInfoDecl], [
statement(MakeTypeInfoCode, MLDS_Context),
CallTraceFuncCode,
statement(DeallocateCode, MLDS_Context)
]),
GCStatement = gc_trace_code(statement(GCTraceCode, MLDS_Context))
;
GCStatement0 = gc_no_stmt,
GCStatement = GCStatement0
),
LocalVarDefn = ml_gen_mlds_var_decl(mlds_data_var(VarName),
mercury_type_to_mlds_type(ModuleInfo, Type),
GCStatement, MLDS_Context).
%-----------------------------------------------------------------------------%
%
% Code for handling success and failure.
%
ml_gen_success(model_det, _, Statements, !Info) :-
%
% det succeed:
% <do true>
% ===>
% /* just fall through */
%
Statements = [].
ml_gen_success(model_semi, Context, [SetSuccessTrue], !Info) :-
%
% semidet succeed:
% <do true>
% ===>
% succeeded = MR_TRUE;
%
ml_gen_set_success(!.Info, ml_const(mlconst_true), Context,
SetSuccessTrue).
ml_gen_success(model_non, Context, [CallCont], !Info) :-
%
% nondet succeed:
% <true && SUCCEED()>
% ===>
% SUCCEED()
%
ml_gen_call_current_success_cont(Context, CallCont, !Info).
ml_gen_failure(model_det, _, _, !Info) :-
unexpected($module, $pred, "`fail' has determinism `det'").
ml_gen_failure(model_semi, Context, [SetSuccessFalse], !Info) :-
%
% semidet fail:
% <do fail>
% ===>
% succeeded = MR_FALSE;
%
ml_gen_set_success(!.Info, ml_const(mlconst_false), Context,
SetSuccessFalse).
ml_gen_failure(model_non, _, Statements, !Info) :-
%
% nondet fail:
% <fail && SUCCEED()>
% ===>
% /* just fall through */
%
Statements = [].
%-----------------------------------------------------------------------------%
ml_gen_succeeded_var_decl(Context) =
ml_gen_mlds_var_decl(mlds_data_var(mlds_var_name("succeeded", no)),
mlds_native_bool_type, gc_no_stmt, Context).
ml_success_lval(Info, SucceededLval) :-
ml_gen_var_lval(Info, mlds_var_name("succeeded", no),
mlds_native_bool_type, SucceededLval).
ml_gen_test_success(Info, SucceededRval) :-
ml_success_lval(Info, SucceededLval),
SucceededRval = ml_lval(SucceededLval).
ml_gen_set_success(Info, Value, Context, Statement) :-
ml_success_lval(Info, Succeeded),
Statement = ml_gen_assign(Succeeded, Value, Context).
%-----------------------------------------------------------------------------%
% Generate the name for the specified `cond_<N>' variable.
%
:- func ml_gen_cond_var_name(cond_seq) = mlds_var_name.
ml_gen_cond_var_name(CondVar) = VarName :-
CondVar = cond_seq(CondNum),
CondName = string.append("cond_", string.int_to_string(CondNum)),
VarName = mlds_var_name(CondName, no).
ml_gen_cond_var_decl(CondVar, Context) =
ml_gen_mlds_var_decl(mlds_data_var(ml_gen_cond_var_name(CondVar)),
mlds_native_bool_type, gc_no_stmt, Context).
ml_cond_var_lval(Info, CondVar, CondVarLval) :-
ml_gen_var_lval(Info, ml_gen_cond_var_name(CondVar),
mlds_native_bool_type, CondVarLval).
ml_gen_test_cond_var(Info, CondVar, CondVarRval) :-
ml_cond_var_lval(Info, CondVar, CondVarLval),
CondVarRval = ml_lval(CondVarLval).
ml_gen_set_cond_var(Info, CondVar, Value, Context, Statement) :-
ml_cond_var_lval(Info, CondVar, CondVarLval),
Statement = ml_gen_assign(CondVarLval, Value, Context).
%-----------------------------------------------------------------------------%
ml_initial_cont(Info, OutputVarLvals0, OutputVarTypes0, Cont) :-
ml_gen_info_get_module_info(Info, ModuleInfo),
ml_skip_dummy_argument_types(OutputVarTypes0, OutputVarLvals0,
ModuleInfo, OutputVarTypes, OutputVarLvals),
list.map(ml_gen_type(Info), OutputVarTypes, MLDS_OutputVarTypes),
% We expect OutputVarlvals0 and OutputVarTypes0 to be empty if
% `--nondet-copy-out' is not enabled.
ml_gen_var_lval(Info, mlds_var_name("cont", no),
mlds_cont_type(MLDS_OutputVarTypes), ContLval),
ml_gen_var_lval(Info, mlds_var_name("cont_env_ptr", no),
mlds_generic_env_ptr_type, ContEnvLval),
Cont = success_cont(ml_lval(ContLval), ml_lval(ContEnvLval),
MLDS_OutputVarTypes, OutputVarLvals).
:- pred ml_skip_dummy_argument_types(list(mer_type)::in, list(T)::in,
module_info::in, list(mer_type)::out, list(T)::out) is det.
ml_skip_dummy_argument_types([], [], _, [], []).
ml_skip_dummy_argument_types([Type | Types0], [Var | Vars0], ModuleInfo,
Types, Vars) :-
ml_skip_dummy_argument_types(Types0, Vars0, ModuleInfo, Types1, Vars1),
IsDummy = check_dummy_type(ModuleInfo, Type),
(
IsDummy = is_dummy_type,
Types = Types1,
Vars = Vars1
;
IsDummy = is_not_dummy_type,
Types = [Type | Types1],
Vars = [Var | Vars1]
).
ml_skip_dummy_argument_types([_ | _], [], _, _, _) :-
unexpected($module, $pred, "length mismatch").
ml_skip_dummy_argument_types([], [_ | _], _, _, _) :-
unexpected($module, $pred, "length mismatch").
ml_gen_call_current_success_cont(Context, Statement, !Info) :-
ml_gen_info_current_success_cont(!.Info, SuccCont),
SuccCont = success_cont(FuncRval, EnvPtrRval, ArgTypes0, ArgLvals0),
ArgRvals0 = list.map(func(Lval) = ml_lval(Lval), ArgLvals0),
ml_gen_info_use_gcc_nested_functions(!.Info, UseNestedFuncs),
(
UseNestedFuncs = yes,
ArgTypes = ArgTypes0,
ArgRvals = ArgRvals0
;
UseNestedFuncs = no,
ArgTypes = ArgTypes0 ++ [mlds_generic_env_ptr_type],
ArgRvals =ArgRvals0 ++ [EnvPtrRval]
),
RetTypes = [],
Signature = mlds_func_signature(ArgTypes, RetTypes),
ObjectRval = no,
RetLvals = [],
CallKind = ordinary_call,
Stmt = ml_stmt_call(Signature, FuncRval, ObjectRval, ArgRvals, RetLvals,
CallKind),
Statement = statement(Stmt, mlds_make_context(Context)).
ml_gen_call_current_success_cont_indirectly(Context, Statement, !Info) :-
% XXX this code is quite similar to some of the existing code
% for calling continuations when doing copy-in/copy-out.
% Sharing code should be investigated.
% We generate a call to the success continuation, just as usual.
ml_gen_info_current_success_cont(!.Info, SuccCont),
SuccCont = success_cont(ContinuationFuncRval, EnvPtrRval,
ArgTypes0, ArgLvals0),
ArgRvals0 = list.map(func(Lval) = ml_lval(Lval), ArgLvals0),
ml_gen_info_use_gcc_nested_functions(!.Info, UseNestedFuncs),
(
UseNestedFuncs = yes,
ArgTypes = ArgTypes0,
ArgRvals = ArgRvals0
;
UseNestedFuncs = no,
ArgTypes = ArgTypes0 ++ [mlds_generic_env_ptr_type],
ArgRvals = ArgRvals0 ++ [EnvPtrRval]
),
RetTypes = [],
Signature = mlds_func_signature(ArgTypes, RetTypes),
ObjectRval = no,
RetLvals = [],
CallKind = ordinary_call,
MLDS_Context = mlds_make_context(Context),
ml_gen_info_get_module_name(!.Info, PredModule),
MLDS_Module = mercury_module_name_to_mlds(PredModule),
% We generate a nested function that does the real call to the
% continuation.
%
% All we do is change the call rvals to be the input variables, and the
% func rval to be the input variable for the continuation.
%
% Note that ml_gen_cont_params does not fill in the gc_statement
% for the parameters. This is OK, because the parameters will not be used
% again after the call. (Also currently this is only used for IL, for which
% GC is the .NET CLR implementation's problem, not ours.)
%
ml_gen_cont_params(ArgTypes0, InnerFuncParams0, !Info),
InnerFuncParams0 = mlds_func_params(InnerArgs0, Rets),
InnerArgRvals = list.map(
(func(mlds_argument(Data, Type, _GC) ) = Lval :-
( Data = entity_data(mlds_data_var(VarName)) ->
Lval = ml_lval(ml_var(qual(MLDS_Module, module_qual, VarName),
Type))
;
unexpected($module, $pred,
"expected variable name in continuation parameters")
)
), InnerArgs0),
InnerFuncArgType = mlds_cont_type(ArgTypes0),
PassedContVarName = mlds_var_name("passed_cont", no),
% The passed_cont variable always points to code, not to heap,
% so the GC never needs to trace it.
PassedContGCStatement = gc_no_stmt,
PassedContArg = mlds_argument(
entity_data(mlds_data_var(PassedContVarName)),
InnerFuncArgType, PassedContGCStatement),
InnerFuncRval = ml_lval(ml_var(qual(MLDS_Module, module_qual,
PassedContVarName), InnerFuncArgType)),
InnerFuncParams = mlds_func_params([PassedContArg | InnerArgs0], Rets),
InnerStmt = ml_stmt_call(Signature, InnerFuncRval, ObjectRval,
InnerArgRvals, RetLvals, CallKind),
InnerStatement = statement(InnerStmt, MLDS_Context),
ml_gen_label_func(!.Info, 1, InnerFuncParams, Context, InnerStatement,
Defn),
ProxySignature = mlds_func_signature([InnerFuncArgType | ArgTypes],
RetTypes),
ProxyArgRvals = [ContinuationFuncRval | ArgRvals],
(
Defn = mlds_defn(EntityName, _, _, EntityDefn),
EntityName = entity_function(PredLabel, ProcId, yes(SeqNum), _),
EntityDefn = mlds_function(_, _, body_defined_here(_), _, _)
->
% We call the proxy function.
ProcLabel = mlds_proc_label(PredLabel, ProcId),
QualProcLabel = qual(MLDS_Module, module_qual, ProcLabel),
ProxyFuncRval = ml_const(mlconst_code_addr(
code_addr_internal(QualProcLabel, SeqNum, ProxySignature))),
% Put it inside a block where we call it.
Stmt = ml_stmt_call(ProxySignature, ProxyFuncRval, ObjectRval,
ProxyArgRvals, RetLvals, CallKind),
BlockStmt = ml_stmt_block([Defn], [statement(Stmt, MLDS_Context)]),
Statement = statement(BlockStmt, MLDS_Context)
;
unexpected($module, $pred,
"success continuation generated was not a function")
).
%-----------------------------------------------------------------------------%
%
% Routines for dealing with the environment pointer used for nested functions.
%
ml_get_env_ptr(Info, ml_lval(EnvPtrLval)) :-
ml_gen_var_lval(Info, mlds_var_name("env_ptr", no), mlds_unknown_type,
EnvPtrLval).
ml_declare_env_ptr_arg(mlds_argument(Name, Type, GCStatement)) :-
Name = entity_data(mlds_data_var(mlds_var_name("env_ptr_arg", no))),
Type = mlds_generic_env_ptr_type,
% The env_ptr_arg always points to the stack, since continuation
% environments are always allocated on the stack (unless
% put_nondet_env_on_heap is true, which won't be the case when
% doing our own GC -- this is enforced in handle_options.m).
% So the GC doesn't need to trace it.
GCStatement = gc_no_stmt.
%-----------------------------------------------------------------------------%
% This function returns the offset to add to the argument
% number of a closure arg to get its field number.
% field 0 is the closure layout
% field 1 is the closure address
% field 2 is the number of arguments
% field 3 is the 1st argument field
% field 4 is the 2nd argument field,
% etc.
% Hence the offset to add to the argument number
% to get the field number is 2.
%
ml_closure_arg_offset = 2.
% This function returns the offset to add to the argument
% number of a typeclass_info arg to get its field number.
% The Nth extra argument to pass to the method is
% in field N of the typeclass_info, so the offset is zero.
%
ml_typeclass_info_arg_offset = 0.
% This function returns the offset to add to the method number
% for a type class method to get its field number within the
% base_typeclass_info.
% field 0 is num_extra
% field 1 is num_constraints
% field 2 is num_superclasses
% field 3 is class_arity
% field 4 is num_methods
% field 5 is the 1st method
% field 6 is the 2nd method
% etc.
% (See the base_typeclass_info type in rtti.m or the
% description in notes/type_class_transformation.html for
% more information about the layout of base_typeclass_infos.)
% Hence the offset is 4.
%
ml_base_typeclass_info_method_offset = 4.
%-----------------------------------------------------------------------------%
%
% Routines for dealing with lookup tables.
%
ml_generate_constants_for_arms(_Vars, [], [], !Info).
ml_generate_constants_for_arms(Vars, [Goal | Goals], [Soln | Solns], !Info) :-
ml_generate_constants_for_arm(Vars, Goal, Soln, !Info),
ml_generate_constants_for_arms(Vars, Goals, Solns, !Info).
ml_generate_constants_for_arm(Vars, Goal, Soln, !Info) :-
ml_gen_info_get_const_var_map(!.Info, InitConstVarMap),
ml_gen_goal(model_det, Goal, _Decls, _Statements, !Info),
ml_gen_info_get_const_var_map(!.Info, FinalConstVarMap),
list.map(lookup_ground_rval(FinalConstVarMap), Vars, Soln),
ml_gen_info_set_const_var_map(InitConstVarMap, !Info).
:- pred lookup_ground_rval(ml_ground_term_map::in, prog_var::in,
mlds_rval::out) is det.
lookup_ground_rval(FinalConstVarMap, Var, Rval) :-
% We can do a map.lookup instead of a map.search here because
% - we execute this code only if we have already determined that
% goal_is_conj_of_unify succeeds for this arm,
% - we don't even start looking for lookup switches unless we know
% that the mark_static_terms pass has been run, and
% - for every arm on which goal_is_conj_of_unify succeeds,
% mark_static_terms will mark all the variables to which Var
% may be bound as being constructed statically. (There can be no need
% to construct them dynamically, since all the arm's nonlocals are
% output, which means none of them can be input.)
map.lookup(FinalConstVarMap, Var, GroundTerm),
GroundTerm = ml_ground_term(Rval, _, _).
ml_generate_field_assign(OutVarLval, FieldType, FieldId, VectorCommon,
StructType, IndexRval, Context, Statement, !Info) :-
BaseRval = ml_vector_common_row(VectorCommon, IndexRval),
FieldLval = ml_field(yes(0), BaseRval, FieldId, FieldType, StructType),
AtomicStmt = assign(OutVarLval, ml_lval(FieldLval)),
Stmt = ml_stmt_atomic(AtomicStmt),
Statement = statement(Stmt, Context).
ml_generate_field_assigns(OutVars, FieldTypes, FieldIds, VectorCommon,
StructType, IndexRval, Context, Statements, !Info) :-
(
OutVars = [],
FieldTypes = [],
FieldIds = []
->
Statements = []
;
OutVars = [HeadOutVar | TailOutVars],
FieldTypes = [HeadFieldType | TailFieldTypes],
FieldIds = [HeadFieldId | TailFieldIds]
->
ml_gen_var(!.Info, HeadOutVar, HeadOutVarLval),
ml_generate_field_assign(HeadOutVarLval, HeadFieldType, HeadFieldId,
VectorCommon, StructType, IndexRval, Context, HeadStatement,
!Info),
ml_generate_field_assigns(TailOutVars, TailFieldTypes, TailFieldIds,
VectorCommon, StructType, IndexRval, Context, TailStatements,
!Info),
Statements = [HeadStatement | TailStatements]
;
unexpected($module, $pred, "mismatched lists")
).
%-----------------------------------------------------------------------------%
%
% Miscellaneous routines.
%
get_copy_out_option(Globals, CodeModel) = CopyOut :-
(
CodeModel = model_non,
globals.lookup_bool_option(Globals, nondet_copy_out, CopyOut)
;
( CodeModel = model_det
; CodeModel = model_semi
),
globals.lookup_bool_option(Globals, det_copy_out, CopyOut)
).
fixup_builtin_module(ModuleName0) = ModuleName :-
( ModuleName0 = unqualified("") ->
ModuleName = mercury_public_builtin_module
;
ModuleName = ModuleName0
).
%-----------------------------------------------------------------------------%
:- end_module ml_backend.ml_code_util.
%-----------------------------------------------------------------------------%
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