Format

format

FuncOpLikeParseResult: TypeAlias = tuple[str, Sequence[Attribute], Sequence[Attribute], Region, DictionaryAttr | None, ArrayAttr[DictionaryAttr] | None, ArrayAttr[DictionaryAttr] | None] module-attribute

FuncOpLikeParseResultWithVariadic: TypeAlias = tuple[str, Sequence[Attribute], Sequence[Attribute], Region, DictionaryAttr | None, ArrayAttr[DictionaryAttr] | None, ArrayAttr[DictionaryAttr] | None, bool] module-attribute

AbstractYieldOperation

Bases: IRDLOperation, Generic[AttributeInvT]

A base class for yielding operations to inherit, provides the standard custom syntax and a definition of the arguments variadic operand.

Source code in xdsl/dialects/utils/format.py

class AbstractYieldOperation(IRDLOperation, Generic[AttributeInvT]):
    """
    A base class for yielding operations to inherit, provides the standard custom syntax
    and a definition of the `arguments` variadic operand.
    """

    arguments = var_operand_def(AttributeInvT)

    assembly_format = "attr-dict ($arguments^ `:` type($arguments))?"

    def __init__(self, *operands: SSAValue | Operation):
        super().__init__(operands=[operands])

arguments = var_operand_def(AttributeInvT) class-attribute instance-attribute

assembly_format = 'attr-dict ($arguments^ `:` type($arguments))?' class-attribute instance-attribute

__init__(*operands: SSAValue | Operation)

Source code in xdsl/dialects/utils/format.py

def __init__(self, *operands: SSAValue | Operation):
    super().__init__(operands=[operands])

print_for_op_like(printer: Printer, lower_bound: SSAValue, upper_bound: SSAValue, step: SSAValue, iter_args: Sequence[SSAValue], body: Region, default_indvar_type: type[TypeAttribute] | None = None, bound_words: Sequence[str] = ['to'])

Prints the loop bounds, step, iteration arguments, and body.

Users can provide a default induction variable type and specific human-readable words for bounds (default: "to").

Note that providing a default induction variable type is required to suggest that all loop control variable types (induction, bounds and step) have the same type, hence moving the induction variable type printing to the end of the for expression. The induction variable type printing is ommited when it matches the expected default type (default_indvar_type).

Source code in xdsl/dialects/utils/format.py

def print_for_op_like(
    printer: Printer,
    lower_bound: SSAValue,
    upper_bound: SSAValue,
    step: SSAValue,
    iter_args: Sequence[SSAValue],
    body: Region,
    default_indvar_type: type[TypeAttribute] | None = None,
    bound_words: Sequence[str] = ["to"],
):
    """
    Prints the loop bounds, step, iteration arguments, and body.

    Users can provide a default induction variable type and specific human-readable
    words for bounds (default: "to").

    Note that providing a default induction variable type is required to suggest that
    all loop control variable types (induction, bounds and step) have the same type,
    hence moving the induction variable type printing to the end of the for expression.
    The induction variable type printing is ommited when it matches the expected default
    type (`default_indvar_type`).
    """

    block = body.block
    indvar, *block_iter_args = block.args

    printer.print_string(" ")

    def print_indvar_type():
        printer.print_string(" : ")
        printer.print_attribute(indvar.type)
        printer.print_string(" ")

    printer.print_ssa_value(indvar)

    if default_indvar_type is None:
        print_indvar_type()

    printer.print_string(" = ")
    printer.print_ssa_value(lower_bound)

    for word in bound_words:
        printer.print_string(f" {word} ")

    printer.print_ssa_value(upper_bound)
    printer.print_string(" step ")
    printer.print_ssa_value(step)
    printer.print_string(" ")
    if block_iter_args:
        printer.print_string("iter_args(")
        printer.print_list(
            zip(block_iter_args, iter_args),
            lambda pair: print_assignment(printer, *pair),
        )
        printer.print_string(") -> (")
        printer.print_list((a.type for a in block_iter_args), printer.print_attribute)
        printer.print_string(") ")

    if default_indvar_type is not None and not isinstance(
        indvar.type, default_indvar_type
    ):
        print_indvar_type()

    printer.print_region(
        body,
        print_entry_block_args=False,
        print_empty_block=False,
        print_block_terminators=bool(iter_args),
    )

parse_for_op_like(parser: Parser, default_indvar_type: TypeAttribute | None = None, bound_words: Sequence[str] = ['to']) -> tuple[SSAValue, SSAValue, SSAValue, Sequence[SSAValue], Region]

Returns the loop bounds, step, iteration arguments, and body.

Users can provide a default induction variable type and specific human-readable words for bounds (default: "to"). Note that providing a default induction variable type is required to suggest that all loop control variable types (induction, bounds and step) have the same type, hence the induction variable type is potentially expected at the end of the for expression.

Source code in xdsl/dialects/utils/format.py

def parse_for_op_like(
    parser: Parser,
    default_indvar_type: TypeAttribute | None = None,
    bound_words: Sequence[str] = ["to"],
) -> tuple[SSAValue, SSAValue, SSAValue, Sequence[SSAValue], Region]:
    """
    Returns the loop bounds, step, iteration arguments, and body.

    Users can provide a default induction variable type and specific human-readable
    words for bounds (default: "to").
    Note that providing a default induction variable type is required to suggest that
    all loop control variable types (induction, bounds and step) have the same type,
    hence the induction variable type is potentially expected at the end of the for
    expression.
    """

    unresolved_indvar = parser.parse_argument(expect_type=False)

    indvar_type = None

    if default_indvar_type is None:
        parser.parse_characters(":")
        indvar_type = parser.parse_type()

    parser.parse_characters("=")
    lower_bound = parser.parse_operand()

    for word in bound_words:
        parser.parse_characters(word)

    upper_bound = parser.parse_operand()
    parser.parse_characters("step")
    step = parser.parse_operand()

    # parse iteration arguments
    pos = parser.pos
    unresolved_iter_args: list[Parser.UnresolvedArgument] = []
    iter_arg_unresolved_operands: list[UnresolvedOperand] = []
    iter_arg_types: list[Attribute] = []
    if parser.parse_optional_characters("iter_args"):
        for iter_arg, iter_arg_operand in parser.parse_comma_separated_list(
            Parser.Delimiter.PAREN, lambda: parse_assignment(parser)
        ):
            unresolved_iter_args.append(iter_arg)
            iter_arg_unresolved_operands.append(iter_arg_operand)
        parser.parse_characters("->")
        iter_arg_types = parser.parse_comma_separated_list(
            Parser.Delimiter.PAREN, parser.parse_attribute
        )

    iter_arg_operands = parser.resolve_operands(
        iter_arg_unresolved_operands, iter_arg_types, pos
    )

    # set block argument types
    iter_args = [
        u_arg.resolve(t) for u_arg, t in zip(unresolved_iter_args, iter_arg_types)
    ]

    if default_indvar_type is not None:
        indvar_type = (
            parser.parse_type()
            if parser.parse_optional_characters(":")
            else default_indvar_type
        )
    assert indvar_type is not None

    # set induction variable type
    indvar = unresolved_indvar.resolve(indvar_type)

    body = parser.parse_region((indvar, *iter_args))

    return lower_bound, upper_bound, step, iter_arg_operands, body

print_func_op_like(printer: Printer, sym_name: StringAttr, function_type: FunctionType, body: Region, attributes: dict[str, Attribute], *, arg_attrs: ArrayAttr[DictionaryAttr] | None = None, res_attrs: ArrayAttr[DictionaryAttr] | None = None, reserved_attr_names: Sequence[str], is_variadic: bool = False, print_empty_outputs: bool = True)

Source code in xdsl/dialects/utils/format.py

def print_func_op_like(
    printer: Printer,
    sym_name: StringAttr,
    function_type: FunctionType,
    body: Region,
    attributes: dict[str, Attribute],
    *,
    arg_attrs: ArrayAttr[DictionaryAttr] | None = None,
    res_attrs: ArrayAttr[DictionaryAttr] | None = None,
    reserved_attr_names: Sequence[str],
    is_variadic: bool = False,
    print_empty_outputs: bool = True,
):
    printer.print_string(" ")
    printer.print_symbol_name(sym_name.data)

    # Non-variadic declaration
    if not body.blocks and not is_variadic:
        if print_empty_outputs:
            printer.print_attribute(function_type)
        else:
            printer.print_string("(")
            printer.print_list(function_type.inputs, printer.print_attribute)
            printer.print_string(")")
            _print_func_outputs(printer, function_type.outputs.data, res_attrs)
        printer.print_op_attributes(
            attributes, reserved_attr_names=reserved_attr_names, print_keyword=True
        )
        return

    # Definition or variadic declaration
    printer.print_string("(")
    if body.blocks:
        block_args = body.blocks[0].args
        if arg_attrs is not None:
            printer.print_list(
                zip(block_args, arg_attrs),
                lambda t: print_func_argument(printer, t[0], t[1]),
            )
        else:
            printer.print_list(block_args, printer.print_block_argument)
        has_args = bool(block_args)
    else:
        printer.print_list(function_type.inputs, printer.print_attribute)
        has_args = bool(function_type.inputs)

    if is_variadic:
        if has_args:
            printer.print_string(", ")
        printer.print_string("...")
    printer.print_string(")")

    _print_func_outputs(printer, function_type.outputs.data, res_attrs)
    printer.print_op_attributes(
        attributes, reserved_attr_names=reserved_attr_names, print_keyword=True
    )

    if body.blocks:
        printer.print_string(" ", indent=0)
        printer.print_region(body, False, False)

parse_func_op_like(parser: Parser, *, reserved_attr_names: Sequence[str], allow_variadic: bool = False) -> FuncOpLikeParseResult | FuncOpLikeParseResultWithVariadic

parse_func_op_like(
    parser: Parser,
    *,
    reserved_attr_names: Sequence[str],
    allow_variadic: Literal[False] = False,
) -> FuncOpLikeParseResult

parse_func_op_like(
    parser: Parser,
    *,
    reserved_attr_names: Sequence[str],
    allow_variadic: Literal[True],
) -> FuncOpLikeParseResultWithVariadic

Returns the function name, argument types, return types, body, extra args, arg_attrs and res_attrs. If allow_variadic=True, also returns is_variadic as the 8th element.

Source code in xdsl/dialects/utils/format.py

def parse_func_op_like(
    parser: Parser,
    *,
    reserved_attr_names: Sequence[str],
    allow_variadic: bool = False,
) -> FuncOpLikeParseResult | FuncOpLikeParseResultWithVariadic:
    """
    Returns the function name, argument types, return types, body, extra args, arg_attrs and res_attrs.
    If allow_variadic=True, also returns is_variadic as the 8th element.
    """
    # Parse function name
    name = parser.parse_symbol_name().data

    # Track variadic state if enabled
    is_variadic = False

    def parse_fun_input() -> (
        Attribute | tuple[Parser.Argument, dict[str, Attribute]] | None
    ):
        def parse_optional_attrs_and_loc() -> tuple[
            dict[str, Attribute], LocationAttr | None
        ]:
            arg_attr_dict = parser.parse_optional_dictionary_attr_dict()
            arg_loc = parser.parse_optional_location()

            # Reject attrs after location, including empty dictionaries.
            if arg_loc is not None:
                arg_attr_pos = parser.pos
                parser.parse_optional_dictionary_attr_dict()
                if parser.pos != arg_attr_pos:
                    parser.raise_error(
                        "Expected function argument attributes before location."
                    )
            return arg_attr_dict, arg_loc

        nonlocal is_variadic
        if allow_variadic and parser.parse_optional_characters("...") is not None:
            is_variadic = True
            return None
        arg = parser.parse_optional_argument()
        if arg is None:
            ret = parser.parse_optional_type()
            if ret is None:
                parser.raise_error("Expected argument or type")
            # Declarative args keep only the type and consume attributes and location.
            parse_optional_attrs_and_loc()
        else:
            arg_attr_dict, arg_loc = parse_optional_attrs_and_loc()
            arg.location = arg_loc
            ret = (arg, arg_attr_dict)
        return ret

    # Parse function arguments
    args_raw = parser.parse_comma_separated_list(
        parser.Delimiter.PAREN,
        parse_fun_input,
    )
    args: list[Attribute | tuple[Parser.Argument, dict[str, Attribute]]]
    args = [arg for arg in args_raw if arg is not None]

    entry_arg_tuples: list[tuple[Parser.Argument, dict[str, Attribute]]] = []
    input_types: list[Attribute] = []
    for arg in args:
        if isinstance(arg, Attribute):
            input_types.append(arg)
        else:
            entry_arg_tuples.append(arg)

    if entry_arg_tuples:
        # Check consistency (They should be either all named or none)
        if input_types:
            parser.raise_error(
                "Expected all arguments to be named or all arguments to be unnamed."
            )

        entry_args = [arg for arg, _ in entry_arg_tuples]
        input_types = [arg.type for arg in entry_args]
    else:
        entry_args = None

    if any(attrs for _, attrs in entry_arg_tuples):
        arg_attrs = ArrayAttr(DictionaryAttr(attrs) for _, attrs in entry_arg_tuples)
    else:
        arg_attrs = None

    # Parse return types
    return_types, res_attrs = _parse_func_outputs(parser)

    extra_attributes = parser.parse_optional_attr_dict_with_keyword(reserved_attr_names)

    # Parse body
    region = parser.parse_optional_region(entry_args)
    if region is None:
        region = Region()

    if allow_variadic:
        return (
            name,
            input_types,
            return_types,
            region,
            extra_attributes,
            arg_attrs,
            res_attrs,
            is_variadic,
        )
    return (
        name,
        input_types,
        return_types,
        region,
        extra_attributes,
        arg_attrs,
        res_attrs,
    )

print_func_argument(printer: Printer, arg: BlockArgument, attrs: DictionaryAttr | None)

Keep function-argument syntax compatible with MLIR parser expectations: %arg : type {attrs} loc(...) (location after attrs).

Source code in xdsl/dialects/utils/format.py

def print_func_argument(
    printer: Printer, arg: BlockArgument, attrs: DictionaryAttr | None
):
    """
    Keep function-argument syntax compatible with MLIR parser expectations:
    `%arg : type {attrs} loc(...)` (location after attrs).
    """
    printer.print_block_argument(arg, print_type=False)
    printer.print_string(": ")
    printer.print_attribute(arg.type)
    if attrs is not None and attrs.data:
        printer.print_op_attributes(attrs.data)
    if printer.print_debuginfo:
        printer.print_string(" ")
        printer.print_attribute(arg.location)

print_func_output(printer: Printer, out_type: Attribute, attrs: DictionaryAttr | None)

Source code in xdsl/dialects/utils/format.py

def print_func_output(
    printer: Printer, out_type: Attribute, attrs: DictionaryAttr | None
):
    printer.print_attribute(out_type)
    if attrs is not None and attrs.data:
        printer.print_op_attributes(attrs.data)

print_assignment(printer: Printer, arg: BlockArgument, val: SSAValue)

Source code in xdsl/dialects/utils/format.py

def print_assignment(printer: Printer, arg: BlockArgument, val: SSAValue):
    printer.print_block_argument(arg, print_type=False)
    printer.print_string(" = ")
    printer.print_ssa_value(val)

parse_assignment(parser: Parser) -> tuple[Parser.UnresolvedArgument, UnresolvedOperand]

Source code in xdsl/dialects/utils/format.py

def parse_assignment(
    parser: Parser,
) -> tuple[Parser.UnresolvedArgument, UnresolvedOperand]:
    arg = parser.parse_argument(expect_type=False)
    parser.parse_characters("=")
    val = parser.parse_unresolved_operand()
    return arg, val