Ejemplo n.º 1
0
    def visit_For(self, node):
        """
        Create For representation for Cxx generation.

        Examples
        --------
        >> for i in range(10):
        >>     ... work ...

        Becomes

        >> typename returnable<decltype(builtins.range(10))>::type __iterX
           = builtins.range(10);
        >> ... possible container size reservation ...
        >> for (auto&& i: __iterX)
        >>     ... the work ...

        This function also handle assignment for local variables.

        We can notice that three kind of loop are possible:
        - Normal for loop on iterator
        - Autofor loop.
        - Normal for loop using integer variable iteration
        Kind of loop used depend on OpenMP, yield use and variable scope.
        """
        if not isinstance(node.target, ast.Name):
            raise PythranSyntaxError(
                "Using something other than an identifier as loop target",
                node.target)
        target = self.visit(node.target)

        # Handle the body of the for loop
        loop_body = Block([self.visit(stmt) for stmt in node.body])

        # Declare local variables at the top of the loop body
        loop_body = self.process_locals(node, loop_body, node.target.id)
        iterable = self.visit(node.iter)

        if self.can_use_c_for(node):
            header, loop = self.gen_c_for(node, target, loop_body)
        else:

            if self.can_use_autofor(node):
                header = []
                self.ldecls.remove(node.target.id)
                autofor = AutoFor(target, iterable, loop_body)
                loop = [self.process_omp_attachements(node, autofor)]
            else:
                # Iterator declaration
                local_iter = "__iter{0}".format(id(node))
                local_iter_decl = self.types.builder.Assignable(
                    self.types[node.iter])

                self.handle_omp_for(node, local_iter)

                # Assign iterable
                # For C loop, it avoids issues
                # if the upper bound is assigned in the loop
                asgnt = self.make_assign(local_iter_decl, local_iter, iterable)
                header = [Statement(asgnt)]
                loop = self.gen_for(node, target, local_iter, local_iter_decl,
                                    loop_body)

        # For xxxComprehension, it is replaced by a for loop. In this case,
        # pre-allocate size of container.
        for comp in metadata.get(node, metadata.Comprehension):
            header.append(
                Statement("pythonic::utils::reserve({0},{1})".format(
                    comp.target, iterable)))

        return Block(header + loop)
Ejemplo n.º 2
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 def visit_Print(self, node):
     values = [self.visit(n) for n in node.values]
     stmt = Statement("pythonic::builtins::print{0}({1})".format(
         "" if node.nl else "_nonl", ", ".join(values)))
     return self.process_omp_attachements(node, stmt)
Ejemplo n.º 3
0
    def gen_c_for(self, node, local_iter, loop_body):
        """
        Create C For representation for Cxx generation.

        Examples
        --------
        >> for i in range(10):
        >>     ... do things ...

        Becomes

        >> for(long i = 0, __targetX = 10; i < __targetX; i += 1)
        >>     ... do things ...

        Or

        >> for i in range(10, 0, -1):
        >>     ... do things ...

        Becomes

        >> for(long i = 10, __targetX = 0; i > __targetX; i += -1)
        >>     ... do things ...


        It the case of not local variable, typing for `i` disappear
        """
        args = node.iter.args
        step = "1L" if len(args) <= 2 else self.visit(args[2])
        if len(args) == 1:
            lower_bound = "0L"
            upper_arg = 0
        else:
            lower_bound = self.visit(args[0])
            upper_arg = 1

        upper_type = iter_type = "long "
        upper_value = self.visit(args[upper_arg])
        if self.is_in_collapse(node, args[upper_arg]):
            upper_bound = upper_value  # compatible with collapse
        else:
            upper_bound = "__target{0}".format(id(node))

        # If variable is local to the for body keep it local...
        if node.target.id in self.scope[node] and not hasattr(self, 'yields'):
            loop = list()
        else:
            # For yield function, upper_bound is globals.
            iter_type = ""
            # Back one step to keep Python behavior (except for break)
            loop = [
                If("{} == {}".format(local_iter, upper_bound),
                   Statement("{} -= {}".format(local_iter, step)))
            ]

        comparison = self.handle_real_loop_comparison(args, local_iter,
                                                      upper_bound)

        forloop = For("{0} {1}={2}".format(iter_type, local_iter, lower_bound),
                      comparison, "{0} += {1}".format(local_iter,
                                                      step), loop_body)

        loop.insert(0, self.process_omp_attachements(node, forloop))

        # Store upper bound value if needed
        if upper_bound is upper_value:
            header = []
        else:
            assgnt = self.make_assign(upper_type, upper_bound, upper_value)
            header = [Statement(assgnt)]
        return header, loop
Ejemplo n.º 4
0
 def visit_Return(self, node):
     return Block([
         Statement("{0} = -1".format(CxxGenerator.StateHolder)),
         Statement("goto {0}".format(CxxGenerator.FinalStatement))
     ])
Ejemplo n.º 5
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 def visit_AugAssign(self, node):
     value = self.visit(node.value)
     target = self.visit(node.target)
     op = update_operator_to_lambda[type(node.op)]
     stmt = Statement(op(target, value)[1:-1])  # strip spurious parenthesis
     return self.process_omp_attachements(node, stmt)
Ejemplo n.º 6
0
    def visit_FunctionDef(self, node):

        self.fname = cxxid(node.name)
        tmp = self.prepare_functiondef_context(node)
        operator_body, formal_types, formal_args = tmp

        tmp = self.prepare_types(node)
        dflt_argv, dflt_argt, result_type, callable_type, pure_type = tmp

        # a function has a call operator to be called
        # and a default constructor to create instances
        fscope = "type{0}::".format("<{0}>".format(", ".join(formal_types))
                                    if formal_types
                                    else "")
        ffscope = "{0}::{1}".format(self.fname, fscope)

        operator_declaration = [
            templatize(
                make_const_function_declaration(
                    self, node,
                    "typename {0}result_type".format(fscope),
                    "operator()",
                    formal_types, formal_args, dflt_argv),
                formal_types,
                dflt_argt),
            EmptyStatement()
            ]
        operator_signature = make_const_function_declaration(
            self, node,
            "typename {0}result_type".format(ffscope),
            "{0}::operator()".format(self.fname),
            formal_types, formal_args)
        ctx = CachedTypeVisitor(self.lctx)
        operator_local_declarations = (
            [Statement("{0} {1}".format(
                self.types[self.local_names[k]].generate(ctx), cxxid(k)))
             for k in self.ldecls]
        )
        dependent_typedefs = ctx.typedefs()
        operator_definition = FunctionBody(
            templatize(operator_signature, formal_types),
            Block(dependent_typedefs +
                  operator_local_declarations +
                  operator_body)
            )

        ctx = CachedTypeVisitor()
        extra_typedefs = (
            [Typedef(Value(t.generate(ctx), t.name))
             for t in self.types[node][1]] +
            [Typedef(Value(
                result_type.generate(ctx),
                "result_type"))]
        )
        extra_typedefs = ctx.typedefs() + extra_typedefs
        return_declaration = [
            templatize(
                Struct("type", extra_typedefs),
                formal_types,
                dflt_argt
                )
            ]
        topstruct = Struct(self.fname,
                           [callable_type, pure_type] +
                           return_declaration +
                           operator_declaration)

        return [topstruct], [operator_definition]
Ejemplo n.º 7
0
    def visit_FunctionDef(self, node):
        tmp = self.prepare_functiondef_context(node)
        operator_body, formal_types, formal_args = tmp

        tmp = self.prepare_types(node)
        dflt_argv, dflt_argt, result_type, callable_type, pure_type = tmp

        # a generator has a call operator that returns the iterator
        next_name = "__generator__{0}".format(cxxid(node.name))
        instanciated_next_name = "{0}{1}".format(
            next_name,
            "<{0}>".format(", ".join(formal_types)) if formal_types else "")

        operator_body.append(
            Statement("{}: return result_type()".format(
                CxxGenerator.FinalStatement)))

        next_declaration = [
            FunctionDeclaration(Value("result_type", "next"), []),
            EmptyStatement()
        ]  # empty statement to force a comma ...

        # the constructors
        next_constructors = [
            FunctionBody(FunctionDeclaration(Value("", next_name), []),
                         Line(': pythonic::yielder() {}'))
        ]
        if formal_types:
            # If all parameters have a default value, we don't need default
            # constructor
            if dflt_argv and all(dflt_argv):
                next_constructors = list()
            next_constructors.append(
                FunctionBody(
                    make_function_declaration(self, node, "", next_name,
                                              formal_types, formal_args,
                                              dflt_argv),
                    Line(": {0} {{ }}".format(", ".join(
                        ["pythonic::yielder()"] +
                        ["{0}({0})".format(arg) for arg in formal_args])))))

        next_iterator = [
            FunctionBody(FunctionDeclaration(Value("void", "operator++"), []),
                         Block([Statement("next()")])),
            FunctionBody(
                FunctionDeclaration(
                    Value(
                        "typename {0}::result_type".format(
                            instanciated_next_name), "operator*"),
                    [], "const"),
                Block([ReturnStatement(CxxGenerator.StateValue)])),
            FunctionBody(
                FunctionDeclaration(
                    Value(
                        "pythonic::types::generator_iterator<{0}>".format(
                            next_name), "begin"), []),
                Block([
                    Statement("next()"),
                    ReturnStatement("pythonic::types::generator_iterator<{0}>"
                                    "(*this)".format(next_name))
                ])),
            FunctionBody(
                FunctionDeclaration(
                    Value(
                        "pythonic::types::generator_iterator<{0}>".format(
                            next_name), "end"), []),
                Block([
                    ReturnStatement(
                        "pythonic::types::generator_iterator<{0}>()".format(
                            next_name))
                ]))
        ]
        next_signature = templatize(
            FunctionDeclaration(
                Value(
                    "typename {0}::result_type".format(instanciated_next_name),
                    "{0}::next".format(instanciated_next_name)), []),
            formal_types)

        next_body = operator_body
        # the dispatch table at the entry point
        next_body.insert(
            0,
            Statement("switch({0}) {{ {1} }}".format(
                CxxGenerator.StateHolder,
                " ".join("case {0}: goto {1};".format(num, where)
                         for (num, where) in sorted(self.yields.values(),
                                                    key=lambda x: x[0])))))

        ctx = CachedTypeVisitor(self.lctx)
        next_members = ([
            Statement("{0} {1}".format(ft, fa))
            for (ft, fa) in zip(formal_types, formal_args)
        ] + [
            Statement("{0} {1}".format(
                self.types[self.local_names[k]].generate(ctx), k))
            for k in self.ldecls
        ] + [
            Statement("{0} {1}".format(v, k))
            for k, v in self.extra_declarations
        ] + [
            Statement("typename {0}::result_type {1}".format(
                instanciated_next_name, CxxGenerator.StateValue))
        ])

        extern_typedefs = [
            Typedef(Value(t.generate(ctx), t.name))
            for t in self.types[node][1]
        ]
        iterator_typedef = [
            Typedef(
                Value(
                    "pythonic::types::generator_iterator<{0}>".format(
                        "{0}<{1}>".format(next_name, ", ".join(formal_types)
                                          ) if formal_types else next_name),
                    "iterator")),
            Typedef(Value(result_type.generate(ctx), "value_type"))
        ]
        result_typedef = [
            Typedef(Value(result_type.generate(ctx), "result_type"))
        ]
        extra_typedefs = (ctx.typedefs() + extern_typedefs + iterator_typedef +
                          result_typedef)

        next_struct = templatize(
            Struct(
                next_name, extra_typedefs + next_members + next_constructors +
                next_iterator + next_declaration, "pythonic::yielder"),
            formal_types)
        next_definition = FunctionBody(next_signature, Block(next_body))

        operator_declaration = [
            templatize(
                make_const_function_declaration(self, node,
                                                instanciated_next_name,
                                                "operator()", formal_types,
                                                formal_args, dflt_argv),
                formal_types, dflt_argt),
            EmptyStatement()
        ]
        operator_signature = make_const_function_declaration(
            self, node, instanciated_next_name,
            "{0}::operator()".format(cxxid(node.name)), formal_types,
            formal_args)
        operator_definition = FunctionBody(
            templatize(operator_signature, formal_types),
            Block([
                ReturnStatement("{0}({1})".format(instanciated_next_name,
                                                  ", ".join(formal_args)))
            ]))

        topstruct_type = templatize(Struct("type", extra_typedefs),
                                    formal_types)
        topstruct = Struct(cxxid(node.name),
                           [topstruct_type, callable_type, pure_type] +
                           operator_declaration)

        return [next_struct, topstruct], [next_definition, operator_definition]
Ejemplo n.º 8
0
def generate_cxx(module_name, code, specs=None, optimizations=None,
                 module_dir=None):
    '''python + pythran spec -> c++ code
    returns a PythonModule object and an error checker

    the error checker can be used to print more detailed info on the origin of
    a compile error (e.g. due to bad typing)

    '''

    pm, ir, renamings, docstrings = front_middle_end(module_name, code,
                                                     optimizations, module_dir)

    # back-end
    content = pm.dump(Cxx, ir)

    # instantiate the meta program
    if specs is None:

        class Generable(object):
            def __init__(self, content):
                self.content = content

            def __str__(self):
                return str(self.content)

            generate = __str__

        mod = Generable(content)

        def error_checker():
            tog.typecheck(ir)

    else:

        # uniform typing
        if isinstance(specs, dict):
            specs = Spec(specs, {})

        def error_checker():
            types = tog.typecheck(ir)
            check_specs(ir, specs, renamings, types)

        specs.to_docstrings(docstrings)
        check_exports(ir, specs, renamings)

        if isinstance(code, bytes):
            code_bytes = code
        else:
            code_bytes = code.encode('ascii', 'ignore')
        metainfo = {'hash': hashlib.sha256(code_bytes).hexdigest(),
                    'version': __version__,
                    'date': datetime.now()}

        mod = PythonModule(module_name, docstrings, metainfo)
        mod.add_to_includes(
            Include("pythonic/core.hpp"),
            Include("pythonic/python/core.hpp"),
            # FIXME: only include these when needed
            Include("pythonic/types/bool.hpp"),
            Include("pythonic/types/int.hpp"),
            Line("#ifdef _OPENMP\n#include <omp.h>\n#endif")
        )
        mod.add_to_includes(*[Include(inc) for inc in
                              _extract_specs_dependencies(specs)])
        mod.add_to_includes(*content.body)
        mod.add_to_includes(
            Include("pythonic/python/exception_handler.hpp"),
        )

        def warded(module_name, internal_name):
            return pythran_ward + '{0}::{1}'.format(module_name, internal_name)

        for function_name, signatures in specs.functions.items():
            internal_func_name = renamings.get(function_name,
                                               function_name)
            # global variables are functions with no signatures :-)
            if not signatures:
                mod.add_global_var(function_name,
                                   "{}()()".format(warded(module_name,
                                                          internal_func_name)))

            for sigid, signature in enumerate(signatures):
                numbered_function_name = "{0}{1}".format(internal_func_name,
                                                         sigid)
                arguments_types = [pytype_to_ctype(t) for t in signature]
                arguments_names = HasArgument(internal_func_name).visit(ir)
                arguments = [n for n, _ in
                             zip(arguments_names, arguments_types)]
                name_fmt = pythran_ward + "{0}::{1}::type{2}"
                args_list = ", ".join(arguments_types)
                specialized_fname = name_fmt.format(module_name,
                                                    internal_func_name,
                                                    "<{0}>".format(args_list)
                                                    if arguments_names else "")
                result_type = "typename %s::result_type" % specialized_fname
                mod.add_pyfunction(
                    FunctionBody(
                        FunctionDeclaration(
                            Value(
                                result_type,
                                numbered_function_name),
                            [Value(t + '&&', a)
                             for t, a in zip(arguments_types, arguments)]),
                        Block([Statement("""
                            PyThreadState *_save = PyEval_SaveThread();
                            try {{
                                auto res = {0}()({1});
                                PyEval_RestoreThread(_save);
                                return res;
                            }}
                            catch(...) {{
                                PyEval_RestoreThread(_save);
                                throw;
                            }}
                            """.format(warded(module_name,
                                              internal_func_name),
                                       ', '.join(arguments)))])
                    ),
                    function_name,
                    arguments_types,
                    signature
                )

        for function_name, signature in specs.capsules.items():
            internal_func_name = renamings.get(function_name,
                                               function_name)

            arguments_types = [pytype_to_ctype(t) for t in signature]
            arguments_names = HasArgument(internal_func_name).visit(ir)
            arguments = [n for n, _ in
                         zip(arguments_names, arguments_types)]
            name_fmt = pythran_ward + "{0}::{1}::type{2}"
            args_list = ", ".join(arguments_types)
            specialized_fname = name_fmt.format(module_name,
                                                internal_func_name,
                                                "<{0}>".format(args_list)
                                                if arguments_names else "")
            result_type = "typename %s::result_type" % specialized_fname
            docstring = spec_to_string(function_name, signature)
            mod.add_capsule(
                FunctionBody(
                    FunctionDeclaration(
                        Value(result_type, function_name),
                        [Value(t, a)
                         for t, a in zip(arguments_types, arguments)]),
                    Block([ReturnStatement("{0}()({1})".format(
                        warded(module_name, internal_func_name),
                        ', '.join(arguments)))])
                ),
                function_name,
                docstring
            )

    return mod, error_checker
Ejemplo n.º 9
0
 def visit_Expr(self, node):
     stmt = Statement(self.visit(node.value))
     return self.process_locals(node,
                                self.process_omp_attachements(node, stmt))
Ejemplo n.º 10
0
    def visit_For(self, node):
        """
        Create For representation for Cxx generation.

        Examples
        --------
        >> for i in xrange(10):
        >>     ... work ...

        Becomes

        >> typename returnable<decltype(__builtin__.xrange(10))>::type __iterX
           = __builtin__.xrange(10);
        >> ... possible container size reservation ...
        >> for (typename decltype(__iterX)::iterator::reference i: __iterX)
        >>     ... the work ...

        This function also handle assignment for local variables.

        We can notice that three kind of loop are possible:
        - Normal for loop on iterator
        - Autofor loop.
        - Normal for loop using integer variable iteration
        Kind of loop used depend on OpenMP, yield use and variable scope.
        """
        if not isinstance(node.target, ast.Name):
            raise PythranSyntaxError(
                "Using something other than an identifier as loop target",
                node.target)
        target = self.visit(node.target)

        # Handle the body of the for loop
        loop_body = Block(map(self.visit, node.body))

        # Declare local variables at the top of the loop body
        loop_body = self.process_locals(node, loop_body, node.target.id)
        iterable = self.visit(node.iter)

        if self.can_use_c_for(node):
            header, loop = self.gen_c_for(node, target, loop_body)
        else:

            # Iterator declaration
            local_iter = "__iter{0}".format(len(self.break_handlers))
            local_iter_decl = Assignable(DeclType(iterable))

            self.handle_omp_for(node, local_iter)

            # For yield function, iterable is globals.
            if self.yields:
                self.extra_declarations.append((
                    local_iter,
                    local_iter_decl,
                ))
                local_iter_decl = ""

            # Assign iterable
            # For C loop, it avoid issue if upper bound is reassign in the loop
            header = [
                Statement("{0} {1} = {2}".format(local_iter_decl, local_iter,
                                                 iterable))
            ]
            if self.can_use_autofor(node):
                self.ldecls = {
                    d
                    for d in self.ldecls if d.id != node.target.id
                }
                autofor = AutoFor(target, local_iter, loop_body)
                loop = [self.process_omp_attachements(node, autofor)]
            else:
                loop = self.gen_for(node, target, local_iter, local_iter_decl,
                                    loop_body)

        # For xxxComprehension, it is replaced by a for loop. In this case,
        # pre-allocate size of container.
        for comp in metadata.get(node, metadata.Comprehension):
            header.append(
                Statement("pythonic::utils::reserve({0},{1})".format(
                    comp.target, iterable)))

        return Block(header + loop)
Ejemplo n.º 11
0
def generate_cxx(module_name, code, specs=None, optimizations=None):
    '''python + pythran spec -> c++ code
    returns a PythonModule object

    '''
    pm = PassManager(module_name)

    # front end
    ir, renamings, docstrings, has_init = frontend.parse(pm, code)

    # middle-end
    optimizations = (optimizations
                     or cfg.get('pythran', 'optimizations').split())
    optimizations = map(_parse_optimization, optimizations)
    refine(pm, ir, optimizations)

    # back-end
    content = pm.dump(Cxx, ir)

    # instanciate the meta program
    if specs is None:

        class Generable(object):
            def __init__(self, content):
                self.content = content

            def __str__(self):
                return str(self.content)

            generate = __str__

        mod = Generable(content)
    else:

        # uniform typing
        for fname, signatures in specs.items():
            if not isinstance(signatures, tuple):
                specs[fname] = (signatures, )

        # verify the pythran export are compatible with the code
        specs = expand_specs(specs)
        check_specs(ir, specs, renamings)
        specs_to_docstrings(specs, docstrings)

        metainfo = {
            'hash': hashlib.sha256(code).hexdigest(),
            'version': __version__,
            'date': datetime.now()
        }

        mod = PythonModule(module_name, docstrings, metainfo, has_init)
        mod.add_to_preamble(Define("BOOST_SIMD_NO_STRICT_ALIASING", "1"))
        mod.add_to_includes(
            Include("pythonic/core.hpp"),
            Include("pythonic/python/core.hpp"),
            # FIXME: only include these when needed
            Include("pythonic/types/bool.hpp"),
            Include("pythonic/types/int.hpp"),
            Line("#ifdef _OPENMP\n#include <omp.h>\n#endif"))
        mod.add_to_includes(*map(Include, _extract_specs_dependencies(specs)))
        mod.add_to_includes(*content.body)

        for function_name, signatures in specs.iteritems():
            internal_func_name = renamings.get(function_name, function_name)
            for sigid, signature in enumerate(signatures):
                numbered_function_name = "{0}{1}".format(
                    internal_func_name, sigid)
                arguments_types = [pytype_to_ctype(t) for t in signature]
                has_arguments = HasArgument(internal_func_name).visit(ir)
                arguments = [
                    "a{0}".format(i) for i in xrange(len(arguments_types))
                ]
                name_fmt = pythran_ward + "{0}::{1}::type{2}"
                args_list = ", ".join(arguments_types)
                specialized_fname = name_fmt.format(
                    module_name, internal_func_name,
                    "<{0}>".format(args_list) if has_arguments else "")
                result_type = "typename %s::result_type" % specialized_fname
                mod.add_function(
                    FunctionBody(
                        FunctionDeclaration(
                            Value(result_type, numbered_function_name), [
                                Value(t, a)
                                for t, a in zip(arguments_types, arguments)
                            ]),
                        Block([
                            Statement("return {0}()({1})".format(
                                pythran_ward + '{0}::{1}'.format(
                                    module_name, internal_func_name),
                                ', '.join(arguments)))
                        ])), function_name, arguments_types)
    return mod
Ejemplo n.º 12
0
    def gen_c_for(self, node, local_iter, loop_body):
        """
        Create C For representation for Cxx generation.

        Examples
        --------
        >> for i in xrange(10):
        >>     ... do things ...

        Becomes

        >> for(long i = 0, __targetX = 10; i < __targetX; i += 1)
        >>     ... do things ...

        Or

        >> for i in xrange(10, 0, -1):
        >>     ... do things ...

        Becomes

        >> for(long i = 10, __targetX = 0; i > __targetX; i += -1)
        >>     ... do things ...

        Or

        >> for i in xrange(a, b, c):
        >>     ... do things ...

        Becomes

        >> std::function<bool(int, int)> __cmpX = std::less<long>();
        >> if(c < 0)
        >>     __cmpX = std::greater<long>();
        >> for(long i = a, __targetX = b; __cmpX(i, __targetX); i += c)
        >>     ... do things ...

        It the case of not local variable, typing for `i` disappear
        """
        args = node.iter.args
        step = "1L" if len(args) <= 2 else self.visit(args[2])
        if len(args) == 1:
            lower_bound = "0L"
            upper_value = self.visit(args[0])
        else:
            lower_bound = self.visit(args[0])
            upper_value = self.visit(args[1])

        upper_bound = "__target{0}".format(len(self.break_handlers))

        upper_type = iter_type = "long "

        # If variable is local to the for body keep it local...
        if node.target.id in self.scope[node] and not self.yields:
            self.ldecls = {d for d in self.ldecls if d.id != node.target.id}
            loop = list()
        else:
            # For yield function, upper_bound is globals.
            if self.yields:
                self.extra_declarations.append((upper_bound, upper_type))
                upper_type = ""
            iter_type = ""
            # Back one step to keep Python behavior (except for break)
            loop = [
                If("{} == {}".format(local_iter, upper_bound),
                   Statement("{} -= {}".format(local_iter, step)))
            ]

        comparison, for_pos = self.handle_real_loop_comparison(
            args, loop, local_iter, upper_bound, step)

        forloop = For(
            "{0} {1} = {2}".format(iter_type, local_iter, lower_bound),
            comparison, "{0} += {1}".format(local_iter, step), loop_body)

        loop.insert(for_pos, self.process_omp_attachements(node, forloop))

        # Store upper bound value
        header = [
            Statement("{0} {1} = {2}".format(upper_type, upper_bound,
                                             upper_value))
        ]
        return header, loop
Ejemplo n.º 13
0
    def visit_FunctionDef(self, node):
        class CachedTypeVisitor:
            class CachedType:
                def __init__(self, s):
                    self.s = s

                def generate(self, ctx):
                    return self.s

            def __init__(self, other=None):
                if other:
                    self.cache = other.cache.copy()
                    self.rcache = other.rcache.copy()
                    self.mapping = other.mapping.copy()
                else:
                    self.cache = dict()
                    self.rcache = dict()
                    self.mapping = dict()

            def __call__(self, node):
                if node not in self.mapping:
                    t = node.generate(self)
                    if t in self.rcache:
                        self.mapping[node] = self.mapping[self.rcache[t]]
                        self.cache[node] = self.cache[self.rcache[t]]
                    else:
                        self.rcache[t] = node
                        self.mapping[node] = len(self.mapping)
                        self.cache[node] = t
                return CachedTypeVisitor.CachedType("__type{0}".format(
                    self.mapping[node]))

            def typedefs(self):
                l = sorted(self.mapping.items(), key=lambda x: x[1])
                L = list()
                visited = set()  # the same value must not be typedefed twice
                for k, v in l:
                    if v not in visited:
                        typename = "__type" + str(v)
                        L.append(Typedef(Value(self.cache[k], typename)))
                        visited.add(v)
                return L

        # prepare context and visit function body
        fargs = node.args.args

        formal_args = [arg.id for arg in fargs]
        formal_types = ["argument_type" + str(i) for i in xrange(len(fargs))]

        self.ldecls = set(self.passmanager.gather(LocalDeclarations, node))

        self.local_names = {sym.id for sym in self.ldecls}.union(formal_args)
        self.extra_declarations = []

        lctx = CachedTypeVisitor()
        self.local_types = {
            n: self.types[n].generate(lctx)
            for n in self.ldecls
        }
        self.local_types.update((n.id, t) for n, t in self.local_types.items())

        # choose one node among all the ones with the same name for each name
        self.ldecls = set({n.id: n for n in self.ldecls}.itervalues())

        # 0 is used as initial_state, thus the +1
        self.yields = {
            k: (1 + v, "yield_point{0}".format(1 + v))
            for (v, k) in enumerate(self.passmanager.gather(YieldPoints, node))
        }

        # gather body dump
        operator_body = map(self.visit, node.body)

        # compute arg dump
        default_arg_values = ([None] *
                              (len(node.args.args) - len(node.args.defaults)) +
                              [self.visit(n) for n in node.args.defaults])
        default_arg_types = ([None] *
                             (len(node.args.args) - len(node.args.defaults)) +
                             [self.types[n] for n in node.args.defaults])

        # compute type dump
        result_type = self.types[node][0]

        callable_type = Typedef(Value("void", "callable"))
        pure_type = (Typedef(Value("void", "pure"))
                     if node in self.pure_expressions else EmptyStatement())

        def make_function_declaration(rtype,
                                      name,
                                      ftypes,
                                      fargs,
                                      defaults=None,
                                      attributes=[]):
            if defaults is None:
                defaults = [None] * len(ftypes)
            arguments = list()
            for i, (t, a, d) in enumerate(zip(ftypes, fargs, defaults)):
                if self.yields:
                    rvalue_ref = ""
                elif self.argument_effects[node][i]:
                    rvalue_ref = "&&"
                else:
                    rvalue_ref = " const &"
                argument = Value(
                    t + rvalue_ref,
                    "{0}{1}".format(a, "= {0}".format(d) if d else ""))
                arguments.append(argument)
            return FunctionDeclaration(Value(rtype, name), arguments,
                                       *attributes)

        def make_const_function_declaration(rtype,
                                            name,
                                            ftypes,
                                            fargs,
                                            defaults=None):
            return make_function_declaration(rtype, name, ftypes, fargs,
                                             defaults, ["const"])

        if self.yields:  # generator case
            # a generator has a call operator that returns the iterator

            next_name = "__generator__{0}".format(node.name)
            instanciated_next_name = "{0}{1}".format(
                next_name, "<{0}>".format(", ".join(formal_types))
                if formal_types else "")

            operator_body.append(
                Statement("{0}: return result_type();".format(
                    Cxx.final_statement)))

            next_declaration = [
                FunctionDeclaration(Value("result_type", "next"), []),
                EmptyStatement()
            ]  # empty statement to force a comma ...

            # the constructors
            next_constructors = [
                FunctionBody(FunctionDeclaration(Value("", next_name), []),
                             Line(': pythonic::yielder() {}'))
            ]
            if formal_types:
                # If all parameters have a default value, we don't need default
                # constructor
                if default_arg_values and all(default_arg_values):
                    next_constructors = list()
                next_constructors.append(
                    FunctionBody(
                        make_function_declaration("", next_name, formal_types,
                                                  formal_args,
                                                  default_arg_values),
                        Line(": {0} {{ }}".format(
                            ", ".join(["pythonic::yielder()"] +
                                      map("{0}({0})".format, formal_args))))))

            next_iterator = [
                FunctionBody(
                    FunctionDeclaration(Value("void", "operator++"), []),
                    Block([Statement("next()")])),
                FunctionBody(
                    FunctionDeclaration(
                        Value(
                            "typename {0}::result_type".format(
                                instanciated_next_name), "operator*"), [],
                        "const"),
                    Block([ReturnStatement(Cxx.generator_state_value)])),
                FunctionBody(
                    FunctionDeclaration(
                        Value(
                            "pythonic::types::generator_iterator<{0}>".format(
                                next_name), "begin"), []),
                    Block([
                        Statement("next()"),
                        ReturnStatement(
                            "pythonic::types::generator_iterator<{0}>"
                            "(*this)".format(next_name))
                    ])),
                FunctionBody(
                    FunctionDeclaration(
                        Value(
                            "pythonic::types::generator_iterator<{0}>".format(
                                next_name), "end"), []),
                    Block([
                        ReturnStatement(
                            "pythonic::types::generator_iterator<{0}>()".
                            format(next_name))
                    ]))
            ]
            next_signature = templatize(
                FunctionDeclaration(
                    Value(
                        "typename {0}::result_type".format(
                            instanciated_next_name),
                        "{0}::next".format(instanciated_next_name)), []),
                formal_types)

            next_body = operator_body
            # the dispatch table at the entry point
            next_body.insert(
                0,
                Statement("switch({0}) {{ {1} }}".format(
                    Cxx.generator_state_holder,
                    " ".join("case {0}: goto {1};".format(num, where)
                             for (num,
                                  where) in sorted(self.yields.itervalues(),
                                                   key=lambda x: x[0])))))

            ctx = CachedTypeVisitor(lctx)
            next_members = ([
                Statement("{0} {1}".format(ft, fa))
                for (ft, fa) in zip(formal_types, formal_args)
            ] + [
                Statement("{0} {1}".format(self.types[k].generate(ctx), k.id))
                for k in self.ldecls
            ] + [
                Statement("{0} {1}".format(v, k))
                for k, v in self.extra_declarations
            ] + [
                Statement("typename {0}::result_type {1}".format(
                    instanciated_next_name, Cxx.generator_state_value))
            ])

            extern_typedefs = [
                Typedef(Value(t.generate(ctx), t.name))
                for t in self.types[node][1] if not t.isweak()
            ]
            iterator_typedef = [
                Typedef(
                    Value(
                        "pythonic::types::generator_iterator<{0}>".format(
                            "{0}<{1}>".format(next_name, ", ".join(
                                formal_types)) if formal_types else next_name),
                        "iterator")),
                Typedef(Value(result_type.generate(ctx), "value_type"))
            ]
            result_typedef = [
                Typedef(Value(result_type.generate(ctx), "result_type"))
            ]
            extra_typedefs = (ctx.typedefs() + extern_typedefs +
                              iterator_typedef + result_typedef)

            next_struct = templatize(
                Struct(
                    next_name, extra_typedefs + next_members +
                    next_constructors + next_iterator + next_declaration,
                    "pythonic::yielder"), formal_types)
            next_definition = FunctionBody(next_signature, Block(next_body))

            operator_declaration = [
                templatize(
                    make_const_function_declaration(instanciated_next_name,
                                                    "operator()", formal_types,
                                                    formal_args,
                                                    default_arg_values),
                    formal_types, default_arg_types),
                EmptyStatement()
            ]
            operator_signature = make_const_function_declaration(
                instanciated_next_name, "{0}::operator()".format(node.name),
                formal_types, formal_args)
            operator_definition = FunctionBody(
                templatize(operator_signature, formal_types),
                Block([
                    ReturnStatement("{0}({1})".format(instanciated_next_name,
                                                      ", ".join(formal_args)))
                ]))

            topstruct_type = templatize(Struct("type", extra_typedefs),
                                        formal_types)
            topstruct = Struct(node.name,
                               [topstruct_type, callable_type, pure_type] +
                               operator_declaration)

            self.declarations.append(next_struct)
            self.definitions.append(next_definition)

        else:  # regular function case
            # a function has a call operator to be called
            # and a default constructor to create instances
            fscope = "type{0}::".format("<{0}>".format(", ".join(formal_types))
                                        if formal_types else "")
            ffscope = "{0}::{1}".format(node.name, fscope)

            operator_declaration = [
                templatize(
                    make_const_function_declaration(
                        "typename {0}result_type".format(fscope), "operator()",
                        formal_types, formal_args, default_arg_values),
                    formal_types, default_arg_types),
                EmptyStatement()
            ]
            operator_signature = make_const_function_declaration(
                "typename {0}result_type".format(ffscope),
                "{0}::operator()".format(node.name), formal_types, formal_args)
            ctx = CachedTypeVisitor(lctx)
            operator_local_declarations = ([
                Statement("{0} {1}".format(self.types[k].generate(ctx), k.id))
                for k in self.ldecls
            ] + [
                Statement("{0} {1}".format(v, k))
                for k, v in self.extra_declarations
            ])
            dependent_typedefs = ctx.typedefs()
            operator_definition = FunctionBody(
                templatize(operator_signature, formal_types),
                Block(dependent_typedefs + operator_local_declarations +
                      operator_body))

            ctx = CachedTypeVisitor()
            extra_typedefs = ([
                Typedef(Value(t.generate(ctx), t.name))
                for t in self.types[node][1] if not t.isweak()
            ] + [Typedef(Value(result_type.generate(ctx), "result_type"))])
            extra_typedefs = ctx.typedefs() + extra_typedefs
            return_declaration = [
                templatize(Struct("type", extra_typedefs), formal_types,
                           default_arg_types)
            ]
            topstruct = Struct(node.name, [callable_type, pure_type] +
                               return_declaration + operator_declaration)

        self.declarations.append(topstruct)
        self.definitions.append(operator_definition)

        return EmptyStatement()
Ejemplo n.º 14
0
 def visit_Assert(self, node):
     params = [self.visit(node.test), node.msg and self.visit(node.msg)]
     sparams = ", ".join(map(strip_exp, filter(None, params)))
     return Statement("pythonic::pythran_assert({0})".format(sparams))
Ejemplo n.º 15
0
 def visit_Raise(self, node):
     exc = node.exc and self.visit(node.exc)
     return Statement("throw {0}".format(exc or ""))
Ejemplo n.º 16
0
 def visit_Continue(self, _):
     return Statement("continue")
Ejemplo n.º 17
0
 def visit_Assert(self, node):
     params = [self.visit(node.test), node.msg and self.visit(node.msg)]
     sparams = ", ".join(_f for _f in params if _f)
     return Statement("pythonic::pythran_assert({0})".format(sparams))
Ejemplo n.º 18
0
def generate_cxx(module_name, code, specs=None, optimizations=None):
    '''python + pythran spec -> c++ code
    returns a BoostPythonModule object

    '''
    pm = PassManager(module_name)

    # front end
    ir, renamings = frontend.parse(pm, code)

    # middle-end
    optimizations = (optimizations or
                     cfg.get('pythran', 'optimizations').split())
    optimizations = map(_parse_optimization, optimizations)
    refine(pm, ir, optimizations)

    # back-end
    content = pm.dump(Cxx, ir)

    # instanciate the meta program
    if specs is None:

        class Generable:
            def __init__(self, content):
                self.content = content

            def __str__(self):
                return str(self.content)

            generate = __str__

        mod = Generable(content)
    else:

        # uniform typing
        for fname, signatures in specs.items():
            if not isinstance(signatures, tuple):
                specs[fname] = (signatures,)

        # verify the pythran export are compatible with the code
        specs = expand_specs(specs)
        check_specs(ir, specs, renamings)

        mod = BoostPythonModule(module_name)
        mod.use_private_namespace = False
        # very low value for max_arity leads to various bugs
        min_val = 2
        specs_max = [max(map(len, s)) for s in specs.itervalues()]
        max_arity = max([min_val] + specs_max)
        mod.add_to_preamble([Define("BOOST_PYTHON_MAX_ARITY", max_arity)])
        mod.add_to_preamble([Define("BOOST_SIMD_NO_STRICT_ALIASING", "1")])
        mod.add_to_preamble([Include("pythonic/core.hpp")])
        mod.add_to_preamble([Include("pythonic/python/core.hpp")])
        mod.add_to_preamble([Line("#ifdef _OPENMP\n#include <omp.h>\n#endif")])
        mod.add_to_preamble(map(Include, _extract_specs_dependencies(specs)))
        mod.add_to_preamble(content.body)
        mod.add_to_init([
            Line('#ifdef PYTHONIC_TYPES_NDARRAY_HPP\nimport_array()\n#endif')])

        # topologically sorted exceptions based on the inheritance hierarchy.
        # needed because otherwise boost python register_exception handlers
        # do not catch exception type in the right way
        # (first valid exception is selected)
        # Inheritance has to be taken into account in the registration order.
        exceptions = nx.DiGraph()
        for function_name, v in functions.iteritems():
            for mname, symbol in v:
                if isinstance(symbol, ConstExceptionIntr):
                    exceptions.add_node(
                        getattr(sys.modules[".".join(mname)], function_name))

        # add edges based on class relationships
        for n in exceptions:
            if n.__base__ in exceptions:
                exceptions.add_edge(n.__base__, n)

        sorted_exceptions = nx.topological_sort(exceptions)
        mod.add_to_init([
            # register exception only if they can be raise from C++ world to
            # Python world. Preprocessors variables are set only if deps
            # analysis detect that this exception can be raised
            Line('#ifdef PYTHONIC_BUILTIN_%s_HPP\n'
                 'boost::python::register_exception_translator<'
                 'pythonic::types::%s>(&pythonic::translate_%s);\n'
                 '#endif' % (n.__name__.upper(), n.__name__, n.__name__)
                 ) for n in sorted_exceptions])

        mod.add_to_init([
            # make sure we get no nested parallelism that wreaks havoc in perf
            Line('#ifdef _OPENMP\n'
                 'omp_set_max_active_levels(1);\n'
                 '#endif')])

        for function_name, signatures in specs.iteritems():
            internal_func_name = renamings.get(function_name,
                                               function_name)
            for sigid, signature in enumerate(signatures):
                numbered_function_name = "{0}{1}".format(internal_func_name,
                                                         sigid)
                arguments_types = [pytype_to_ctype(t) for t in signature]
                has_arguments = HasArgument(internal_func_name).visit(ir)
                arguments = ["a{0}".format(i)
                             for i in xrange(len(arguments_types))]
                name_fmt = pythran_ward + "{0}::{1}::type{2}"
                args_list = ", ".join(arguments_types)
                specialized_fname = name_fmt.format(module_name,
                                                    internal_func_name,
                                                    "<{0}>".format(args_list)
                                                    if has_arguments else "")
                result_type = ("typename std::remove_cv<"
                               "typename std::remove_reference"
                               "<typename {0}::result_type>::type"
                               ">::type").format(specialized_fname)
                mod.add_to_init(
                    [Statement("pythonic::python_to_pythran<{0}>()".format(t))
                     for t in _extract_all_constructed_types(signature)])
                mod.add_to_init([Statement(
                    "pythonic::pythran_to_python<{0}>()".format(result_type))])
                mod.add_function(
                    FunctionBody(
                        FunctionDeclaration(
                            Value(
                                result_type,
                                numbered_function_name),
                            [Value(t, a)
                             for t, a in zip(arguments_types, arguments)]),
                        Block([Statement("return {0}()({1})".format(
                            pythran_ward + '{0}::{1}'.format(
                                module_name, internal_func_name),
                            ', '.join(arguments)))])
                    ),
                    function_name
                )
        # call __init__() to execute top-level statements
        init_call = '::'.join([pythran_ward + module_name, '__init__()()'])
        mod.add_to_init([Statement(init_call)])
    return mod