DriverTrac/venv/lib/python3.12/site-packages/triton/compiler/code_generator.py
2025-11-28 09:08:33 +05:30

1615 lines
70 KiB
Python

import ast
import builtins
import contextlib
import copy
import inspect
import re
import warnings
import textwrap
import itertools
from dataclasses import dataclass
from types import ModuleType
from typing import Any, Callable, Dict, Optional, Tuple, Type, Union, Iterable, List
from .. import knobs, language
from .._C.libtriton import ir, gluon_ir
from ..language import constexpr, str_to_ty, tensor, tuple as tl_tuple
from ..language.core import _unwrap_if_constexpr, base_value, base_type
# ideally we wouldn't need any runtime component
from ..runtime.jit import get_jit_fn_file_line, get_full_name, JITCallable, BoundConstexprFunction, ConstexprFunction, JITFunction
from .._utils import find_paths_if, get_iterable_path, set_iterable_path
from .errors import (CompilationError, CompileTimeAssertionFailure, UnsupportedLanguageConstruct)
def check_identifier_legality(name, type):
pattern = r'^[a-zA-Z_][a-zA-Z0-9_]*$'
if not re.match(pattern, name):
raise CompilationError(f"invalid {type} identifier: {name}", name)
return name
def mangle_fn(name, arg_tys, constants, caller_context):
# doesn't mangle ret type, which must be a function of arg tys
mangled_arg_names = '_'.join([ty.mangle() for ty in arg_tys])
mangled_constants = '_'.join([f'{i}c{repr(constants[i])}' for i in sorted(constants)])
mangled_constants = mangled_constants.replace('.', '_d_')
mangled_constants = mangled_constants.replace("'", '_sq_')
# [ and ] are not allowed in LLVM identifiers
mangled_constants = mangled_constants.replace('[', '_').replace(']', '_')
ret = f'{name}__{mangled_arg_names}__{mangled_constants}'
if caller_context is not None:
ret += caller_context.mangle()
return ret
def _is_triton_value(o: Any) -> bool:
return isinstance(o, base_value)
def _is_triton_tensor(o: Any) -> bool:
return isinstance(o, tensor)
def _is_constexpr(o: Any) -> bool:
return o is None or isinstance(o, (constexpr, language.core.dtype, JITCallable))
def _is_non_scalar_tensor(o: Any) -> bool:
return _is_triton_tensor(o) and (o.type.is_block() and o.type.numel != 1)
def _is_list_like(o: Any) -> bool:
return isinstance(o, (list, tuple))
def _check_fn_args(node, fn, args):
if fn.noinline:
for idx, arg in enumerate(args):
if not _is_constexpr(arg) and _is_non_scalar_tensor(arg):
raise UnsupportedLanguageConstruct(
fn.src, node,
f'Function {fn.__name__} is marked noinline, but was called with non-scalar argument {fn.arg_names[idx]}:{arg}'
)
def _is_namedtuple(val):
return isinstance(val, type) and issubclass(val, tuple) and hasattr(val, "_fields")
def _apply_to_tuple_values(value, fn):
if _is_namedtuple(type(value)):
fields = value._fields
elif isinstance(value, language.tuple):
fields = value.type.fields
else:
assert False, f"Unsupported type {type(value)}"
vals = [fn(v) for v in value]
vals = [constexpr(v) if v is None else v for v in vals]
types = [v.type for v in vals]
return language.tuple(vals, language.tuple_type(types, fields))
def flatten_values_to_ir(values: Iterable[base_value]):
handles = []
for v in values:
v._flatten_ir(handles)
return handles
def unflatten_ir_values(handles: List[ir.value], types: List[base_type]):
cursor = 0
for ty in types:
value, cursor = ty._unflatten_ir(handles, cursor)
yield value
assert cursor == len(handles)
_condition_types = {bool, int, type(None)} # Python types accepted for conditionals inside kernels
def _clone_triton_value(val):
handles = []
val._flatten_ir(handles)
clone, _ = val.type._unflatten_ir(handles, 0)
return clone
def _clone_scope(scope):
return {name: _clone_triton_value(val) if _is_triton_value(val) else val for name, val in scope.items()}
class enter_sub_region:
def __init__(self, generator):
self.generator = generator
def __enter__(self):
# record lscope & local_defs in the parent scope
self.liveins = _clone_scope(self.generator.lscope)
self.prev_defs = _clone_scope(self.generator.local_defs)
self.generator.local_defs = {}
self.insert_block = self.generator.builder.get_insertion_block()
self.insert_point = self.generator.builder.get_insertion_point()
return self.liveins, self.insert_block
def __exit__(self, *args, **kwargs):
self.generator.builder.restore_insertion_point(self.insert_point)
self.generator.lscope = self.liveins
self.generator.local_defs = self.prev_defs
# Check if the given syntax node has an "early" return
class ContainsReturnChecker(ast.NodeVisitor):
def __init__(self, gscope):
self.gscope = gscope
def _visit_stmts(self, body) -> bool:
return any(self.visit(s) for s in body)
def _visit_function(self, fn) -> bool:
# No need to check within the function as it won't cause an early return.
# If the function itself has unstructured control flow we may not be able to inline it causing poor performance,
# we should check for this and emit a warning.
return False
def generic_visit(self, node) -> bool:
ret = False
for _, value in ast.iter_fields(node):
if isinstance(value, list):
for item in value:
if isinstance(item, ast.AST):
ret = ret or self.visit(item)
elif isinstance(value, ast.AST):
ret = ret or self.visit(value)
return ret
def visit_Attribute(self, node: ast.Attribute) -> bool:
# If the left part is a name, it's possible that
# we call triton native function or a jit function from another module.
# If the left part is not a name, it must return a tensor or a constexpr
# whose methods do not contain return statements
# e.g., (tl.load(x)).to(y)
# So we only check if the expressions within value have return or not
if isinstance(node.value, ast.Name):
if node.value.id in self.gscope:
value = self.gscope[node.value.id]
fn = getattr(value, node.attr)
return self._visit_function(fn)
return False
return self.visit(node.value)
def visit_Name(self, node: ast.Name) -> bool:
if type(node.ctx) is ast.Store:
return False
if node.id in self.gscope:
fn = self.gscope[node.id]
return self._visit_function(fn)
return False
def visit_Return(self, node: ast.Return) -> bool:
return True
def visit_Assign(self, node: ast.Assign) -> bool:
# There couldn't be an early return
# x = ...
return False
def visit_AugAssign(self, node: ast.AugAssign) -> bool:
# There couldn't be an early return
# x += ...
return False
def visit_Module(self, node: ast.Module) -> bool:
return self._visit_stmts(node.body)
def visit_FunctionDef(self, node: ast.FunctionDef) -> bool:
return self._visit_stmts(node.body)
def visit_If(self, node: ast.If) -> bool:
# TODO: optimize the following case in which we actually don't have
# a return when static_cond is false:
# if dynamic_cond
# if static_cond
# func_with_return
# else
# func_without_return
ret = self._visit_stmts(node.body)
if node.orelse:
ret = ret or self._visit_stmts(node.orelse)
return ret
def visit_IfExp(self, node: ast.IfExp) -> bool:
return self.visit(node.body) or self.visit(node.orelse)
def visit_Call(self, node: ast.Call) -> bool:
return self.visit(node.func)
class ASTFunction:
def __init__(self, ret_types, arg_types, constants, attrs):
self.ret_types = ret_types
self.arg_types = arg_types
self.constants = constants
self.attrs = attrs
def flatten_ir_types(self, builder: ir.builder, types: List[base_type]) -> List[ir.type]:
ir_types = []
for ty in types:
if ty is None:
continue
ty._flatten_ir_types(builder, ir_types)
return ir_types
def return_types_ir(self, builder: ir.builder) -> List[ir.type]:
return self.flatten_ir_types(builder, self.ret_types)
def serialize(self, builder: ir.builder):
# fill up IR values in template
# > build function
is_val = lambda path, _: path not in self.constants and _ is not None
val_paths = list(find_paths_if(self.arg_types, is_val))
arg_types = [get_iterable_path(self.arg_types, path) for path in val_paths]
arg_types_ir = self.flatten_ir_types(builder, arg_types)
ret_types_ir = self.return_types_ir(builder)
return builder.get_function_ty(arg_types_ir, ret_types_ir)
def deserialize(self, fn):
# create "template"
def make_template(ty):
if isinstance(ty, (list, tuple, language.tuple_type)):
return language.tuple([make_template(x) for x in ty], ty)
return language.constexpr(None)
vals = make_template(self.arg_types)
is_val = lambda path, _: path not in self.constants and _ is not None
val_paths = list(find_paths_if(self.arg_types, is_val))
# > add IR values to the template
cursor = 0
handles = [fn.args(i) for i in range(fn.get_num_args())]
for path in val_paths:
ty = get_iterable_path(self.arg_types, path)
# > set attributes
attr_specs = self.attrs.get(path, [])
for attr_name, attr_val in attr_specs:
fn.set_arg_attr(cursor, attr_name, attr_val)
# > build frontend value
val, cursor = ty._unflatten_ir(handles, cursor)
set_iterable_path(vals, path, val)
# > add constexpr values to the template
constants = self.constants
for path, val in constants.items():
set_iterable_path(vals, path, language.constexpr(val))
return vals
@dataclass(frozen=True)
class BoundJITMethod:
__self__: base_value
__func__: JITFunction
class CodeGenerator(ast.NodeVisitor):
def __init__(self, context, prototype, gscope, function_name, jit_fn: JITFunction, *, options, codegen_fns,
module_map, is_gluon, module=None, is_kernel=False, function_types: Optional[Dict] = None,
noinline=False, caller_context=None, file_name: Optional[str] = None, begin_line=0):
self.context = context
self.is_gluon = is_gluon
if is_gluon:
from triton.experimental.gluon.language._semantic import GluonSemantic
self.builder = gluon_ir.GluonOpBuilder(context)
self.semantic = GluonSemantic(self.builder)
else:
from triton.language.semantic import TritonSemantic
self.builder = ir.builder(context)
self.semantic = TritonSemantic(self.builder)
self.name_loc_as_prefix = None
self.file_name = file_name
# node.lineno starts from 1, so we need to subtract 1
self.begin_line = begin_line - 1
self.builder.set_loc(file_name, begin_line, 0)
self.builder.options = options
# dict of functions provided by the backend. Below are the list of possible functions:
# Convert custom types not natively supported on HW.
# convert_custom_types(input_tensor, dtype, fp_downcast_rounding=None, _builder=None)
self.builder.codegen_fns = codegen_fns
self.builder.module_map = {} if module_map is None else module_map
self.module = self.builder.create_module() if module is None else module
self.function_ret_types = {} if function_types is None else function_types
self.prototype = prototype
self.gscope = {}
for k, v in gscope.items():
if isinstance(v, ModuleType):
self.gscope[k] = module_map.get(v.__name__, v)
continue
module_name = getattr(v, "__module__", "")
if module_name in module_map:
self.gscope[k] = getattr(module_map[module_name], v.__name__)
else:
self.gscope[k] = v
self.lscope = {}
self.jit_fn = jit_fn
# TODO: we currently generate illegal names for non-kernel functions involving constexprs!
if is_kernel:
function_name = function_name[function_name.rfind('.') + 1:]
function_name = check_identifier_legality(function_name, "function")
self.function_name = function_name
self.is_kernel = is_kernel
self.cur_node = None
self.noinline = noinline
self.caller_context = caller_context
self.scf_stack = []
self.ret_type = None
# SSA-construction
# name => language.tensor
self.local_defs: Dict[str, tensor] = {}
self.dereference_name: Callable[[str], Any] = self._define_name_lookup()
self.fn = None
# Are we currently visiting an ast.arg's default value? These have some
# special handling.
self.visiting_arg_default_value = False
builtin_namespace: Dict[str, Any] = {
_.__name__: _
for _ in (len, list, range, float, int, isinstance, getattr, hasattr)
}
builtin_namespace.update((
('print', language.core.device_print),
('min', language.minimum),
('max', language.maximum),
))
def _unsupported(self, node, message):
return UnsupportedLanguageConstruct(self.jit_fn.src, node, message)
def _is_constexpr_global(self, name):
absent_marker = object()
val = self.gscope.get(name, absent_marker)
if val is absent_marker:
return False
if _is_constexpr(val):
return True
return False
def _define_name_lookup(self):
def local_lookup(name: str, absent):
# this needs to be re-fetched from `self` every time, because it gets switched occasionally
return self.lscope.get(name, absent)
def global_lookup(name: str, absent):
val = self.gscope.get(name, absent)
# The high-level rule is that only constexpr globals are allowed.
# But actually a bunch of other things, such as module imports, are
# technically Python globals. We have to allow these too!
if any([
val is absent,
name in self.builtin_namespace, #
type(val) is ModuleType, #
isinstance(val, JITCallable), #
getattr(val, "__triton_builtin__", False), #
getattr(val, "__triton_aggregate__", False), #
getattr(val, "__module__", "").startswith("triton.language"), #
getattr(val, "__module__", "").startswith("triton.experimental.gluon.language"), #
isinstance(val, language.dtype), #
_is_namedtuple(val),
self._is_constexpr_global(name), #
# Allow accesses to globals while visiting an ast.arg
# because you should be able to do
# @triton.jit def fn(x: tl.constexpr = GLOBAL): ...
self.visiting_arg_default_value, #
knobs.compilation.allow_non_constexpr_globals,
]):
return val
raise NameError(
textwrap.dedent(f"""\
Cannot access global variable {name} from within @jit'ed
function. Triton kernels can only access global variables that
are instanstiated as constexpr (`x = triton.language.constexpr(42)`). Note that this is different from
annotating a variable as constexpr (`x: triton.language.constexpr = 42`), which is not supported. Alternatively, set the
envvar TRITON_ALLOW_NON_CONSTEXPR_GLOBALS=1, but we do not
promise to support this forever.""").replace("\n", " "))
absent_marker = object()
def name_lookup(name: str) -> Any:
absent = absent_marker
for lookup_function in local_lookup, global_lookup, self.builtin_namespace.get:
value = lookup_function(name, absent)
if value is not absent:
return value
raise NameError(f'{name} is not defined')
return name_lookup
@contextlib.contextmanager
def _name_loc_prefix(self, prefix):
self.name_loc_as_prefix = prefix
yield
self.name_loc_as_prefix = None
def _maybe_set_loc_to_name(self, val, name):
if isinstance(val, (ir.value, ir.block_argument)):
val.set_loc(self.builder.create_name_loc(name, val.get_loc()))
elif _is_triton_value(val):
handles = []
val._flatten_ir(handles)
for handle in handles:
handle.set_loc(self.builder.create_name_loc(name, handle.get_loc()))
def set_value(self, name: str, value: Union[base_value, constexpr]) -> None:
''' This function:
called by visit_Assign() & visit_FunctionDef() to store left value (lvalue)
1. record local defined name (FIXME: should consider control flow)
2. store tensor in self.lvalue
'''
self.lscope[name] = value
self.local_defs[name] = value
def _get_insertion_point_and_loc(self):
# XXX: this is a hack to get the location of the insertion point.
# The insertion point's location could be invalid sometimes,
# so we need to explicitly set the location
loc = self.builder.get_loc()
ip = self.builder.get_insertion_point()
return ip, loc
def _set_insertion_point_and_loc(self, ip, loc):
self.builder.restore_insertion_point(ip)
self.builder.set_loc(loc)
def _find_carries(self, node, liveins):
# create loop body block
block = self.builder.create_block()
self.builder.set_insertion_point_to_start(block)
# dry visit loop body
self.scf_stack.append(node)
self.visit_compound_statement(node.body)
self.scf_stack.pop()
block.erase()
# If a variable (name) has changed value within the loop, then it's
# a loop-carried variable. (The new and old value must be of the
# same type)
init_tys = []
init_handles = []
names = []
for name, live_val in liveins.items():
if _is_triton_value(live_val):
loop_val = self.lscope[name]
self._verify_loop_carried_variable(name, loop_val, live_val)
live_handles = flatten_values_to_ir([live_val])
loop_handles = flatten_values_to_ir([loop_val])
if live_handles != loop_handles:
names.append(name)
init_tys.append(live_val.type)
init_handles.extend(live_handles)
else:
assert name not in self.local_defs, f'Loop carried variable {name} is not a triton value'
# reset local scope to not pick up local defs from the dry run.
self.lscope = liveins.copy()
self.local_defs = {}
return names, init_handles, init_tys
#
# AST visitor
#
def visit_compound_statement(self, stmts):
# Ensure that stmts is iterable
if not _is_list_like(stmts):
stmts = [stmts]
for stmt in stmts:
self.visit(stmt)
# Stop parsing as soon as we hit a `return` statement; everything
# after this is dead code.
if isinstance(stmt, ast.Return):
break
def visit_Module(self, node):
ast.NodeVisitor.generic_visit(self, node)
def visit_List(self, node):
ctx = self.visit(node.ctx)
assert ctx is None
elts = language.tuple([self.visit(elt) for elt in node.elts])
return elts
def visit_ListComp(self, node: ast.ListComp):
if len(node.generators) != 1:
raise ValueError("nested comprehensions are not supported")
comp = node.generators[0]
iter = self.visit(comp.iter)
if not isinstance(iter, tl_tuple):
raise NotImplementedError("only tuple comprehensions are supported")
results = []
for item in iter:
self.set_value(comp.target.id, item)
results.append(self.visit(node.elt))
return tl_tuple(results)
# By design, only non-kernel functions can return
def visit_Return(self, node):
ret_value = self.visit(node.value)
handles = []
def decay(value):
if isinstance(value, language.tuple):
return _apply_to_tuple_values(value, decay)
elif isinstance(value, (language.constexpr, int, float)):
return self.semantic.to_tensor(value)
return value
ret_value = decay(ret_value)
if ret_value is None:
ret_ty = language.void
else:
assert isinstance(ret_value, language.core.base_value)
ret_value._flatten_ir(handles)
ret_ty = ret_value.type
self.builder.ret(handles)
if self.ret_type is None:
self.ret_type = ret_ty
elif self.ret_type != ret_ty:
raise TypeError(f'Inconsistent return types: {self.ret_type} and {ret_ty}')
# A return op must always terminate the basic block, so we create a dead
# basic block in case there are any ops after the return.
post_ret_block = self.builder.create_block()
self.builder.set_insertion_point_to_end(post_ret_block)
def visit_Starred(self, node) -> Any:
args = self.visit(node.value)
assert isinstance(args, language.core.tuple)
return args.values
def visit_FunctionDef(self, node):
arg_names, kwarg_names = self.visit(node.args)
if self.fn:
raise self._unsupported(node, "nested function definition is not supported.")
# initialize defaults
for i, default_value in enumerate(node.args.defaults[::-1]):
arg_node = node.args.args[-i - 1]
annotation = arg_node.annotation
name = arg_node.arg
st_target = ast.Name(id=name, ctx=ast.Store())
if annotation is None:
init_node = ast.Assign(targets=[st_target], value=default_value)
else:
init_node = ast.AnnAssign(target=st_target, value=default_value, annotation=annotation)
try:
assert not self.visiting_arg_default_value
self.visiting_arg_default_value = True
self.visit(init_node)
finally:
self.visiting_arg_default_value = False
# initialize function
visibility = "public" if self.is_kernel else "private"
fn_ty = self.prototype.serialize(self.builder)
self.fn = self.builder.get_or_insert_function(self.module, self.function_name, fn_ty, visibility, self.noinline)
self.module.push_back(self.fn)
entry = self.fn.add_entry_block()
arg_values = self.prototype.deserialize(self.fn)
if self.caller_context is not None:
self.caller_context.initialize_callee(self.fn, self.builder)
# bind arguments to symbols
for arg_name, arg_value in zip(arg_names, arg_values):
self._maybe_set_loc_to_name(arg_value, arg_name)
self.set_value(arg_name, arg_value)
insert_pt = self.builder.get_insertion_block()
self.builder.set_insertion_point_to_start(entry)
# visit function body
self.visit_compound_statement(node.body)
# finalize function
assert not self.builder.get_insertion_block().has_terminator()
if self.ret_type is None or self.ret_type == language.void:
self.ret_type = language.void
self.builder.ret([])
else:
if isinstance(self.ret_type, language.tuple_type):
self.prototype.ret_types = self.ret_type.types
else:
self.prototype.ret_types = [self.ret_type]
self.fn.reset_type(self.prototype.serialize(self.builder))
self.builder.ret([self.builder.create_poison(ty) for ty in self.prototype.return_types_ir(self.builder)])
self.fn.finalize()
if insert_pt:
self.builder.set_insertion_point_to_end(insert_pt)
def visit_arguments(self, node):
arg_names = []
for arg in node.args:
arg_names += [self.visit(arg)]
kwarg_names = self.visit(node.kwarg)
return arg_names, kwarg_names
def visit_arg(self, node):
ast.NodeVisitor.generic_visit(self, node)
return node.arg
def visit_AnnAssign(self, node):
# extract attributes
annotation = self.visit(node.annotation)
target = self.visit(node.target)
value = self.visit(node.value)
# constexpr
if annotation == constexpr:
if target in self.lscope:
raise ValueError(f'{target} is already defined.'
f' constexpr cannot be reassigned.')
value = constexpr(value)
self.lscope[target] = value
return self.lscope[target]
# default: call visit_Assign
return self.visit_Assign(node)
def assignTarget(self, target, value):
assert isinstance(target.ctx, ast.Store)
if isinstance(target, ast.Subscript):
return self.visit_Subscript_Store(target, value)
if isinstance(target, ast.Tuple):
for i, target in enumerate(target.elts):
self.assignTarget(target, value.values[i])
return
if isinstance(target, ast.Attribute):
raise NotImplementedError("Attribute assignment is not supported in triton")
assert isinstance(target, ast.Name)
self.set_value(self.visit(target), value)
def visit_Assign(self, node):
# construct values to assign
def _sanitize_value(value):
if isinstance(value, language.tuple):
return _apply_to_tuple_values(value, _sanitize_value)
native_nontensor_types = (language.dtype, language.tuple)
value = _unwrap_if_constexpr(value)
if value is not None and \
not _is_triton_value(value) and \
not isinstance(value, native_nontensor_types):
value = self.semantic.to_tensor(value)
return value
targets = [node.target] if isinstance(node, ast.AnnAssign) else node.targets
assert len(targets) == 1
target = targets[0]
if isinstance(target, ast.Name):
with self._name_loc_prefix(target.id):
values = _sanitize_value(self.visit(node.value))
else:
values = _sanitize_value(self.visit(node.value))
self.assignTarget(target, values)
def visit_AugAssign(self, node):
lhs = copy.deepcopy(node.target)
lhs.ctx = ast.Load()
rhs = ast.BinOp(lhs, node.op, node.value)
assign = ast.Assign(targets=[node.target], value=rhs)
self.visit(assign)
return self.visit(lhs)
def visit_Name(self, node):
if type(node.ctx) is ast.Store:
return node.id
return self.dereference_name(node.id)
def visit_Store(self, node):
ast.NodeVisitor.generic_visit(self, node)
def visit_Load(self, node):
ast.NodeVisitor.generic_visit(self, node)
def visit_Tuple(self, node):
args = [self.visit(x) for x in node.elts]
return language.tuple(args)
def _apply_binary_method(self, method_name, lhs, rhs):
# TODO: raise something meaningful if getattr fails below, esp for reverse method
if _is_triton_tensor(lhs):
return getattr(lhs, method_name)(rhs, _semantic=self.semantic)
if _is_triton_tensor(rhs):
reverse_method_name = re.sub(r"__(.*)__", r"__r\1__", method_name)
return getattr(rhs, reverse_method_name)(lhs, _semantic=self.semantic)
if not isinstance(lhs, (constexpr, language.tuple)) and isinstance(rhs, constexpr):
lhs = constexpr(lhs)
return getattr(lhs, method_name)(rhs)
def visit_BinOp(self, node):
lhs = self.visit(node.left)
rhs = self.visit(node.right)
method_name = self._method_name_for_bin_op.get(type(node.op))
if method_name is None:
raise self._unsupported(node,
"AST binary operator '{}' is not (currently) implemented.".format(node.op.__name__))
return self._apply_binary_method(method_name, lhs, rhs)
_method_name_for_bin_op: Dict[Type[ast.operator], str] = {
ast.Add: '__add__',
ast.Sub: '__sub__',
ast.Mult: '__mul__',
ast.Div: '__truediv__',
ast.FloorDiv: '__floordiv__',
ast.Mod: '__mod__',
ast.Pow: '__pow__',
ast.LShift: '__lshift__',
ast.RShift: '__rshift__',
ast.BitAnd: '__and__',
ast.BitOr: '__or__',
ast.BitXor: '__xor__',
}
def visit_then_else_blocks(self, node, liveins, then_block, else_block):
# then block
self.builder.set_insertion_point_to_start(then_block)
self.visit_compound_statement(node.body)
then_block = self.builder.get_insertion_block()
then_defs = self.local_defs.copy()
then_vals = self.lscope.copy()
# else block
else_defs = {}
else_vals = liveins.copy()
if node.orelse:
self.builder.set_insertion_point_to_start(else_block)
self.lscope = liveins.copy()
self.local_defs = {}
self.visit_compound_statement(node.orelse)
else_defs = self.local_defs.copy()
else_block = self.builder.get_insertion_block()
else_vals = self.lscope.copy()
# update block arguments
names = []
# variables in livein whose value is updated in `if`
for name, value in liveins.items():
# livein variable changed value in either then or else
if not _is_triton_value(value):
continue
then_handles = flatten_values_to_ir([then_vals[name]])
else_handles = flatten_values_to_ir([else_vals[name]])
if then_handles == else_handles:
continue
names.append(name)
then_defs[name] = then_vals[name]
else_defs[name] = else_vals[name]
# check type
for defs, block_name in [(then_defs, 'then'), (else_defs, 'else')]:
type_equal = type(defs[name]) == type(value) # noqa: E721
assert type_equal and defs[name].type == value.type, \
f'initial value for `{name}` is of type {value}, '\
f'but the {block_name} block redefines it as {defs[name]}'
# variables that are both in then and else but not in liveins
# TODO: could probably be cleaned up
for name in sorted(then_defs.keys() & else_defs.keys()):
if name in names:
continue
then_val = then_defs[name]
then_ty = then_val.type
else_val = else_defs[name]
else_ty = else_val.type
type_equal = type(then_val) == type(else_val) # noqa: E721
assert type_equal and then_ty == else_ty, \
f'Mismatched type for {name} between then block ({then_ty}) '\
f'and else block ({else_ty})'
names.append(name)
return then_defs, else_defs, then_block, else_block, names
def visit_if_top_level(self, cond, node):
with enter_sub_region(self) as sr:
liveins, ip_block = sr
then_block = self.builder.create_block()
else_block = self.builder.create_block()
# create branch
self.builder.set_insertion_point_to_end(ip_block)
self.builder.create_cond_branch(cond.handle, then_block, else_block)
# visit then and else blocks
then_defs, else_defs, then_block, else_block, names = \
self.visit_then_else_blocks(node, liveins, then_block, else_block)
# create basic-block after conditional
endif_block = self.builder.create_block()
# then terminator
self.builder.set_insertion_point_to_end(then_block)
assert not then_block.has_terminator(), f"{then_block}"
then_handles = flatten_values_to_ir(then_defs[name] for name in names)
self.builder.create_branch(endif_block, then_handles)
# else terminator
self.builder.set_insertion_point_to_end(else_block)
assert not else_block.has_terminator(), f"{else_block}"
else_handles = flatten_values_to_ir(else_defs[name] for name in names)
self.builder.create_branch(endif_block, else_handles)
assert len(then_handles) == len(else_handles)
for then_h, else_h in zip(then_handles, else_handles):
ty = then_h.get_type()
assert ty == else_h.get_type()
endif_block.add_argument(ty)
# change block
self.builder.set_insertion_point_to_start(endif_block)
# update value
res_handles = [endif_block.arg(i) for i in range(len(then_handles))]
types = [then_defs[name].type for name in names]
new_values = unflatten_ir_values(res_handles, types)
for name, new_value in zip(names, new_values):
self.set_value(name, new_value)
# TODO: refactor
def visit_if_scf(self, cond, node):
with enter_sub_region(self) as sr:
liveins, _ = sr
ip, last_loc = self._get_insertion_point_and_loc()
then_block = self.builder.create_block()
else_block = self.builder.create_block() if node.orelse else None
then_defs, else_defs, then_block, else_block, names = \
self.visit_then_else_blocks(node, liveins, then_block, else_block)
# create if op
then_handles = flatten_values_to_ir(then_defs[name] for name in names)
for name, val in zip(names, then_handles):
self._maybe_set_loc_to_name(val, name)
self._set_insertion_point_and_loc(ip, last_loc)
if_op = self.builder.create_if_op([h.get_type() for h in then_handles], cond.handle, True)
then_block.merge_block_before(if_op.get_then_block())
self.builder.set_insertion_point_to_end(if_op.get_then_block())
if len(names) > 0:
self.builder.create_yield_op(then_handles)
if not node.orelse:
else_block = if_op.get_else_block()
else:
else_block.merge_block_before(if_op.get_else_block())
self.builder.set_insertion_point_to_end(if_op.get_else_block())
if len(names) > 0:
else_handles = flatten_values_to_ir(else_defs[name] for name in names)
for name, val in zip(names, else_handles):
self._maybe_set_loc_to_name(val, name)
self.builder.create_yield_op(else_handles)
# update values
res_handles = [if_op.get_result(i) for i in range(len(then_handles))]
types = [then_defs[name].type for name in names]
new_values = unflatten_ir_values(res_handles, types)
for name, new_value in zip(names, new_values):
self.set_value(name, new_value)
def visit_If(self, node):
cond = self.visit(node.test)
if _is_triton_tensor(cond):
if _is_non_scalar_tensor(cond):
raise self._unsupported(node, "Boolean value of Tensor with more than one value is ambiguous")
if cond.type.is_block():
warnings.warn(
"If conditional called with multidimensional Tensor instead of scalar; please use \"if (%s).item()\" instead"
% ast.unparse(node.test))
cond = language.core._unsplat(cond, _semantic=self.semantic, _generator=self)
cond = cond.to(language.int1, _semantic=self.semantic)
if ContainsReturnChecker(self.gscope).visit(node):
if self.scf_stack:
raise self._unsupported(
node, "Cannot have `return` statements inside `while` or `for` statements in triton.")
self.visit_if_top_level(cond, node)
else:
self.visit_if_scf(cond, node)
else:
cond = _unwrap_if_constexpr(cond)
# not isinstance - we insist the real thing, no subclasses and no ducks
if type(cond) not in _condition_types:
raise self._unsupported(
node, "`if` conditionals can only accept values of type {{{}}}, not objects of type {}".format(
', '.join(_.__name__ for _ in _condition_types),
type(cond).__name__))
active_block = node.body if cond else node.orelse
self.visit_compound_statement(active_block)
def visit_IfExp(self, node):
cond = self.visit(node.test)
if _is_triton_tensor(cond):
cond = cond.to(language.int1, _semantic=self.semantic)
# TODO: Deal w/ more complicated return types (e.g tuple)
with enter_sub_region(self):
ip, last_loc = self._get_insertion_point_and_loc()
then_block = self.builder.create_block()
self.builder.set_insertion_point_to_start(then_block)
then_val = self.semantic.to_tensor(self.visit(node.body))
then_block = self.builder.get_insertion_block()
else_block = self.builder.create_block()
self.builder.set_insertion_point_to_start(else_block)
# do not need to reset lscope since
# ternary expressions cannot define new variables
else_val = self.semantic.to_tensor(self.visit(node.orelse))
else_block = self.builder.get_insertion_block()
self._set_insertion_point_and_loc(ip, last_loc)
assert then_val.type == else_val.type, \
f'Ternary expression with dynamic condition has inconsistent types {then_val.type} and {else_val.type}'
ret_type = then_val.type
ret_type_ir = [ret_type.to_ir(self.builder)] if ret_type != language.void else []
if_op = self.builder.create_if_op(ret_type_ir, cond.handle, True)
then_block.merge_block_before(if_op.get_then_block())
if ret_type_ir:
self.builder.set_insertion_point_to_end(if_op.get_then_block())
self.builder.create_yield_op([then_val.handle])
self.builder.set_insertion_point_to_end(if_op.get_then_block())
else_block.merge_block_before(if_op.get_else_block())
if ret_type_ir:
self.builder.set_insertion_point_to_end(if_op.get_else_block())
self.builder.create_yield_op([else_val.handle])
return language.core.tensor(if_op.get_result(0), ret_type) if ret_type_ir else None
else:
cond = _unwrap_if_constexpr(cond)
# not isinstance - we insist the real thing, no subclasses and no ducks
if type(cond) not in _condition_types:
raise self._unsupported(
node, "`if` conditionals can only accept values of type {{{}}}, not objects of type {}".format(
', '.join(_.__name__ for _ in _condition_types),
type(cond).__name__))
if cond:
return self.visit(node.body)
else:
return self.visit(node.orelse)
def visit_With(self, node):
# Lower `with` statements by constructing context managers and calling their enter/exit hooks
# Instantiate each context manager with builder injection
if len(node.items) == 1: # Handle async_task
context = node.items[0].context_expr
withitemClass = self.visit(context.func)
if withitemClass == language.async_task:
args = [self.visit(arg) for arg in context.args]
with withitemClass(*args, _builder=self.builder):
self.visit_compound_statement(node.body)
return
cm_list = []
for item in node.items:
call = item.context_expr
fn = self.visit(call.func)
args = [self.visit(arg) for arg in call.args]
kws = dict(self.visit(kw) for kw in call.keywords)
cm = fn(*args, _semantic=self.semantic, **kws)
cm_list.append(cm)
for cm, item in zip(cm_list, node.items):
res = cm.__enter__()
if item.optional_vars is not None:
var_name = self.visit(item.optional_vars)
self.set_value(var_name, res)
if ContainsReturnChecker(self.gscope).visit(node):
raise self._unsupported(node, "Cannot have `return` statements inside `with` statements in triton ")
self.visit_compound_statement(node.body)
for cm in reversed(cm_list):
cm.__exit__(None, None, None)
def visit_Pass(self, node):
pass
def visit_Compare(self, node):
if not (len(node.comparators) == 1 and len(node.ops) == 1):
raise self._unsupported(node, "simultaneous multiple comparison is not supported")
lhs = self.visit(node.left)
rhs = self.visit(node.comparators[0])
lhs_value = _unwrap_if_constexpr(lhs)
rhs_value = _unwrap_if_constexpr(rhs)
if type(node.ops[0]) is ast.Is:
return constexpr(lhs_value is rhs_value)
if type(node.ops[0]) is ast.IsNot:
return constexpr(lhs_value is not rhs_value)
method_name = self._method_name_for_comp_op.get(type(node.ops[0]))
if method_name is None:
raise self._unsupported(
node, "AST comparison operator '{}' is not (currently) implemented.".format(node.ops[0].__name__))
return self._apply_binary_method(method_name, lhs, rhs)
_method_name_for_comp_op: Dict[Type[ast.cmpop], str] = {
ast.Eq: '__eq__', ast.NotEq: '__ne__', ast.Lt: '__lt__', ast.LtE: '__le__', ast.Gt: '__gt__', ast.GtE: '__ge__'
}
def visit_UnaryOp(self, node):
operand = self.visit(node.operand)
fn = self._method_name_for_unary_op.get(type(node.op))
if fn is None:
raise self._unsupported(node, f"AST unary operator '{node.op.__name__}' is not (currently) implemented.")
if _is_triton_tensor(operand):
return getattr(operand, fn)(_semantic=self.semantic)
try:
return getattr(operand, fn)()
except AttributeError:
if fn == "__not__":
return constexpr(not operand)
raise self._unsupported(
node, f"AST unary operator '{fn}' is not (currently) implemented on type {type(operand).__name__}")
_method_name_for_unary_op: Dict[Type[ast.unaryop], str] = {
ast.USub: '__neg__', ast.UAdd: '__pos__', ast.Not: '__not__', ast.Invert: '__invert__'
}
def _verify_loop_carried_variable(self, name, loop_val, live_val):
assert _is_triton_value(loop_val), f'cannot reassign constexpr {name} in the loop'
assert _is_triton_value(live_val), f'cannot reassign constexpr {name} in the loop'
assert type(loop_val) is type(live_val), (
f'Loop carried variable {name} changed type, was {type(loop_val)} but is now {type(live_val)}')
assert not _is_triton_tensor(loop_val) or loop_val.type == live_val.type, \
f'Loop-carried variable {name} has initial type {live_val.type} '\
f'but is re-assigned to {loop_val.type} in loop! '\
f'Please make sure that the type stays consistent.'
def visit_withitem(self, node):
return self.visit(node.context_expr)
def visit_While(self, node):
with enter_sub_region(self) as sr:
liveins, insert_block = sr
ip, last_loc = self._get_insertion_point_and_loc()
names, init_handles, init_fe_tys = self._find_carries(node, liveins)
init_tys = [h.get_type() for h in init_handles]
self._set_insertion_point_and_loc(ip, last_loc)
while_op = self.builder.create_while_op(init_tys, init_handles)
# merge the condition region
before_block = self.builder.create_block_with_parent(while_op.get_before(), init_tys)
self.builder.set_insertion_point_to_start(before_block)
block_args = [before_block.arg(i) for i in range(len(init_handles))]
condition_args = unflatten_ir_values(block_args, init_fe_tys)
for name, val in zip(names, condition_args):
self.lscope[name] = val
self.local_defs[name] = val
self._maybe_set_loc_to_name(val, name)
cond = self.visit(node.test)
if isinstance(cond, language.condition):
if cond.disable_licm:
while_op.set_attr("llvm.loop_annotation", self.builder.get_disable_loop_licm_attr())
cond = cond.condition
self.builder.set_insertion_point_to_end(before_block)
# create ConditionOp: e.g., scf.condition(%cond) %arg0, %arg1, ...
self.builder.create_condition_op(cond.handle, block_args)
# merge the loop body
after_block = self.builder.create_block_with_parent(while_op.get_after(), init_tys)
# generate loop body
self.builder.set_insertion_point_to_start(after_block)
body_handles = [after_block.arg(i) for i in range(len(init_handles))]
body_args = unflatten_ir_values(body_handles, init_fe_tys)
for name, val in zip(names, body_args):
self.lscope[name] = val
self.local_defs[name] = val
self._maybe_set_loc_to_name(val, name)
self.scf_stack.append(node)
self.visit_compound_statement(node.body)
self.scf_stack.pop()
yield_handles = flatten_values_to_ir(self.lscope[name] for name in names)
self.builder.create_yield_op(yield_handles)
# WhileOp defines new values, update the symbol table (lscope, local_defs)
result_handles = [while_op.get_result(i) for i in range(len(init_handles))]
result_vals = unflatten_ir_values(result_handles, init_fe_tys)
for name, new_def in zip(names, result_vals):
self.lscope[name] = new_def
self.local_defs[name] = new_def
self._maybe_set_loc_to_name(new_def, name)
for stmt in node.orelse:
assert False, "Not implemented"
ast.NodeVisitor.generic_visit(self, stmt)
def visit_Subscript_Load(self, node):
assert isinstance(node.ctx, ast.Load)
lhs = self.visit(node.value)
slices = self.visit(node.slice)
if _is_triton_value(lhs):
return self.call_Method(node, lhs.__getitem__, lhs, [slices], {})
return lhs[slices]
def visit_Subscript_Store(self, node, value):
raise NotImplementedError("__setitem__ is not supported in triton")
def visit_Subscript(self, node):
return self.visit_Subscript_Load(node)
def visit_ExtSlice(self, node):
return [self.visit(dim) for dim in node.dims]
def visit_For(self, node):
IteratorClass = self.visit(node.iter.func)
iter_args = [self.visit(arg) for arg in node.iter.args]
iter_kwargs = dict(self.visit(keyword) for keyword in node.iter.keywords)
if IteratorClass == language.static_range:
iterator = IteratorClass(*iter_args, **iter_kwargs)
static_range = range(iterator.start.value, iterator.end.value, iterator.step.value)
for i in static_range:
self.lscope[node.target.id] = constexpr(i)
self.visit_compound_statement(node.body)
for stmt in node.orelse:
ast.NodeVisitor.generic_visit(self, stmt)
return
num_stages = None
loop_unroll_factor = None
disallow_acc_multi_buffer = False
flatten = False
warp_specialize = False
disable_licm = False
if IteratorClass is language.range:
iterator = IteratorClass(*iter_args, **iter_kwargs)
# visit iterator arguments
# note: only `range` iterator is supported now
# collect lower bound (lb), upper bound (ub), and step
lb = iterator.start
ub = iterator.end
step = iterator.step
num_stages = iterator.num_stages
loop_unroll_factor = iterator.loop_unroll_factor
disallow_acc_multi_buffer = iterator.disallow_acc_multi_buffer
flatten = iterator.flatten
warp_specialize = iterator.warp_specialize
disable_licm = iterator.disable_licm
elif IteratorClass is range:
# visit iterator arguments
# note: only `range` iterator is supported now
# collect lower bound (lb), upper bound (ub), and step
lb = iter_args[0] if len(iter_args) > 1 else self.visit(ast.Num(0))
ub = iter_args[1] if len(iter_args) > 1 else self.visit(node.iter.args[0])
step = iter_args[2] if len(iter_args) > 2 else self.visit(ast.Num(1))
else:
raise RuntimeError('Only `range` and `static_range` iterators are currently supported')
# handle negative constant step (not supported by scf.for in MLIR)
negative_step = False
if _is_constexpr(step) and step.value < 0:
step = constexpr(-step.value)
negative_step = True
lb, ub = ub, lb
lb = self.semantic.to_tensor(lb)
ub = self.semantic.to_tensor(ub)
step = self.semantic.to_tensor(step)
# induction variable type
if not lb.dtype.is_int() or not ub.dtype.is_int() or not step.dtype.is_int():
raise TypeError(f"For loop bounds and step must all be ints, are ({lb.dtype}, {ub.dtype}, {step.dtype})")
iv_type = self.semantic.integer_promote_impl(lb.dtype, ub.dtype)
iv_type = self.semantic.integer_promote_impl(iv_type, step.dtype)
iv_ir_type = iv_type.to_ir(self.builder)
iv_is_signed = iv_type.int_signedness == language.core.dtype.SIGNEDNESS.SIGNED
# lb/ub/step might be constexpr, we need to cast them to tensor
lb = lb.handle
ub = ub.handle
step = step.handle
# ForOp can only accept IndexType as lb/ub/step. Cast integer to Index
lb = self.builder.create_int_cast(lb, iv_ir_type, iv_is_signed)
ub = self.builder.create_int_cast(ub, iv_ir_type, iv_is_signed)
step = self.builder.create_int_cast(step, iv_ir_type, iv_is_signed)
# Create placeholder for the loop induction variable
iv = self.builder.create_poison(iv_ir_type)
self.set_value(node.target.id, language.core.tensor(iv, iv_type))
with enter_sub_region(self) as sr:
liveins, insert_block = sr
ip, last_loc = self._get_insertion_point_and_loc()
names, init_handles, init_tys = self._find_carries(node, liveins)
# create ForOp
self._set_insertion_point_and_loc(ip, last_loc)
for_op = self.builder.create_for_op(lb, ub, step, init_handles)
if _unwrap_if_constexpr(num_stages) is not None:
for_op.set_attr("tt.num_stages", self.builder.get_int32_attr(num_stages))
if _unwrap_if_constexpr(loop_unroll_factor) is not None:
for_op.set_attr("tt.loop_unroll_factor", self.builder.get_int32_attr(loop_unroll_factor))
if disallow_acc_multi_buffer:
for_op.set_attr("tt.disallow_acc_multi_buffer", self.builder.get_unit_attr())
if flatten:
for_op.set_attr("tt.flatten", self.builder.get_unit_attr())
if warp_specialize:
for_op.set_attr("tt.warp_specialize", self.builder.get_unit_attr())
if disable_licm:
for_op.set_attr("llvm.loop_annotation", self.builder.get_disable_loop_licm_attr())
self.scf_stack.append(node)
for_op_body = for_op.get_body(0)
self.builder.set_insertion_point_to_start(for_op_body)
block_handles = [for_op_body.arg(i + 1) for i in range(len(init_handles))]
block_args = unflatten_ir_values(block_handles, init_tys)
for name, val in zip(names, block_args):
self._maybe_set_loc_to_name(val, name)
self.set_value(name, val)
self.visit_compound_statement(node.body)
self.scf_stack.pop()
yield_handles = flatten_values_to_ir(self.lscope[name] for name in names)
# create YieldOp
if len(yield_handles) > 0:
self.builder.create_yield_op(yield_handles)
for_op_region = for_op_body.get_parent()
assert for_op_region.size() == 1, "We use SCF, so the loop body should only have one block"
# update induction variable with actual value, and replace all uses
self.builder.set_insertion_point_to_start(for_op_body)
iv = for_op.get_induction_var()
if negative_step:
iv = self.builder.create_sub(ub, iv)
iv = self.builder.create_add(iv, lb)
self.lscope[node.target.id].handle.replace_all_uses_with(iv)
self.set_value(node.target.id, language.core.tensor(iv, iv_type))
self._maybe_set_loc_to_name(iv, node.target.id)
# update lscope & local_defs (ForOp defines new values)
result_handles = [for_op.get_result(i) for i in range(len(init_handles))]
result_values = unflatten_ir_values(result_handles, init_tys)
for name, val in zip(names, result_values):
self.set_value(name, val)
self._maybe_set_loc_to_name(val, name)
for stmt in node.orelse:
assert False, "Don't know what to do with else after for"
ast.NodeVisitor.generic_visit(self, stmt)
def visit_Slice(self, node):
lower = self.visit(node.lower)
upper = self.visit(node.upper)
step = self.visit(node.step)
return language.slice(lower, upper, step)
def visit_Index(self, node):
return self.visit(node.value)
def visit_keyword(self, node) -> Tuple[str, Any]:
return node.arg, self.visit(node.value)
def visit_Assert(self, node) -> Any:
test = self.visit(node.test)
msg = self.visit(node.msg) if node.msg is not None else ""
return language.core.device_assert(test, msg, _semantic=self.semantic)
def call_JitFunction(self, fn: JITFunction, args, kwargs, caller_context=None):
args = inspect.getcallargs(fn.fn, *args, **kwargs)
args = [args[name] for name in fn.arg_names]
for i, arg in enumerate(args):
if isinstance(arg, (language.dtype, float, int, bool, JITFunction)):
args[i] = language.core.constexpr(arg)
args_cst = find_paths_if(args, lambda _, x: _is_constexpr(x))
args_cst = {path: get_iterable_path(args, path) for path in args_cst}
args_path = find_paths_if(args, lambda _, x: not _is_constexpr(x))
args_val = [get_iterable_path(args, path) for path in args_path]
# mangle
caller_context = caller_context or self.caller_context
fn_name = mangle_fn(get_full_name(fn), [arg.type for arg in args_val], args_cst, caller_context)
# generate function def if necessary
if not self.module.has_function(fn_name):
# If the callee is not set, we use the same debug setting as the caller
file_name, begin_line = get_jit_fn_file_line(fn)
arg_types = [
language.core.constexpr if arg is None or isinstance(arg,
(bool, int, language.core.dtype)) else arg.type
for arg in args
]
prototype = ASTFunction([], arg_types, args_cst, dict())
generator = CodeGenerator(self.context, prototype, fn.get_capture_scope(), module=self.module, jit_fn=fn,
function_name=fn_name, function_types=self.function_ret_types,
noinline=fn.noinline, file_name=file_name, begin_line=begin_line,
options=self.builder.options, codegen_fns=self.builder.codegen_fns,
module_map=self.builder.module_map, caller_context=caller_context,
is_gluon=self.is_gluon)
try:
generator.visit(fn.parse())
except Exception as e:
# Wrap the error in the callee with the location of the call.
if knobs.compilation.front_end_debugging:
raise
raise CompilationError(self.jit_fn.src, self.cur_node, None) from e
callee_ret_type = generator.ret_type
self.function_ret_types[fn_name] = callee_ret_type
else:
callee_ret_type = self.function_ret_types[fn_name]
symbol = self.module.get_function(fn_name)
args_val = flatten_values_to_ir(args_val)
call_op = self.builder.call(symbol, args_val)
if callee_ret_type == language.void:
return None
handles = [call_op.get_result(i) for i in range(call_op.get_num_results())]
return next(unflatten_ir_values(handles, [callee_ret_type]))
def call_Function(self, node, fn, args, kws):
if isinstance(fn, (BoundJITMethod, BoundConstexprFunction)):
args.insert(0, fn.__self__)
fn = fn.__func__
if isinstance(fn, JITFunction):
_check_fn_args(node, fn, args)
return self.call_JitFunction(fn, args, kws)
if (hasattr(fn, '__self__') and _is_triton_value(fn.__self__)) or language.core.is_builtin(fn) or isinstance(
fn, ConstexprFunction):
extra_kwargs = dict()
if isinstance(fn, ConstexprFunction):
sig = inspect.signature(fn.__call__)
else:
sig = inspect.signature(fn)
if '_semantic' in sig.parameters:
extra_kwargs["_semantic"] = self.semantic
if '_generator' in sig.parameters:
extra_kwargs['_generator'] = self
try:
ret = fn(*args, **extra_kwargs, **kws)
# builtin functions return plain tuples for readability
if isinstance(ret, tuple):
ret = language.tuple(ret)
return ret
except Exception as e:
if knobs.compilation.front_end_debugging:
raise
# Normally when we raise a CompilationError, we raise it as
# `from None`, because the original fileline from the exception
# is not relevant (and often points into code_generator.py
# itself). But when calling a function, we raise as `from e` to
# preserve the traceback of the original error, which may e.g.
# be in core.py.
raise CompilationError(self.jit_fn.src, node, str(e)) from e
if fn in self.builtin_namespace.values():
args = map(_unwrap_if_constexpr, args)
ret = fn(*args, **kws)
def wrap_constexpr(x):
if _is_triton_value(x):
return x
return constexpr(x)
if isinstance(ret, (builtins.tuple, language.tuple)):
return _apply_to_tuple_values(ret, wrap_constexpr)
return wrap_constexpr(ret)
def call_Method(self, node, fn, fn_self, args, kws):
if isinstance(fn, JITFunction):
args.insert(0, fn_self)
return self.call_Function(node, fn, args, kws)
def visit_Call(self, node):
fn = _unwrap_if_constexpr(self.visit(node.func))
if not isinstance(fn, BoundJITMethod):
static_implementation = self.statically_implemented_functions.get(fn)
if static_implementation is not None:
return static_implementation(self, node)
mur = getattr(fn, '_must_use_result', False)
if mur and getattr(node, '_is_unused', False):
error_message = ["The result of %s is not being used." % ast.unparse(node.func)]
if isinstance(mur, str):
error_message.append(mur)
raise CompilationError(self.jit_fn.src, node, " ".join(error_message))
kws = dict(self.visit(keyword) for keyword in node.keywords)
args = [self.visit(arg) for arg in node.args]
args = list(itertools.chain.from_iterable(x if isinstance(x, list) else [x] for x in args))
return self.call_Function(node, fn, args, kws)
def visit_Constant(self, node):
return constexpr(node.value)
def visit_BoolOp(self, node: ast.BoolOp):
method_name = self._method_name_for_bool_op.get(type(node.op))
if method_name is None:
raise self._unsupported(
node, "AST boolean operator '{}' is not (currently) implemented.".format(node.op.__name__))
nontrivial_values = []
for subnode in node.values:
# we visit the values in order, executing their side-effects
# and possibly early-exiting:
value = self.visit(subnode)
if not _is_triton_tensor(value):
# this is a constexpr, so we might be able to short-circuit:
bv = bool(value)
if (bv is False) and (method_name == "logical_and"):
# value is falsey so return that:
return value
if (bv is True) and (method_name == "logical_or"):
# value is truthy so return that:
return value
# otherwise, our constexpr has no effect on the output of the
# expression so we do not append it to nontrivial_values.
else:
if value.type.is_block():
lineno = getattr(node, "lineno", None)
if lineno is not None:
lineno += self.begin_line
warnings.warn_explicit(
"Logical operators 'and' and 'or' are deprecated for non-scalar tensors; please use '&' or '|' instead",
category=UserWarning,
filename=self.file_name,
lineno=lineno,
source=ast.unparse(node),
)
# not a constexpr so we must append it:
nontrivial_values.append(value)
if len(nontrivial_values) == 0:
# the semantics of a disjunction of falsey values or conjunction
# of truthy values is to return the final value:
nontrivial_values.append(value)
while len(nontrivial_values) >= 2:
rhs = nontrivial_values.pop()
lhs = nontrivial_values.pop()
res = self._apply_binary_method(method_name, lhs, rhs)
nontrivial_values.append(res)
assert len(nontrivial_values) == 1
return nontrivial_values[0]
_method_name_for_bool_op: Dict[Type[ast.boolop], str] = {ast.And: 'logical_and', ast.Or: 'logical_or'}
def visit_Attribute(self, node):
lhs = self.visit(node.value)
if _is_triton_tensor(lhs) and node.attr == "T":
return self.semantic.permute(lhs, (1, 0))
# NOTE: special case ".value" for BC
if isinstance(lhs, constexpr) and node.attr not in ("value", "type"):
lhs = lhs.value
attr = getattr(lhs, node.attr)
if _is_triton_value(lhs) and isinstance(attr, JITFunction):
return BoundJITMethod(lhs, attr)
return attr
def visit_Expr(self, node):
node.value._is_unused = True
ast.NodeVisitor.generic_visit(self, node)
def visit_NoneType(self, node):
return None
def visit_JoinedStr(self, node):
values = list(node.values)
for i, value in enumerate(values):
if isinstance(value, ast.Constant):
values[i] = str(value.value)
elif isinstance(value, ast.FormattedValue):
conversion_code = value.conversion
evaluated = self.visit(value.value)
if not _is_constexpr(evaluated):
raise self._unsupported(
node,
"Cannot evaluate f-string containing non-constexpr conversion values, found conversion of type "
+ str(type(evaluated)))
values[i] = ("{}" if conversion_code < 0 else "{!" + chr(conversion_code) + "}").format(evaluated.value)
else:
raise AssertionError("encountered unexpected node of type {} in a JoinedStr node".format(type(value)))
return ''.join(values)
def visit(self, node):
if node is None:
return
with warnings.catch_warnings():
# The ast library added visit_Constant and deprecated some other
# methods but we can't move to that without breaking Python 3.6 and 3.7.
warnings.simplefilter("ignore", DeprecationWarning) # python 3.9
warnings.simplefilter("ignore", PendingDeprecationWarning) # python 3.8
last_node = self.cur_node
last_loc = self.builder.get_loc()
self.cur_node = node
if hasattr(node, 'lineno') and hasattr(node, 'col_offset'):
here_loc = self.builder.create_loc(self.file_name, self.begin_line + node.lineno, node.col_offset)
if self.name_loc_as_prefix is not None:
self.builder.set_loc(self.builder.create_name_loc(self.name_loc_as_prefix, here_loc))
else:
self.builder.set_loc(here_loc)
last_loc = self.builder.get_loc()
try:
ret = super().visit(node)
except CompilationError:
raise
except Exception as e:
if knobs.compilation.front_end_debugging:
raise
# Wrap the error in a CompilationError which contains the source
# of the @jit function.
raise CompilationError(self.jit_fn.src, self.cur_node, repr(e)) from None
# Reset the location to the last one before the visit
if last_loc:
self.cur_node = last_node
self.builder.set_loc(last_loc)
return ret
def generic_visit(self, node):
raise self._unsupported(node, "unsupported AST node type: {}".format(type(node).__name__))
def execute_static_assert(self, node: ast.Call) -> None:
arg_count = len(node.args)
if not (0 < arg_count <= 2) or len(node.keywords):
raise TypeError("`static_assert` requires one or two positional arguments only")
passed = _unwrap_if_constexpr(self.visit(node.args[0]))
if not isinstance(passed, bool):
raise NotImplementedError(
"Assertion condition could not be determined at compile-time. Make sure that it depends only on `constexpr` values"
)
if not passed:
if arg_count == 1:
message = ""
else:
try:
message = self.visit(node.args[1])
except Exception as e:
message = "<failed to evaluate assertion message: " + repr(e) + ">"
raise CompileTimeAssertionFailure(self.jit_fn.src, node, _unwrap_if_constexpr(message))
return None
def static_executor(python_fn):
def ret(self, node: ast.Call):
kws = {
name: _unwrap_if_constexpr(value)
for name, value in (self.visit(keyword) for keyword in node.keywords)
}
args = [_unwrap_if_constexpr(self.visit(arg)) for arg in node.args]
return constexpr(python_fn(*args, **kws))
return ret
from ..experimental.gluon import language as ttgl
statically_implemented_functions: Dict[object, Callable[[ast.Call], Any]] = {
language.core.static_assert: execute_static_assert,
language.core.static_print: static_executor(print),
ttgl.static_assert: execute_static_assert,
ttgl.static_print: static_executor(print),
int: static_executor(int),
len: static_executor(len),
}
def ast_to_ttir(fn, src, context, options, codegen_fns, module_map, module=None):
arg_types = [None] * len(fn.arg_names)
const_iter = iter(src.constants.items())
kc, vc = next(const_iter, (None, None))
for i, (ks, v) in enumerate(src.signature.items()):
idx = fn.arg_names.index(ks)
cexpr = None
if kc is not None and kc[0] == i:
cexpr = vc
kc, vc = next(const_iter, (None, None))
arg_types[idx] = str_to_ty(v, cexpr)
prototype = ASTFunction([], arg_types, src.constants, src.attrs)
file_name, begin_line = get_jit_fn_file_line(fn)
# query function representation
from collections import namedtuple
leaves = filter(lambda v: len(v) == 1, src.constants)
constants = {fn.arg_names[i[0]]: src.constants[i] for i in leaves}
signature = src.signature
proxy = namedtuple("SpecializationProxy", ["constants", "signature"])(constants, signature)
generator = CodeGenerator(context, prototype, gscope=fn.get_capture_scope(), function_name=fn.repr(proxy),
jit_fn=fn, is_kernel=True, file_name=file_name, begin_line=begin_line, options=options,
codegen_fns=codegen_fns, module_map=module_map, module=module, is_gluon=fn.is_gluon())
generator.visit(fn.parse())
module = generator.module
# module takes ownership of the context
module.context = context
if not module.verify_with_diagnostics():
if not fn.is_gluon():
print(module)
raise RuntimeError("error encountered during parsing")
return module