1304 lines
56 KiB
Python
1304 lines
56 KiB
Python
import ast
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import inspect
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import re
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import sys
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import warnings
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import os
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import textwrap
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from typing import Any, Callable, Dict, Optional, Tuple, Type, Union
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from .. import language
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from .._C.libtriton import ir
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from ..language import constexpr, tensor, str_to_ty
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from ..runtime.jit import _normalize_ty
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# ideally we wouldn't need any runtime component
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from ..runtime import JITFunction
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from .errors import (CompilationError, CompileTimeAssertionFailure, UnsupportedLanguageConstruct)
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from types import ModuleType
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def mangle_ty(ty):
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if ty.is_ptr():
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return 'P' + mangle_ty(ty.element_ty)
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if ty.is_int():
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SIGNED = language.dtype.SIGNEDNESS.SIGNED
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prefix = 'i' if ty.int_signedness == SIGNED else 'u'
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return prefix + str(ty.int_bitwidth)
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if ty.is_floating():
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return str(ty)
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if ty.is_block():
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elt = mangle_ty(ty.scalar)
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shape = '_'.join(map(str, ty.shape))
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return f'{elt}S{shape}S'
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if ty.is_void():
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return 'V'
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assert False, "Unsupported type"
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def mangle_fn(name, arg_tys, constants):
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# doesn't mangle ret type, which must be a function of arg tys
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mangled_arg_names = '_'.join([mangle_ty(ty) for ty in arg_tys])
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mangled_constants = '_'.join([f'{i}c{repr(constants[i])}' for i in sorted(constants)])
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mangled_constants = mangled_constants.replace('.', '_d_')
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mangled_constants = mangled_constants.replace("'", '_sq_')
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# [ and ] are not allowed in LLVM identifiers
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mangled_constants = mangled_constants.replace('[', '_').replace(']', '_')
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ret = f'{name}__{mangled_arg_names}__{mangled_constants}'
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return ret
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def _is_triton_tensor(o: Any) -> bool:
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return isinstance(o, tensor)
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def _is_constexpr(o: Any) -> bool:
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return isinstance(o, constexpr)
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def _is_triton_scalar(o: Any) -> bool:
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return _is_triton_tensor(o) and (not o.type.is_block() or o.type.numel == 1)
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def _is_list_like(o: Any) -> bool:
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return isinstance(o, (list, tuple))
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def _unwrap_if_constexpr(o: Any):
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return o.value if isinstance(o, constexpr) else o
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def _check_fn_args(node, fn, args):
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if fn.noinline:
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for idx, arg in enumerate(args):
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if not _is_constexpr(arg) and not _is_triton_scalar(arg):
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raise UnsupportedLanguageConstruct(
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fn.src, node,
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f'Function {fn.__name__} is marked noinline, but was called with non-scalar argument {fn.arg_names[idx]}:{arg}'
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)
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def _get_fn_file_line(fn):
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base_fn = fn
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while not isinstance(base_fn, JITFunction):
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base_fn = base_fn.fn
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file_name = base_fn.fn.__code__.co_filename
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lines, begin_line = inspect.getsourcelines(base_fn.fn)
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# Match the following pattern:
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# @triton.autotune(...) <- foo.__code__.co_firstlineno
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# @triton.heuristics(...)
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# @triton.jit
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# def foo(...): <- this line is the first line
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for idx, line in enumerate(lines):
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if line.strip().startswith("def "):
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begin_line += idx
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break
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return file_name, begin_line
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_condition_types = {bool, int, type(None)} # Python types accepted for conditionals inside kernels
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class enter_sub_region:
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def __init__(self, generator):
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self.generator = generator
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def __enter__(self):
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# record lscope & local_defs in the parent scope
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self.liveins = self.generator.lscope.copy()
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self.prev_defs = self.generator.local_defs.copy()
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self.generator.local_defs = {}
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self.insert_block = self.generator.builder.get_insertion_block()
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self.insert_point = self.generator.builder.get_insertion_point()
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return self.liveins, self.insert_block
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def __exit__(self, *args, **kwargs):
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self.generator.builder.restore_insertion_point(self.insert_point)
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self.generator.lscope = self.liveins
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self.generator.local_defs = self.prev_defs
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# Check if the given syntax node has an "early" return
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class ContainsReturnChecker(ast.NodeVisitor):
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def __init__(self, gscope):
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self.gscope = gscope
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def _visit_stmts(self, body) -> bool:
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for s in body:
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if self.visit(s):
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return True
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return False
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def _visit_function(self, fn) -> bool:
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# Currently we only support JITFunctions defined in the global scope
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if isinstance(fn, JITFunction) and not fn.noinline:
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fn_node = fn.parse()
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return ContainsReturnChecker(self.gscope).visit(fn_node)
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return False
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def generic_visit(self, node) -> bool:
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ret = False
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for _, value in ast.iter_fields(node):
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if isinstance(value, list):
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for item in value:
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if isinstance(item, ast.AST):
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ret = ret or self.visit(item)
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elif isinstance(value, ast.AST):
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ret = ret or self.visit(value)
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return ret
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def visit_Attribute(self, node: ast.Attribute) -> bool:
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# If the left part is a name, it's possible that
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# we call triton native function or a jit function from another module.
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# If the left part is not a name, it must return a tensor or a constexpr
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# whose methods do not contain return statements
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# e.g., (tl.load(x)).to(y)
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# So we only check if the expressions within value have return or not
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if isinstance(node.value, ast.Name):
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if node.value.id in self.gscope:
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value = self.gscope[node.value.id]
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fn = getattr(value, node.attr)
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return self._visit_function(fn)
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return False
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return self.visit(node.value)
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def visit_Name(self, node: ast.Name) -> bool:
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if type(node.ctx) == ast.Store:
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return False
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if node.id in self.gscope:
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fn = self.gscope[node.id]
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return self._visit_function(fn)
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return False
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def visit_Return(self, node: ast.Return) -> bool:
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return True
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def visit_Assign(self, node: ast.Assign) -> bool:
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# There couldn't be an early return
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# x = ...
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return False
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def visit_AugAssign(self, node: ast.AugAssign) -> bool:
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# There couldn't be an early return
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# x += ...
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return False
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def visit_Module(self, node: ast.Module) -> bool:
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return self._visit_stmts(node.body)
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def visit_FunctionDef(self, node: ast.FunctionDef) -> bool:
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return self._visit_stmts(node.body)
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def visit_If(self, node: ast.If) -> bool:
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# TODO: optimize the following case in which we actually don't have
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# a return when static_cond is false:
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# if dynamic_cond
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# if static_cond
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# func_with_return
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# else
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# func_without_return
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ret = self._visit_stmts(node.body)
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if node.orelse:
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ret = ret or self._visit_stmts(node.orelse)
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return ret
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def visit_IfExp(self, node: ast.IfExp) -> bool:
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return self.visit(node.body) or self.visit(node.orelse)
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def visit_Call(self, node: ast.Call) -> bool:
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return self.visit(node.func)
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class CodeGenerator(ast.NodeVisitor):
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def __init__(self, context, prototype, gscope, attributes, constants, function_name, jit_fn: JITFunction, options,
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codegen_fns, debug=None, module=None, is_kernel=False, function_types: Optional[Dict] = None,
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noinline=False, file_name: Optional[str] = None, begin_line=0):
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self.context = context
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self.builder = ir.builder(context)
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self.file_name = file_name
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# node.lineno starts from 1, so we need to subtract 1
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self.begin_line = begin_line - 1
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self.builder.set_loc(file_name, begin_line, 0)
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self.builder.options = options
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# dict of functions provided by the backend. Below are the list of possible functions:
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# Convert custom types not natively supported on HW.
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# convert_custom_types(intput_tensor, dtype, fp_downcast_rounding=None, _builder=None)
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self.builder.codegen_fns = codegen_fns
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self.module = self.builder.create_module() if module is None else module
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self.function_ret_types = {} if function_types is None else function_types
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self.prototype = prototype
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self.gscope = gscope
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self.lscope = dict()
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self.attributes = attributes
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self.constants = constants
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self.jit_fn = jit_fn
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self.function_name = function_name
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self.is_kernel = is_kernel
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self.cur_node = None
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self.debug = options.debug if debug is None else debug
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self.noinline = noinline
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self.scf_stack = []
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self.ret_type = None
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# SSA-construction
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# name => language.tensor
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self.local_defs: Dict[str, tensor] = {}
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self.dereference_name: Callable[[str], Any] = self._define_name_lookup()
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self.fn = None
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# Are we currently visiting an ast.arg's default value? These have some
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# special handling.
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self.visiting_arg_default_value = False
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builtin_namespace: Dict[str, Any] = {_.__name__: _ for _ in (len, list, range, float, int, isinstance, getattr)}
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builtin_namespace.update((
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('print', language.core.device_print),
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('min', language.minimum),
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('max', language.maximum),
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))
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def _unsupported(self, node, message):
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return UnsupportedLanguageConstruct(self.jit_fn.src, node, message)
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def _is_constexpr_global(self, name):
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absent_marker = object()
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val = self.gscope.get(name, absent_marker)
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if val is absent_marker:
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return False
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if _is_constexpr(val):
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return True
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if a := self.gscope.get("__annotations__", {}).get(name):
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return _normalize_ty(a) == "constexpr"
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return False
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def _define_name_lookup(self):
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def local_lookup(name: str, absent):
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# this needs to be re-fetched from `self` every time, because it gets switched occasionally
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return self.lscope.get(name, absent)
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def global_lookup(name: str, absent):
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val = self.gscope.get(name, absent)
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# The high-level rule is that only constexpr globals are allowed.
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# But actually a bunch of other things, such as module imports, are
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# technically Python globals. We have to allow these too!
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if (val is absent #
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or name in self.builtin_namespace #
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or type(val) == ModuleType #
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or isinstance(val, JITFunction) #
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or getattr(val, "__triton_builtin__", False) #
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or getattr(val, "__module__", "").startswith("triton.language") #
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or isinstance(val, language.dtype) #
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or self._is_constexpr_global(name) #
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# Allow accesses to globals while visiting an ast.arg
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# because you should be able to do
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# @triton.jit def fn(x: tl.constexpr = GLOBAL): ...
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or self.visiting_arg_default_value #
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or os.environ.get("TRITON_ALLOW_NON_CONSTEXPR_GLOBALS", "0") == "1"):
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return val
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raise NameError(
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textwrap.dedent(f"""\
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Cannot access global variable {name} from within @jit'ed
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function. Triton kernels can only access global variables that
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are annotated as constexpr (`x: triton.language.constexpr = 42`
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or `x = triton.language.constexpr(42)`). Alternatively, set the
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envvar TRITON_ALLOW_NON_CONSTEXPR_GLOBALS=1, but we do not
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promise to support this forever.""").replace("\n", " "))
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absent_marker = object()
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def name_lookup(name: str) -> Any:
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absent = absent_marker
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for lookup_function in local_lookup, global_lookup, self.builtin_namespace.get:
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value = lookup_function(name, absent)
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if value is not absent:
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return value
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raise NameError(f'{name} is not defined')
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return name_lookup
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def set_value(self, name: str, value: Union[tensor, constexpr]) -> None:
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''' This function:
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called by visit_Assign() & visit_FunctionDef() to store left value (lvalue)
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1. record local defined name (FIXME: should consider control flow)
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2. store tensor in self.lvalue
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'''
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self.lscope[name] = value
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self.local_defs[name] = value
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def _get_insertion_point_and_loc(self):
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# XXX: this is a hack to get the location of the insertion point.
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# The insertion point's location could be invalid sometimes,
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# so we need to explicitly set the location
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loc = self.builder.get_loc()
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ip = self.builder.get_insertion_point()
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return ip, loc
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def _set_insertion_point_and_loc(self, ip, loc):
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self.builder.restore_insertion_point(ip)
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self.builder.set_loc(loc)
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#
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# AST visitor
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#
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def visit_compound_statement(self, stmts):
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# Ensure that stmts is iterable
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if not _is_list_like(stmts):
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stmts = [stmts]
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for stmt in stmts:
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self.visit(stmt)
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# Stop parsing as soon as we hit a `return` statement; everything
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# after this is dead code.
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if isinstance(stmt, ast.Return):
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break
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def visit_Module(self, node):
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ast.NodeVisitor.generic_visit(self, node)
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def visit_List(self, node):
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ctx = self.visit(node.ctx)
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assert ctx is None
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elts = [self.visit(elt) for elt in node.elts]
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return elts
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# By design, only non-kernel functions can return
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def visit_Return(self, node):
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ret_value = self.visit(node.value)
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# ret_block = self.builder.create_block()
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# post_ret_block = self.builder.create_block()
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# self.builder.create_branch(ret_block)
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# self.builder.set_insertion_point_to_end(ret_block)
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if ret_value is None:
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self.builder.ret([])
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ret_ty = language.void
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elif isinstance(ret_value, tuple):
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ret_values = [language.core._to_tensor(v, self.builder) for v in ret_value]
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ret_types = [v.type for v in ret_values]
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self.builder.ret([v.handle for v in ret_values])
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ret_ty = tuple(ret_types)
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else:
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ret = language.core._to_tensor(ret_value, self.builder)
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self.builder.ret([ret.handle])
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ret_ty = ret.type
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# self.builder.create_branch(post_ret_block)
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# self.builder.set_insertion_point_to_end(post_ret_block)
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if self.ret_type is None:
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self.ret_type = ret_ty
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elif self.ret_type != ret_ty:
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raise TypeError(f'Inconsistent return types: {self.ret_type} and {ret_ty}')
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def visit_FunctionDef(self, node):
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arg_names, kwarg_names = self.visit(node.args)
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if self.fn:
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raise self._unsupported(node, "nested function definition is not supported.")
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# initialize defaults
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for i, default_value in enumerate(node.args.defaults):
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arg_node = node.args.args[-i - 1]
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annotation = arg_node.annotation
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name = arg_node.arg
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st_target = ast.Name(id=name, ctx=ast.Store())
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if annotation is None:
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init_node = ast.Assign(targets=[st_target], value=default_value)
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else:
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init_node = ast.AnnAssign(target=st_target, value=default_value, annotation=annotation)
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try:
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assert not self.visiting_arg_default_value
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self.visiting_arg_default_value = True
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self.visit(init_node)
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finally:
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self.visiting_arg_default_value = False
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# initialize function
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visibility = "public" if self.is_kernel else "private"
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self.fn = self.builder.get_or_insert_function(self.module, self.function_name,
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self.prototype.to_ir(self.builder), visibility, self.noinline)
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self.module.push_back(self.fn)
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entry = self.fn.add_entry_block()
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arg_values = []
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idx = 0
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for i, arg_name in enumerate(arg_names):
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if i in self.constants:
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cst = self.constants[i]
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if not _is_constexpr(cst):
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cst = constexpr(self.constants[i])
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arg_values.append(cst)
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continue
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else:
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if i in self.attributes:
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for name, value in self.attributes[i]:
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self.fn.set_arg_attr(idx, name, value)
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arg_values.append(tensor(self.fn.args(idx), self.prototype.param_types[idx]))
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idx += 1
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insert_pt = self.builder.get_insertion_block()
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for arg_name, arg_value in zip(arg_names, arg_values):
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self.set_value(arg_name, arg_value)
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self.builder.set_insertion_point_to_start(entry)
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# visit function body
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self.visit_compound_statement(node.body)
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# finalize function
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if self.ret_type is None or self.ret_type == language.void:
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self.ret_type = language.void
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self.builder.ret([])
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else:
|
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# update return type
|
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if isinstance(self.ret_type, tuple):
|
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self.prototype.ret_types = list(self.ret_type)
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self.fn.reset_type(self.prototype.to_ir(self.builder))
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else:
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self.prototype.ret_types = [self.ret_type]
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self.fn.reset_type(self.prototype.to_ir(self.builder))
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if insert_pt:
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self.builder.set_insertion_point_to_end(insert_pt)
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# Remove dead code
|
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self.fn.finalize()
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|
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def visit_arguments(self, node):
|
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arg_names = []
|
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for arg in node.args:
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arg_names += [self.visit(arg)]
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kwarg_names = self.visit(node.kwarg)
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return arg_names, kwarg_names
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|
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def visit_arg(self, node):
|
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ast.NodeVisitor.generic_visit(self, node)
|
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return node.arg
|
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|
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def visit_AnnAssign(self, node):
|
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# 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.')
|
|
if not _is_constexpr(value):
|
|
value = constexpr(value)
|
|
self.lscope[target] = value
|
|
return self.lscope[target]
|
|
# default: call visit_Assign
|
|
return self.visit_Assign(node)
|
|
|
|
def visit_Assign(self, node):
|
|
_names = []
|
|
targets = [node.target] if isinstance(node, ast.AnnAssign) else node.targets
|
|
for target in targets:
|
|
_names += [self.visit(target)]
|
|
if len(_names) > 1:
|
|
raise self._unsupported(node, "simultaneous multiple assignment is not supported.")
|
|
names = _names[0]
|
|
values = self.visit(node.value)
|
|
if not _is_list_like(names):
|
|
names = [names]
|
|
if not _is_list_like(values):
|
|
values = [values]
|
|
native_nontensor_types = (language.dtype, )
|
|
for name, value in zip(names, values):
|
|
# by default, constexpr are assigned into python variable
|
|
value = _unwrap_if_constexpr(value)
|
|
if value is not None and \
|
|
not _is_triton_tensor(value) and \
|
|
not isinstance(value, native_nontensor_types):
|
|
value = language.core._to_tensor(value, self.builder)
|
|
self.set_value(name, value)
|
|
|
|
def visit_AugAssign(self, node):
|
|
name = node.target.id
|
|
lhs = ast.Name(id=name, ctx=ast.Load())
|
|
rhs = ast.BinOp(lhs, node.op, node.value)
|
|
assign = ast.Assign(targets=[node.target], value=rhs)
|
|
self.visit(assign)
|
|
return self.dereference_name(name)
|
|
|
|
def visit_Name(self, node):
|
|
if type(node.ctx) == 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 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, _builder=self.builder)
|
|
if _is_triton_tensor(rhs):
|
|
reverse_method_name = re.sub(r"__(.*)__", r"__r\1__", method_name)
|
|
return getattr(rhs, reverse_method_name)(lhs, _builder=self.builder)
|
|
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()
|
|
# else block
|
|
else_defs = {}
|
|
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()
|
|
|
|
# update block arguments
|
|
names = []
|
|
ret_types = []
|
|
ir_ret_types = []
|
|
# variables in livein whose value is updated in `if`
|
|
for name in liveins:
|
|
# check type
|
|
for defs, block_name in [(then_defs, 'then'), (else_defs, 'else')]:
|
|
if name in defs:
|
|
assert defs[name].type == liveins[name].type, \
|
|
f'initial value for `{name}` is of type {liveins[name].type}, '\
|
|
f'but the {block_name} block redefines it as {defs[name].type}'
|
|
if name in then_defs or name in else_defs:
|
|
names.append(name)
|
|
ret_types.append(then_defs[name].type if name in then_defs else else_defs[name].type)
|
|
ir_ret_types.append(then_defs[name].handle.get_type() if name in
|
|
then_defs else else_defs[name].handle.get_type())
|
|
# variable defined in then but not in else
|
|
if name in then_defs and name not in else_defs:
|
|
else_defs[name] = liveins[name]
|
|
# variable defined in else but not in then
|
|
if name in else_defs and name not in then_defs:
|
|
then_defs[name] = liveins[name]
|
|
# variables that are both in then and else but not in liveins
|
|
# TODO: could probably be cleaned up
|
|
for name in then_defs.keys() & else_defs.keys():
|
|
if name in names:
|
|
continue
|
|
then_ty = then_defs[name].type
|
|
else_ty = else_defs[name].type
|
|
assert then_ty == else_ty, \
|
|
f'mismatched type for {name} between then block ({then_ty}) '\
|
|
f'and else block ({else_ty})'
|
|
names.append(name)
|
|
ret_types.append(then_ty)
|
|
ir_ret_types.append(then_defs[name].handle.get_type())
|
|
|
|
return then_defs, else_defs, then_block, else_block, names, ret_types, ir_ret_types
|
|
|
|
def visit_if_top_level(self, cond, node):
|
|
has_endif_block = True
|
|
with enter_sub_region(self) as sr:
|
|
liveins, ip_block = sr
|
|
then_block = self.builder.create_block()
|
|
else_block = self.builder.create_block()
|
|
# create basic-block after conditional
|
|
endif_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, ret_types, ir_ret_types = \
|
|
self.visit_then_else_blocks(node, liveins, then_block, else_block)
|
|
# then terminator
|
|
self.builder.set_insertion_point_to_end(then_block)
|
|
if then_block.has_return() and else_block.has_return():
|
|
has_endif_block = False
|
|
endif_block.erase()
|
|
if not then_block.has_terminator() and has_endif_block:
|
|
self.builder.create_branch(endif_block, [then_defs[n].handle for n in names])
|
|
# else terminator
|
|
self.builder.set_insertion_point_to_end(else_block)
|
|
if not else_block.has_terminator() and has_endif_block:
|
|
self.builder.create_branch(endif_block, [else_defs[n].handle for n in names])
|
|
if has_endif_block:
|
|
for ty in ir_ret_types:
|
|
endif_block.add_argument(ty)
|
|
if has_endif_block:
|
|
# change block
|
|
self.builder.set_insertion_point_to_start(endif_block)
|
|
# update value
|
|
for i, name in enumerate(names):
|
|
new_tensor = language.core.tensor(endif_block.arg(i), ret_types[i])
|
|
self.set_value(name, new_tensor)
|
|
|
|
# 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, ret_types, _ = \
|
|
self.visit_then_else_blocks(node, liveins, then_block, else_block)
|
|
# create if op
|
|
self._set_insertion_point_and_loc(ip, last_loc)
|
|
if_op = self.builder.create_if_op([ty.to_ir(self.builder) for ty in ret_types], 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_defs[n].handle for n in names])
|
|
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:
|
|
self.builder.create_yield_op([else_defs[n].handle for n in names])
|
|
# update values
|
|
for i, name in enumerate(names):
|
|
new_tensor = language.core.tensor(if_op.get_result(i), ret_types[i])
|
|
self.set_value(name, new_tensor)
|
|
|
|
def visit_If(self, node):
|
|
cond = self.visit(node.test)
|
|
if _is_triton_tensor(cond):
|
|
cond = cond.to(language.int1, _builder=self.builder)
|
|
contains_return = ContainsReturnChecker(self.gscope).visit(node)
|
|
if self.scf_stack and contains_return:
|
|
raise self._unsupported(
|
|
node, "Cannot have `return` statements inside `while` or `for` statements in triton "
|
|
"(note that this also applies to `return` statements that are inside functions "
|
|
"transitively called from within `while`/`for` statements)")
|
|
elif self.scf_stack or not contains_return:
|
|
self.visit_if_scf(cond, node)
|
|
else:
|
|
self.visit_if_top_level(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__))
|
|
if cond:
|
|
self.visit_compound_statement(node.body)
|
|
else:
|
|
self.visit_compound_statement(node.orelse)
|
|
|
|
def visit_IfExp(self, node):
|
|
cond = self.visit(node.test)
|
|
if _is_triton_tensor(cond):
|
|
cond = cond.to(language.int1, _builder=self.builder)
|
|
# 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 = language.core._to_tensor(self.visit(node.body), self.builder)
|
|
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 = language.core._to_tensor(self.visit(node.orelse), self.builder)
|
|
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_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]) == ast.Is:
|
|
return constexpr(lhs_value is rhs_value)
|
|
if type(node.ops[0]) == 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)(_builder=self.builder)
|
|
try:
|
|
return getattr(operand, fn)()
|
|
except AttributeError:
|
|
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 visit_While(self, node):
|
|
with enter_sub_region(self) as sr:
|
|
liveins, insert_block = sr
|
|
ip, last_loc = self._get_insertion_point_and_loc()
|
|
|
|
# loop body (the after region)
|
|
# loop_block = self.builder.create_block()
|
|
dummy = self.builder.create_block()
|
|
self.builder.set_insertion_point_to_start(dummy)
|
|
self.scf_stack.append(node)
|
|
self.visit_compound_statement(node.body)
|
|
self.scf_stack.pop()
|
|
loop_defs = self.local_defs
|
|
dummy.erase()
|
|
|
|
# collect loop-carried values
|
|
names = []
|
|
ret_types = []
|
|
init_args = []
|
|
for name in loop_defs:
|
|
if name in liveins:
|
|
# We should not def new constexpr
|
|
assert _is_triton_tensor(loop_defs[name]), f'cannot reassign constxpr {name} in the loop'
|
|
assert _is_triton_tensor(liveins[name]), f'cannot reasign constexpr {name} in the loop'
|
|
assert loop_defs[name].type == liveins[name].type, \
|
|
f'Loop-carried variable {name} has initial type {liveins[name].type} '\
|
|
f'but is re-assigned to {loop_defs[name].type} in loop! '\
|
|
f'Please make sure that the type stays consistent.'
|
|
|
|
# these are loop-carried values
|
|
names.append(name)
|
|
ret_types.append(loop_defs[name].type)
|
|
init_args.append(liveins[name])
|
|
|
|
self._set_insertion_point_and_loc(ip, last_loc)
|
|
while_op = self.builder.create_while_op([ty.to_ir(self.builder) for ty in ret_types],
|
|
[arg.handle for arg in init_args])
|
|
# merge the condition region
|
|
before_block = self.builder.create_block_with_parent(while_op.get_before(),
|
|
[ty.to_ir(self.builder) for ty in ret_types])
|
|
self.builder.set_insertion_point_to_start(before_block)
|
|
for i, name in enumerate(names):
|
|
self.lscope[name] = language.core.tensor(before_block.arg(i), ret_types[i])
|
|
self.local_defs[name] = self.lscope[name]
|
|
cond = self.visit(node.test)
|
|
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, [before_block.arg(i) for i in range(len(init_args))])
|
|
# merge the loop body
|
|
after_block = self.builder.create_block_with_parent(while_op.get_after(),
|
|
[ty.to_ir(self.builder) for ty in ret_types])
|
|
|
|
# generate loop body
|
|
self.builder.set_insertion_point_to_start(after_block)
|
|
for i, name in enumerate(names):
|
|
self.lscope[name] = language.core.tensor(after_block.arg(i), ret_types[i])
|
|
self.local_defs[name] = self.lscope[name]
|
|
self.scf_stack.append(node)
|
|
self.visit_compound_statement(node.body)
|
|
self.scf_stack.pop()
|
|
loop_defs = self.local_defs
|
|
yields = []
|
|
for name in loop_defs:
|
|
if name in liveins:
|
|
yields.append(loop_defs[name])
|
|
self.builder.create_yield_op([y.handle for y in yields])
|
|
|
|
# WhileOp defines new values, update the symbol table (lscope, local_defs)
|
|
for i, name in enumerate(names):
|
|
new_def = language.core.tensor(while_op.get_result(i), ret_types[i])
|
|
self.lscope[name] = new_def
|
|
self.local_defs[name] = new_def
|
|
|
|
for stmt in node.orelse:
|
|
assert False, "Not implemented"
|
|
ast.NodeVisitor.generic_visit(self, stmt)
|
|
|
|
def visit_Subscript(self, node):
|
|
assert node.ctx.__class__.__name__ == "Load"
|
|
lhs = self.visit(node.value)
|
|
slices = self.visit(node.slice)
|
|
if _is_triton_tensor(lhs):
|
|
return lhs.__getitem__(slices, _builder=self.builder)
|
|
return lhs[slices]
|
|
|
|
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
|
|
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
|
|
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 = language.core._to_tensor(lb, self.builder)
|
|
ub = language.core._to_tensor(ub, self.builder)
|
|
step = language.core._to_tensor(step, self.builder)
|
|
# 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 = language.semantic.integer_promote_impl(lb.dtype, ub.dtype)
|
|
iv_type = language.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_undef(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()
|
|
|
|
# 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) is defined in both its parent & itself, then it's
|
|
# a loop-carried variable. (They must be of the same type)
|
|
init_args = []
|
|
yields = []
|
|
names = []
|
|
for name in self.local_defs:
|
|
if name in liveins:
|
|
assert _is_triton_tensor(self.local_defs[name]), f'{name} is not tensor'
|
|
assert _is_triton_tensor(liveins[name])
|
|
assert self.local_defs[name].type == liveins[name].type, \
|
|
f'Loop-carried variable {name} has initial type {liveins[name].type} '\
|
|
f'but is re-assigned to {self.local_defs[name].type} in loop! '\
|
|
f'Please make sure that the type stays consistent.'
|
|
|
|
names.append(name)
|
|
init_args.append(language.core._to_tensor(liveins[name], self.builder))
|
|
yields.append(language.core._to_tensor(self.local_defs[name], self.builder))
|
|
|
|
# create ForOp
|
|
self._set_insertion_point_and_loc(ip, last_loc)
|
|
for_op = self.builder.create_for_op(lb, ub, step, [arg.handle for arg in init_args])
|
|
if num_stages is not None:
|
|
for_op.set_attr("tt.num_stages", self.builder.get_int32_attr(num_stages))
|
|
|
|
self.scf_stack.append(node)
|
|
self.builder.set_insertion_point_to_start(for_op.get_body(0))
|
|
# reset local scope to not pick up local defs from the previous dry run.
|
|
self.lscope = liveins.copy()
|
|
self.local_defs = {}
|
|
for i, name in enumerate(names):
|
|
self.set_value(name, language.core.tensor(for_op.get_body(0).arg(i + 1), yields[i].type))
|
|
self.visit_compound_statement(node.body)
|
|
self.scf_stack.pop()
|
|
yields = []
|
|
for name in self.local_defs:
|
|
if name in liveins:
|
|
yields.append(language.core._to_tensor(self.local_defs[name], self.builder))
|
|
|
|
# create YieldOp
|
|
if len(yields) > 0:
|
|
self.builder.create_yield_op([y.handle for y in yields])
|
|
for_op_region = for_op.get_body(0).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.get_body(0))
|
|
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))
|
|
|
|
# update lscope & local_defs (ForOp defines new values)
|
|
for i, name in enumerate(names):
|
|
self.set_value(name, language.core.tensor(for_op.get_result(i), yields[i].type))
|
|
|
|
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 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:
|
|
if not self.debug:
|
|
return
|
|
test = self.visit(node.test)
|
|
msg = self.visit(node.msg) if node.msg is not None else ""
|
|
# Convert assert to triton's device_assert which happens on the device
|
|
return language.core.device_assert(test, msg, _builder=self.builder)
|
|
|
|
def call_JitFunction(self, fn: JITFunction, args, kwargs):
|
|
args = inspect.getcallargs(fn.fn, *args, **kwargs)
|
|
args = [args[name] for name in fn.arg_names]
|
|
args = [arg if _is_triton_tensor(arg) else constexpr(arg) for arg in args]
|
|
# generate function def
|
|
attributes = dict()
|
|
constexprs = [i for i, arg in enumerate(args) if _is_constexpr(arg)]
|
|
constants = {i: args[i] for i in constexprs}
|
|
# generate call
|
|
args = [None if i in constexprs else arg for i, arg in enumerate(args)]
|
|
arg_vals = [arg.handle for arg in args if arg is not None]
|
|
arg_types = [arg.type for arg in args if arg is not None]
|
|
fn_name = mangle_fn(fn.__name__, arg_types, constants)
|
|
# generate function def if necessary
|
|
if not self.module.has_function(fn_name):
|
|
prototype = language.function_type([], arg_types)
|
|
gscope = fn.__globals__
|
|
# If the callee is not set, we use the same debug setting as the caller
|
|
file_name, begin_line = _get_fn_file_line(fn)
|
|
debug = self.debug if fn.debug is None else fn.debug
|
|
generator = CodeGenerator(self.context, prototype, gscope, attributes, constants, 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, debug=debug)
|
|
try:
|
|
generator.visit(fn.parse())
|
|
except Exception as e:
|
|
# Wrap the error in the callee with the location of the call.
|
|
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)
|
|
call_op = self.builder.call(symbol, arg_vals)
|
|
if call_op.get_num_results() == 0 or callee_ret_type is None:
|
|
return None
|
|
elif call_op.get_num_results() == 1:
|
|
return tensor(call_op.get_result(0), callee_ret_type)
|
|
else:
|
|
# should return a tuple of tl.tensor
|
|
results = []
|
|
for i in range(call_op.get_num_results()):
|
|
results.append(tensor(call_op.get_result(i), callee_ret_type[i]))
|
|
return tuple(results)
|
|
|
|
def visit_Call(self, node):
|
|
fn = _unwrap_if_constexpr(self.visit(node.func))
|
|
static_implementation = self.statically_implemented_functions.get(fn)
|
|
if static_implementation is not None:
|
|
return static_implementation(self, node)
|
|
|
|
kws = dict(self.visit(keyword) for keyword in node.keywords)
|
|
args = [self.visit(arg) for arg in node.args]
|
|
if fn is language.core.device_assert: # TODO: this should not be so hardcoded
|
|
if not self.debug:
|
|
return
|
|
if isinstance(fn, JITFunction):
|
|
_check_fn_args(node, fn, args)
|
|
return self.call_JitFunction(fn, args, kws)
|
|
if (hasattr(fn, '__self__') and _is_triton_tensor(fn.__self__)) or language.core.is_builtin(fn):
|
|
extra_kwargs = dict(_builder=self.builder)
|
|
sig = inspect.signature(fn)
|
|
if '_generator' in sig.parameters:
|
|
extra_kwargs['_generator'] = self
|
|
try:
|
|
return fn(*args, **extra_kwargs, **kws)
|
|
except Exception as e:
|
|
# 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, None) from e
|
|
|
|
if fn in self.builtin_namespace.values():
|
|
args = map(_unwrap_if_constexpr, args)
|
|
return fn(*args, **kws)
|
|
|
|
def visit_Constant(self, node):
|
|
return constexpr(node.value)
|
|
|
|
def visit_BoolOp(self, node: ast.BoolOp):
|
|
if len(node.values) != 2:
|
|
raise self._unsupported(
|
|
node, "chained boolean operators (A or B or C) are not supported; use parentheses to split the chain.")
|
|
lhs = self.visit(node.values[0])
|
|
rhs = self.visit(node.values[1])
|
|
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__))
|
|
return self._apply_binary_method(method_name, lhs, rhs)
|
|
|
|
_method_name_for_bool_op: Dict[Type[ast.boolop], str] = {ast.And: 'logical_and', ast.Or: 'logical_or'}
|
|
|
|
if sys.version_info < (3, 8):
|
|
|
|
def visit_NameConstant(self, node):
|
|
return constexpr(node.value)
|
|
|
|
def visit_Num(self, node):
|
|
return constexpr(node.n)
|
|
|
|
def visit_Str(self, node):
|
|
return constexpr(ast.literal_eval(node))
|
|
|
|
def visit_Attribute(self, node):
|
|
lhs = self.visit(node.value)
|
|
if _is_triton_tensor(lhs):
|
|
if node.attr == "T":
|
|
return language.semantic.permute(lhs, (1, 0), builder=self.builder)
|
|
return getattr(lhs, node.attr)
|
|
|
|
def visit_Expr(self, node):
|
|
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'):
|
|
self.builder.set_loc(self.file_name, self.begin_line + node.lineno, node.col_offset)
|
|
last_loc = self.builder.get_loc()
|
|
try:
|
|
ret = super().visit(node)
|
|
except CompilationError:
|
|
raise
|
|
except Exception as e:
|
|
# 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
|
|
|
|
statically_implemented_functions: Dict[object, Callable[[ast.Call], Any]] = {
|
|
language.core.static_assert: execute_static_assert,
|
|
language.core.static_print: static_executor(print),
|
|
int: static_executor(int),
|
|
len: static_executor(len),
|
|
}
|
|
|
|
|
|
def kernel_suffix(signature, specialization):
|
|
# suffix format:
|
|
# <argid><'c' if equal to 1><'d' if divisible by 16><'e' if divisible by 8>
|
|
suffix = ''
|
|
for i, _ in enumerate(signature):
|
|
suffix += str(i)
|
|
if i in specialization.equal_to_1:
|
|
suffix += 'c'
|
|
if i in specialization.divisible_by_16:
|
|
suffix += 'd'
|
|
return suffix
|
|
|
|
|
|
def ast_to_ttir(fn, specialization, context, options, codegen_fns):
|
|
attrs = specialization.attrs
|
|
# create kernel prototype
|
|
cst_key = lambda i: fn.arg_names.index(i) if isinstance(i, str) else i
|
|
constants = {cst_key(key): value for key, value in specialization.constants.items()}
|
|
# visit kernel AST
|
|
gscope = fn.__globals__.copy()
|
|
function_name = fn.repr(specialization)
|
|
tys = list(specialization.signature.values())
|
|
new_constants = {k: True if k in tys and tys[k] == "i1" else 1 for k in attrs.equal_to_1}
|
|
new_attrs = {k: [("tt.divisibility", 16)] for k in attrs.divisible_by_16}
|
|
|
|
all_constants = constants.copy()
|
|
all_constants.update(new_constants)
|
|
arg_types = [str_to_ty(v) for k, v in specialization.signature.items() if k not in specialization.constants]
|
|
file_name, begin_line = _get_fn_file_line(fn)
|
|
|
|
prototype = language.function_type([], arg_types)
|
|
generator = CodeGenerator(context, prototype, gscope=gscope, constants=all_constants, function_name=function_name,
|
|
jit_fn=fn, attributes=new_attrs, is_kernel=True, file_name=file_name,
|
|
begin_line=begin_line, options=options, codegen_fns=codegen_fns)
|
|
generator.visit(fn.parse())
|
|
|
|
ret = generator.module
|
|
# module takes ownership of the context
|
|
ret.context = context
|
|
return ret
|