| import collections |
| import dataclasses |
| import itertools |
| import logging |
| import re |
| import typing |
| from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union |
| |
| import sympy |
| |
| import torch |
| |
| from .codegen.common import index_prevent_reordering |
| from .utils import get_dtype_size, sympy_str, sympy_subs, sympy_symbol, VarRanges |
| from .virtualized import V |
| |
| log = logging.getLogger(__name__) |
| is_indirect = re.compile(r"indirect|tmp").search |
| Dep = Union["MemoryDep", "StarDep", "WeakDep"] |
| |
| |
| class MemoryDep(typing.NamedTuple): |
| name: str |
| index: sympy.Expr # type: ignore[assignment] |
| var_names: Tuple[sympy.Symbol, ...] |
| size: Tuple[sympy.Expr, ...] |
| |
| def __repr__(self): |
| return f"MemoryDep({self.name!r}, {self.index}, {self.ranges})" |
| |
| @property |
| def ranges(self) -> Dict[sympy.Symbol, sympy.Expr]: |
| """{c0: 128, c1: 512, ...}""" |
| return dict(zip(self.var_names, self.size)) |
| |
| def rename(self, renames: Dict[str, str]) -> "MemoryDep": |
| if self.name in renames: |
| return MemoryDep( |
| renames[self.name], self.index, var_names=self.var_names, size=self.size |
| ) |
| return self |
| |
| def numbytes_hint(self): |
| if self.is_indirect(): |
| numel = V.graph.get_numel(self.name) |
| else: |
| vars = set(self.index.free_symbols) |
| numel = sympy.Integer(1) |
| for var, size in zip(self.var_names, self.size): |
| if var in vars: |
| numel = numel * size |
| return V.graph.sizevars.size_hint(numel) * get_dtype_size( |
| V.graph.get_dtype(self.name) |
| ) |
| |
| def is_contiguous(self) -> bool: |
| return isinstance(self.index, sympy.Symbol) and self.index in self.var_names |
| |
| def is_scalar(self) -> bool: |
| if isinstance(self.index, sympy.Symbol): |
| return self.index not in self.var_names and not self.is_indirect() |
| return isinstance(self.index, (int, sympy.Integer)) |
| |
| def is_indirect(self) -> bool: |
| return any(is_indirect(v.name) for v in self.index.free_symbols) |
| |
| |
| class StarDep(typing.NamedTuple): |
| # depends on the entire buffer |
| name: str |
| |
| @property |
| def index(self): |
| raise NotImplementedError("StarDep does not have an index") |
| |
| def rename(self, renames: Dict[str, str]) -> "StarDep": |
| if self.name in renames: |
| return StarDep(renames[self.name]) |
| return self |
| |
| def numbytes_hint(self): |
| return V.graph.sizevars.size_hint( |
| V.graph.get_numel(self.name) |
| ) * get_dtype_size(V.graph.get_dtype(self.name)) |
| |
| def is_contiguous(self) -> bool: |
| return False |
| |
| def is_scalar(self) -> bool: |
| return False |
| |
| def is_indirect(self) -> bool: |
| return False |
| |
| |
| # Used for tracking mutation ordering |
| # if A reads a buffer and B mutates it |
| # B must be ordered after A |
| # |
| # It is weak because if it turns out A's read is never used, we can still |
| # eliminate it |
| class WeakDep(typing.NamedTuple): |
| name: str |
| |
| @property |
| def index(self): |
| raise NotImplementedError("WeakDep does not have an index") |
| |
| def rename(self, renames: Dict[str, str]) -> "WeakDep": |
| if self.name in renames: |
| return WeakDep(renames[self.name]) |
| return self |
| |
| def numbytes_hint(self): |
| return 1 # Purely inserted for ordering, not an actual dep |
| |
| def is_contiguous(self) -> bool: |
| return False |
| |
| |
| class IndexExprDep(typing.NamedTuple): |
| index: sympy.Expr # type: ignore[assignment] |
| var_names: Tuple[sympy.Symbol, ...] |
| size: Tuple[sympy.Expr, ...] |
| |
| |
| @dataclasses.dataclass |
| class ReadWrites: |
| reads: Set[Dep] |
| writes: Set[Dep] |
| index_exprs: Set[IndexExprDep] |
| range_vars: Optional[List[sympy.Expr]] = None |
| var_ranges: Optional[VarRanges] = None |
| op_counts: typing.Counter[Any] = None # type: ignore[assignment] |
| |
| def rename(self, renames: typing.Dict[str, str]) -> "ReadWrites": |
| return ReadWrites( |
| {dep.rename(renames) for dep in self.reads}, |
| {dep.rename(renames) for dep in self.writes}, |
| self.index_exprs, |
| self.range_vars, |
| self.var_ranges, |
| op_counts=self.op_counts, |
| ) |
| |
| def with_read(self, dep: Dep) -> "ReadWrites": |
| assert isinstance(dep, (WeakDep, StarDep)) |
| return ReadWrites( |
| set.union(self.reads, {dep}), |
| self.writes, |
| self.index_exprs, |
| self.range_vars, |
| self.var_ranges, |
| op_counts=self.op_counts, |
| ) |
| |
| def merge(self, other: "ReadWrites"): |
| reads = set.union(self.reads, other.reads) |
| writes = set.union(self.writes, other.writes) |
| index_exprs = set.union(self.index_exprs, other.index_exprs) |
| if self.op_counts is not None: |
| op_counts = collections.Counter(self.op_counts) |
| op_counts.update(other.op_counts or {}) |
| else: |
| op_counts = other.op_counts |
| return ReadWrites(reads - writes, writes, index_exprs, op_counts=op_counts) |
| |
| @staticmethod |
| def merge_list(read_writes: List["ReadWrites"]): |
| all_writes = set.union(*[rw.writes for rw in read_writes]) |
| all_reads = set.union(*[rw.reads for rw in read_writes]) - all_writes |
| all_index_exprs = set.union(*[rw.index_exprs for rw in read_writes]) |
| |
| op_counts: typing.Counter[Any] = collections.Counter() |
| for rw in read_writes: |
| if rw.op_counts is not None: |
| op_counts.update(rw.op_counts) |
| |
| return ReadWrites(all_reads, all_writes, all_index_exprs, op_counts=op_counts) |
| |
| def remove_reads(self, rem_reads): |
| return ReadWrites( |
| self.reads - rem_reads, |
| self.writes, |
| self.index_exprs, |
| self.range_vars, |
| self.var_ranges, |
| op_counts=self.op_counts, |
| ) |
| |
| def reads_and_writes(self): |
| return itertools.chain(self.reads, self.writes) |
| |
| |
| class _RecordLoadStoreInner(V.MockHandler): # type: ignore[name-defined] |
| def __init__(self, var_ranges: VarRanges, normalize: bool): |
| super().__init__() |
| self._reads: Set[MemoryDep] = set() |
| self._writes: Set[MemoryDep] = set() |
| self._index_exprs: Set[IndexExprDep] = set() |
| self._var_ranges: VarRanges = var_ranges |
| self._normalize: bool = normalize |
| |
| def canonicalize( |
| self, index: sympy.Expr |
| ) -> Tuple[sympy.Expr, Tuple[sympy.Expr, ...]]: |
| if not self._normalize: |
| sizes = [V.graph.sizevars.simplify(x) for x in self._var_ranges.values()] |
| var_names = tuple( |
| k for k, v in zip(self._var_ranges.keys(), sizes) if v != 1 |
| ) |
| sizes = tuple(v for v in sizes if v != 1) |
| return index, var_names, sizes # type: ignore[return-value] |
| |
| # Try to further simplify the indexes even if simplify_loops didn't |
| # convert it to the simplest form because of the interference from |
| # different indexing formulas. |
| free_symbols = index.free_symbols |
| var_ranges = { |
| k: V.graph.sizevars.simplify(v) |
| for k, v in self._var_ranges.items() |
| # TODO(jansel): explore this further normalization |
| # if k in free_symbols |
| } |
| index_vars = [*var_ranges.keys()] |
| sizes = [*var_ranges.values()] # type: ignore[assignment] |
| new_sizes, reindex, prune = V.graph.sizevars._simplify_loops( |
| index_vars, |
| sizes, |
| index_prevent_reordering([index], index_vars, sizes), |
| ) |
| |
| # assign new variables each dimension to deal with numbering mismatches |
| # d0, d1, d2 could become d0, d2 -- which won't match d0, d1 |
| new_vars, add_var = var_builder(canonicalization_prefix()) |
| replacement = dict(zip(index_vars, reindex([add_var(x) for x in new_sizes]))) |
| index = sympy_subs(sympy.expand(index), replacement) |
| |
| new_vars = [*new_vars.keys()] |
| new_sizes = [*new_sizes] |
| free_symbols = index.free_symbols |
| while new_vars and new_vars[-1] not in free_symbols: |
| # Reduction has last (reduced) dim in its sizes, but |
| # downstream users won't. Normalize this away. |
| new_vars.pop() |
| new_sizes.pop() |
| return index, tuple(new_vars), tuple(new_sizes) # type: ignore[return-value] |
| |
| def load(self, name: str, index: sympy.Expr) -> str: |
| self._reads.add(MemoryDep(name, *self.canonicalize(index))) # type: ignore[call-arg] |
| return f"load({name}, {sympy_str(index)})" |
| |
| def load_seed(self, name: str, index: int): |
| assert isinstance(index, int) |
| return self.load(name, sympy.Integer(index)) |
| |
| def store(self, name: str, index: sympy.Expr, value: str, mode=None) -> str: |
| self._writes.add(MemoryDep(name, *self.canonicalize(index))) # type: ignore[call-arg] |
| return f"store({name}, {sympy_str(index)}, {value}, {mode})" |
| |
| def store_reduction(self, name: str, index, value) -> str: |
| return self.store(name, index, f"store_reduction({value})") |
| |
| def index_expr(self, index: sympy.Expr, dtype) -> str: |
| self._index_exprs.add(IndexExprDep(*self.canonicalize(index))) # type: ignore[call-arg] |
| return f"index_expr({sympy_str(index)}, {dtype})" |
| |
| def bucketize( |
| self, |
| values, |
| offsets_name: str, |
| offsets_size: sympy.Expr, |
| indexing_dtype: torch.dtype, |
| right: bool, |
| ): |
| self._reads.add(StarDep(offsets_name)) # type: ignore[arg-type] |
| return f"bucketize({values}, {offsets_name}, {sympy_str(offsets_size)}, {indexing_dtype}, {right})" |
| |
| |
| class _OpCounter: |
| """Shim to count how many times each op is used""" |
| |
| def __init__(self, inner): |
| super().__init__() |
| self.parent_handler = inner |
| self._op_counts: typing.Counter[Any] = collections.Counter() |
| |
| def __getattr__(self, name): |
| self._op_counts[name] += 1 |
| return getattr(self.parent_handler, name) |
| |
| |
| class RecordLoadStore(V.KernelFormatterHandler): # type: ignore[name-defined] |
| def __init__(self, var_ranges: VarRanges, normalize: bool): |
| parent_handler = _RecordLoadStoreInner( |
| var_ranges=var_ranges, normalize=normalize |
| ) |
| parent_handler = _OpCounter(parent_handler) |
| super().__init__(parent_handler=parent_handler) |
| |
| |
| def var_builder(prefix: str) -> Tuple[VarRanges, Callable[[sympy.Expr], sympy.Symbol]]: |
| cnt = itertools.count() |
| var_ranges: VarRanges = dict() |
| |
| def add_var(length: sympy.Expr) -> sympy.Symbol: |
| v = sympy_symbol(f"{prefix}{next(cnt)}") |
| var_ranges[v] = length |
| return v |
| |
| return var_ranges, add_var |
| |
| |
| def index_vars_no_squeeze(*argsizes: Tuple[sympy.Expr, ...], prefix: str): |
| var_ranges, add_var = var_builder(prefix) |
| args: List[List[sympy.Symbol]] = [] |
| for size in argsizes: |
| args.append(list(map(add_var, size))) |
| return args, var_ranges |
| |
| |
| def index_vars_squeeze(*argsizes: Tuple[sympy.Expr, ...], prefix: str = "d"): |
| from .ir import SqueezeView |
| |
| var_ranges, add_var = var_builder(prefix) |
| args: List[List[sympy.Expr]] = [] |
| new_sizes: List[List[sympy.Expr]] = [] |
| for size in argsizes: |
| new_size, reindex = SqueezeView.squeezer(size) |
| new_sizes.append(new_size) |
| args.append(reindex(list(map(add_var, new_size)))) |
| return args, var_ranges |
| |
| |
| def extract_read_writes( |
| fn: Callable[[sympy.Expr], Any], |
| *argsizes: Tuple[sympy.Expr, ...], |
| normalize: bool = False, |
| prefix: str = "d", |
| ): |
| args, var_ranges = index_vars_squeeze(*argsizes, prefix=prefix) |
| rw = RecordLoadStore(var_ranges, normalize=normalize) |
| with V.set_ops_handler(rw): # type: ignore[call-arg] |
| fn(*args) |
| |
| if normalize: |
| range_vars = [] # Number of vars could differ due to normalization |
| else: |
| range_vars = [*itertools.chain(*args)] |
| |
| inner = rw.parent_handler.parent_handler |
| return ReadWrites( |
| set(inner._reads), |
| set(inner._writes), |
| inner._index_exprs, |
| range_vars, |
| var_ranges, |
| rw.parent_handler._op_counts, |
| ) |
| |
| |
| def canonicalization_prefix(): |
| return "c" |
