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onepilot/tinygrad_repo/tinygrad/schedule/rangeify.py
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firestar5683 d0e1db6766 StarPilot
2026-03-22 03:15:05 -05:00

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Python

from dataclasses import dataclass, field, replace
import itertools
from tinygrad.dtype import dtypes, PtrDType, ImageDType, AddrSpace
from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, _substitute, KernelInfo, pm_gate_kernel_sink
from tinygrad.uop.ops import graph_rewrite, identity_element, sint, AxisType, BottomUpGate, _remove_all_tags, range_str
from tinygrad.uop.symbolic import symbolic
from tinygrad.helpers import argsort, prod, all_same, getenv, flatten, dedup, all_int, DEBUG, SPLIT_REDUCEOP, DEBUG_RANGEIFY, VIZ
from tinygrad.helpers import PCONTIG, partition, get_single_element
from tinygrad.codegen.simplify import pm_flatten_range, pm_reduce_simplify
from tinygrad.codegen.opt import Opt
from tinygrad.schedule.indexing import run_rangeify, BufferizeOpts, ALWAYS_CONTIGUOUS, IndexingContext, apply_movement_op
# creation can recurse a lot
import sys
sys.setrecursionlimit(10000)
pm_syntactic_sugar = PatternMatcher([
# INDEX on ptr INDEX concats them
(UPat(Ops.INDEX, name="i1").f(Ops.INDEX, name="i2", allow_any_len=True),
lambda i1,i2: i2.replace(src=i1.src+i2.src[1:]) if isinstance(i1.dtype, PtrDType) and not isinstance(i2.dtype, PtrDType) else None),
])
# movement op on INDEX as a PatternMatcher
pm_mops = PatternMatcher([
(UPat(GroupOp.Movement, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"),
lambda r,idx: r.src[0].index(*apply_movement_op(r.op, r.src[0].shape, r.marg, idx.src[1:]), dtype=idx.dtype, arg=idx.arg)),
# move movement ops after AFTER
(UPat(GroupOp.Movement, name="r").after(name="a", allow_any_len=True),
lambda r,a: UOp(r.op, r.dtype, (a.replace(src=(r.src[0],)+a.src[1:], tag=None),)+r.src[1:], r.arg, tag=a.tag)),
(UPat(GroupOp.Movement, name="r").end(name="a", allow_any_len=True), lambda r,a: a.replace(src=(r.src[0],)+a.src[1:])),
])
# *****************
# 0. do some cleanup rewrites, mostly copied from the old stuff
def collapse_nested_assign(assign:UOp, target:UOp, src:UOp):
"""nested ASSIGN to the same buffer (e.g. __iadd__ in __setitem__): collapse the redundant outer ASSIGN"""
if src.src[0].base is target.base: return src if src.src[0] is target else assign.replace(src=(target, src.src[1]))
def assign_to_contiguous(assign:UOp, target:UOp, src:UOp):
if (t := target.base).op is Ops.PARAM or (t.op is Ops.MSTACK and all(s.op is Ops.PARAM for s in t.src)): return None
# partial view of unrealized graph: insert CONTIGUOUS at base to realize it
if target is not t and target.op_in_backward_slice_with_self(Ops.SHRINK):
# base already realized: copy src only if it reads from the same buffer (overlapping read/write hazard)
if t.op is Ops.CONTIGUOUS: return assign.replace(src=(target, src.contiguous())) if t in src.toposort() else None
if t.op is Ops.CONST: raise RuntimeError("setitem target must be a writable view backed by a buffer")
mops: list[UOp] = []
while target.op in GroupOp.Movement:
mops.append(target)
target = target.src[0]
new_target = t.f(Ops.CONTIGUOUS, tag=t.tag)
for m in reversed(mops): new_target = m.replace(src=(new_target,)+m.src[1:])
return assign.replace(src=(new_target, src))
return src.f(Ops.CONTIGUOUS, tag=assign.tag)
def fix_assign_hazard(assign:UOp, target:UOp, src:UOp):
# PERMUTE and FLIP reorder indices, SHRINK can have overlapping regions when dest is also shrunk
unsafe = {Ops.PERMUTE, Ops.FLIP} | ({Ops.SHRINK} if target.op_in_backward_slice_with_self(Ops.SHRINK) else set())
if not (hazards:=[s for s in src.toposort(gate=lambda s:s.op not in ALWAYS_CONTIGUOUS) if s.op in unsafe]): return
for h in hazards:
if any(s is target.base for s in h.toposort(gate=lambda s:s.op not in ALWAYS_CONTIGUOUS-{Ops.PARAM})):
return assign.replace(src=(target, src.contiguous()))
def split_reduceop(reduce:UOp, x:UOp):
if prod(reduce.shape) == 0: return None
if not SPLIT_REDUCEOP or not all_int(x.shape) or (prod(x.shape)//prod(reduce.shape))<getenv("REDUCEOP_SPLIT_THRESHOLD", 32768): return None
# if there are few globals, make some reduces into globals by splitting into two kernels
# cap output buffer to 2**22: heuristic number of global outputs to achieve max occupancy with enough locals+upcasts for gemm
# ~2**10 should be enough if GROUP is used
# 256 split maximum should be "negligible reduce" for low prod(reduce.shape), 8 split minimum.
# split is moved to the end to provide maximum locality for the second phase reduce.
# get expanded by rangeifying the UOp x
indexed = x.index(*[UOp.range(s, i) if resolve(s>1) else UOp.const(dtypes.index, 0) for i,s in enumerate(x.shape)])
range_nums = [y.arg[0] for y in indexed.substitute({x.base:UOp(Ops.NOOP)}, extra_pm=pm_mops).ranges]
is_expanded = [i not in range_nums for i in range(len(x.shape))]
if not (split_candidates:=[(i,d) for i in reduce.arg[1] for d in range(min(256,2**getenv("REDUCEOP_SPLIT_SIZE",22)//prod(reduce.shape)),8-1,-1)
if x.shape[i]%d==0 and not is_expanded[i]]): return None
dim_to_split, divisor = split_candidates[0]
splitted_shape = x.shape[:dim_to_split]+(divisor,)+(x.shape[dim_to_split]//divisor,)+x.shape[dim_to_split+1:]
splitted = x.reshape(splitted_shape).permute(tuple([d for d in range(len(splitted_shape)) if d!=dim_to_split]+[dim_to_split]))
if DEBUG >= 3: print(f"split {divisor}: {x.shape} -> {splitted.shape} -> {reduce.shape}")
# reduce original axes, then split
return splitted.r(*reduce.arg).contiguous().r(reduce.arg[0], (len(reduce.shape),)).reshape(reduce.shape).replace(tag=reduce.tag)
mop_cleanup = PatternMatcher([
# merge adjacent RESHAPES, safe because they are not tagged
(UPat(Ops.RESHAPE, src=(UPat(Ops.RESHAPE, name="x2"), UPat()), name="x"),
lambda x,x2: x.replace(src=(x2.src[0], x.src[1])) if x.tag is None and x2.tag is None else None),
])
def resolve_call(c:UOp) -> UOp|None:
# don't resolve real kernel calls, sink or program
if c.src[0].op is Ops.SINK and isinstance(c.src[0].arg, KernelInfo): return None
if c.src[0].op is Ops.PROGRAM: return None
params = sorted([x for x in c.src[0].toposort() if x.op == Ops.PARAM], key=lambda x: x.arg)
args = c.src[1:]
# TODO: this check belongs in spec, not here
if [x.arg for x in params] != list(range(len(params))): raise RuntimeError(f"params not in order: {[x.arg for x in params]}")
if len(params) != len(args): raise TypeError(f"expected {len(params)} args, got {len(args)}")
for i, (p, a) in enumerate(zip(params, args)):
if p.shape != a.shape: raise TypeError(f"arg {i} shape mismatch: expected {p.shape}, got {a.shape}")
if p.dtype != a.dtype: raise TypeError(f"arg {i} dtype mismatch: expected {p.dtype}, got {a.dtype}")
return c.src[0].substitute(dict(zip(params, args))).rtag(c.tag)
earliest_rewrites = mop_cleanup+PatternMatcher([
# just removing it works...
(UPat((Ops.DETACH, Ops.CONTIGUOUS_BACKWARD), name="x"), lambda x: x.src[0]),
# resolve calls
(UPat(Ops.CALL, name="c"), resolve_call),
# remove CONTIGUOUS if the source is already contiguous
(UPat(Ops.RESHAPE, src=(UPat((Ops.PARAM, Ops.CONTIGUOUS)), UPat()), name="r").f(Ops.CONTIGUOUS, name="c"), lambda r,c: r.replace(tag=c.tag)),
# split_reduceop
(UPat(Ops.REDUCE_AXIS, name="reduce", src=(UPat.var("x"),)), split_reduceop),
# preserve tags?
# reduce of size 0 is the identity element
(UPat(Ops.REDUCE_AXIS, name="reduce", src=(UPat.var("x"),)),
lambda reduce,x: reduce.const_like(identity_element(reduce.arg[0], reduce.dtype)) if x.size == 0 and reduce.size != 0 else None),
# handle size 0
(UPat(GroupOp.All-{Ops.SINK}, name="x"), lambda x: x.const_like(0).rtag(x.tag) if x._shape is not None and x.size == 0 else None),
# remove contiguous on movement ops before a copy on disk
(UPat(GroupOp.Movement-{Ops.SHRINK, Ops.RESHAPE}, name="x").f(Ops.CONTIGUOUS).f(Ops.COPY, allow_any_len=True, name="copy"),
lambda x,copy: copy.replace(src=(x,)+copy.src[1:]) if isinstance(x.device, str) and x.device.startswith("DISK") else None),
# push copy past movement ops to disk
(UPat(GroupOp.Movement-{Ops.SHRINK, Ops.RESHAPE}, name="x").f(Ops.COPY, allow_any_len=True, name="copy"),
lambda x,copy: x.replace(src=(copy.replace(src=(x.src[0],)+copy.src[1:], tag=None),)+x.src[1:], tag=copy.tag) \
if isinstance(x.device, str) and x.device.startswith("DISK") else None),
# ** copy rules **
# early fixup const copy
(UPat(Ops.COPY, src=(UPat.var("s"), UPat()), name="c"), lambda c,s: c.const_like(ss.arg) if (ss:=s.base).op is Ops.CONST else None),
# COPY and source size need to match
# TODO: expand after copy creates issues with tagging
(UPat(Ops.COPY, src=(UPat(GroupOp.Movement, name="r"), UPat(name="d")), name="c"),
lambda c,r,d: c.replace(src=(r.contiguous(), d)) if r.size != r.base.size else None),
# copy only to different device
(UPat(Ops.COPY, src=(UPat.var("x"), UPat()), name="copy"), lambda x,copy: x.f(Ops.NOOP, tag=copy.tag) if x.device == copy.device else None),
# ** assign rules **
# collapse nested ASSIGN to the same buffer (e.g. __iadd__ in __setitem__)
(UPat(Ops.ASSIGN, src=(UPat(name="target"), UPat(Ops.ASSIGN, name="src")), name="assign"), collapse_nested_assign),
# move bitcast from assign target to source: a.bitcast(X).assign(src) -> a.assign(src.bitcast(a.dtype))
(UPat(Ops.ASSIGN, src=(UPat(Ops.BITCAST, src=(UPat(name="target"),)), UPat(name="src")), name="assign"),
lambda assign, target, src: target.assign(src.bitcast(target.dtype)).replace(tag=assign.tag)),
# assign only to buffer, otherwise make it a CONTIGUOUS
(UPat(Ops.ASSIGN, src=(UPat(GroupOp.All-{Ops.PARAM}, name="target"), UPat(name="src")), name="assign"), assign_to_contiguous),
# make source contiguous if it has hazardous movement ops on the dest buffer
(UPat(Ops.ASSIGN, src=(UPat.var("target"), UPat.var("src")), name="assign"), fix_assign_hazard),
])
# *****************
# 3.5 cleanups
ALWAYS_RUN_OPS = {Ops.CONTIGUOUS, Ops.COPY, Ops.ASSIGN, Ops.ENCDEC}
# you don't know in the first pass if axes are going to die, this happens if there's an EXPAND to the left
def cleanup_dead_axes(b:UOp):
# don't optimize ALWAYS_RUN_OPS
if b.src[0].op in ALWAYS_RUN_OPS: return None
new_rng = []
hit = False
reshape: list[sint] = []
for s,rng in zip(b.shape, b.src[1:]):
# skip for symbolic. TODO: fix this
if rng.op is Ops.RANGE and rng.src[0].op is not Ops.CONST: return None
# CONSTs are already dead axes
if rng.op is Ops.CONST or (rng.op is Ops.RANGE and rng not in b.src[0].ranges):
reshape.append(1)
hit = True
else:
reshape.append(s)
new_rng.append(rng)
if hit:
# move the tag to the expand. NOTE: this expand tag might not survive
return b.replace(src=b.src[0:1]+tuple(new_rng), tag=None).reshape(tuple(reshape)).expand(b.shape).replace(tag=b.tag)
def gate_substitute(ctx, b:UOp) -> None:
if not any(r in b.ranges for r in ctx.keys()): raise BottomUpGate()
pm_gate_substitute = PatternMatcher([(UPat(GroupOp.All, name="b"), gate_substitute)], compiled=False)
# if a buffer is being stored just for permutes or something, remove it
# we want to reexpress the indexes of idx2 in terms of the implied b1
def remove_bufferize(src:UOp, buf:UOp, idx:UOp):
# see if we can't do it, should this ever hit?
assert len(buf.src) == len(idx.src), f"index on wrong bufferize, {len(buf.src)} != {len(idx.src)}"
assert all(x.op in {Ops.RANGE, Ops.CONST} for x in buf.src[1:])
# if it's user contiguous, we never remove it
if src.op in ALWAYS_RUN_OPS or not buf.arg.removable: return None
# we don't want to bufferize threefry, also causes problems because not all platforms support long
if src.op is not Ops.THREEFRY:
# *** here is where we compute the cost ***
# if we return None, the bufferize is kept
accessed_buffers: list[UOp] = []
indexes: list[UOp] = []
reduces: list[UOp] = []
def red_gate(x:UOp):
if (x.op is Ops.BUFFERIZE and x.arg.addrspace == AddrSpace.GLOBAL) or x.op is Ops.MSTACK:
accessed_buffers.append(x)
return False
if x.op is Ops.PARAM:
accessed_buffers.append(x)
if x.op is Ops.INDEX:
indexes.append(x)
if x.op is Ops.REDUCE: reduces.append(x)
return True
src.toposort(gate=red_gate)
del red_gate
accessed_buffers = dedup(accessed_buffers)
# if this is generated from multiple buffers, don't remove this buffer
if len(accessed_buffers) > 3 and not (PCONTIG > 2): return None
# if any reduces access a buffer, don't remove this buffer
buffer_in_reduce = False
def buf_gate(x:UOp):
nonlocal buffer_in_reduce
if x.op in {Ops.PARAM, Ops.BUFFERIZE}: buffer_in_reduce = True
return not buffer_in_reduce
UOp.sink(*[x.src[0] for x in reduces]).toposort(gate=buf_gate)
del buf_gate
if buffer_in_reduce:
if PCONTIG > 2:
out_in_ratio = (prod(buf.shape)+1) / (sum([x.size for x in accessed_buffers])+1)
if out_in_ratio < 10: return None
# here we have to check the indexes, we might do a partial contig here
local_indexes = [x for x in indexes if x.src[0].op is Ops.BUFFERIZE and x.src[0].arg.addrspace == AddrSpace.LOCAL]
exclude_ranges = UOp.group(*[UOp.group(*x.src[1:]) for x in local_indexes]).ranges
subs = [(k,v) for k,v in zip(buf.src[1:], idx.src[1:]) if k.op is not Ops.CONST]
# if it's bufferized or a reduce, it's pcontig
is_pcontig, is_subs = partition(subs, lambda x: x[0] in exclude_ranges or any([r.arg[-1] == AxisType.REDUCE for r in x[1].ranges]))
if not len(is_subs):
return None
if len(is_pcontig):
ret = src.substitute(dict(is_subs), extra_pm=pm_gate_substitute)
return ret.bufferize(*[x[0] for x in is_pcontig], arg=BufferizeOpts(None, AddrSpace.LOCAL)).index(*[x[1] for x in is_pcontig])
else:
return None
# if it makes it here, the bufferize is removed
# this is the ranges replaced
# NOTE: if buf src is a const, we don't replace it
return src.substitute({k:v for k,v in zip(buf.src[1:], idx.src[1:]) if k.op is not Ops.CONST}, extra_pm=pm_gate_substitute)
def remove_noop_bufferize(idx,b2):
if idx.src[1:] != b2.src[1:] or idx.src[0].op is Ops.BUFFER_VIEW: return None
new_tag = (idx.src[0].tag or ()) + (b2.tag or ()) or None
return idx.src[0].rtag(new_tag).shrink(tuple((0, s) for s in b2.shape)) if b2.shape else idx.src[0].rtag(new_tag)
pm_const_buffer_folding = pm_mops+PatternMatcher([
(UPat(Ops.BUFFERIZE, name="b"), cleanup_dead_axes),
(UPat(GroupOp.All-{Ops.BUFFERIZE, Ops.PARAM}, name="x"), lambda x: x.replace(dtype=x.dtype.base) if isinstance(x.dtype, ImageDType) else None),
(UPat((Ops.BUFFERIZE), name="x"), lambda x: x.replace(dtype=x.dtype.base) if isinstance(x.dtype, ImageDType)
and (resolve(prod(x.dtype.shape)!=prod(x.shape)) or x.shape[-1]%4!=0) else None),
# remove noop buffers. if we look at the next index we can remove even more of these
(UPat(Ops.INDEX, name="idx").f(Ops.BUFFERIZE, allow_any_len=True, name="b2"), remove_noop_bufferize),
# no buffers for const (ranges don't matter for const - it's the same value everywhere)
(UPat(Ops.CONST, name='c').f(Ops.BUFFERIZE, allow_any_len=True, name="b"), lambda c,b: b.const_like(c.arg).rtag(b.tag)),
# indexing a const is a const
(UPat(Ops.INDEX, src=(UPat(Ops.CONST, name="c"),),), lambda c: c),
# copy on CONST is CONST
(UPat(Ops.COPY, src=(UPat.cvar("x"), UPat()), name="copy"), lambda copy,x: copy.const_like(x.arg)),
# hack if a noop turned to a const
(UPat(Ops.NOOP, src=(UPat.cvar("c"),), name="noop"), lambda c,noop: c.rtag(noop.tag)),
# mstack on CONST is CONST
(UPat(Ops.MSTACK, src=(UPat.var("s"),), allow_any_len=True).f(Ops.INDEX, allow_any_len=True),
lambda s: UOp.const(c.dtype, c.arg) if (c:=s.base).op is Ops.CONST else None),
])
pm_remove_bufferize = PatternMatcher([
# remove reindexing with cost function
(UPat.var("src").f(Ops.BUFFERIZE, allow_any_len=True, name="buf").f(Ops.INDEX, allow_any_len=True, name="idx"), remove_bufferize),
])
def late_buffer_view(t:UOp, b:UOp):
if not (isinstance(b.device, str) and b.device.startswith(("DISK", "TINYFS"))): return b
shape = b.shape
size = prod(shape)
# walk up for the INDEX
x = t
while not any(u.op is Ops.INDEX for u in x.src):
assert x.op not in GroupOp.Elementwise, "can't buffer view elementwise"
x = x.src[0]
x = next(u for u in x.src if u.op is Ops.INDEX)
if len(shape) == 0: offset = x.src[1].arg
else: offset = max(sum(idx.vmin for idx in x.src[1:]), 0)
return b.replace(src=(UOp(Ops.BUFFER_VIEW, t.dtype, (x.base,), (size, offset), tag=t.tag), b.src[1]))
to_bufferview = PatternMatcher([
(UPat(Ops.BUFFERIZE, src=(UPat((Ops.BITCAST, Ops.CONTIGUOUS), name="t"), UPat()), name="b"), late_buffer_view),
])
DEVICE_MAX_BUFS = {"METAL": 31, "WEBGPU": 8} # TODO: get from device?
def limit_bufs(ctx:IndexingContext, root:UOp):
if (device:=root._device) is None: return None # no device, index related calculations
device = device if isinstance(device, str) else device[0].split(":")[0]
if not (MAX_BUFS:=getenv("MAX_KERNEL_BUFFERS", DEVICE_MAX_BUFS.get(device, 0))): return None
bufs: set[UOp] = set()
def gate_input(u:UOp):
# TODO: add cache to fix n^2
if is_load:=(u.op in {Ops.BUFFERIZE, Ops.AFTER, Ops.PARAM, Ops.MSELECT, Ops.MSTACK, Ops.DEFINE_VAR}): bufs.add(u)
return not is_load
root.toposort(gate=gate_input)
if len(bufs) > MAX_BUFS - 1: # NOTE: this -1 is for the output buffer
srcs = []
for s in root.src:
if s.op in GroupOp.Elementwise:
# Insert bufferize: all AxisType.REDUCE before bufferize are AxisType.LOOP
orig_ranges, end_ranges = s.ranges, [x.replace(arg=(next(ctx.range_idx), AxisType.LOOP)) if x.op is Ops.RANGE else x for x in s.ranges]
s = s.substitute(dict(zip(orig_ranges, end_ranges))).bufferize(*end_ranges, arg=BufferizeOpts(device=s.device)).index(*orig_ranges)
srcs.append(s)
return root.replace(src=tuple(srcs))
pm_limit_bufs = PatternMatcher([(UPat(set.union(GroupOp.Binary, GroupOp.Ternary), name="root"), limit_bufs)])
# *****************
# 4. put in buffers for bufferize
# TODO: should BUFFERIZE look a lot more like STORE
# BUFFERIZE has device in arg
# BUFFERIZE doesn't have indexing, that's implied by the ranges it closes
# BUFFERIZE returns the BUFFER ready for INDEXing (doing this will make splitting a lot easier)
# NOTE: this has been fixed up a bit
def bufferize_to_store(ctx:itertools.count, x:UOp, idx:UOp, allow_locals=True):
#assert isinstance(x.tag, Flat), "bufferize must be flat"
size = prod(x.shape)
rngs = sorted(idx.ranges, key=lambda x: x.arg)
assert size > 0 and isinstance(size, int), f"no zero sized or symbolic sized buffers {size}"
sdtype = x.dtype.ptr(size=size, addrspace=x.arg.addrspace)
if (assign := x.src[0]).op is Ops.ASSIGN:
assign_target, assign_src = assign.src[0], assign.src[1]
assert assign_target.op is Ops.INDEX, f"{assign_target.op} is not index"
while assign_src.op is Ops.NOOP: assign_src = assign_src.src[0]
# skip self-assign from same-device copy, otherwise create the store
# in assign, this is the buffer size, not the bufferize size
if assign_src is assign_target: ret = assign_target.src[0]
else: ret = assign_target.src[0].after(assign_target.replace(dtype=sdtype).store(assign_src, tag=x.tag).end(*rngs))
for op, marg in reversed(assign.arg or ()): ret = ret._mop(op, marg)
return ret
# lower outerworld reduce here
if x.src[0].op is Ops.REDUCE and len(x.src[0].src) == 2 and x.src[0].src[1].arg[-1] == AxisType.OUTER:
assert sdtype.addrspace == AddrSpace.GLOBAL
outer_range = x.src[0].src[1]
buf = UOp(Ops.BUFFER, x.dtype, (UOp(Ops.LUNIQUE, arg=next(ctx)), UOp(Ops.DEVICE, arg=x.arg.device)), size)
# NOTE: this has the same number as the outer range, we need string ranges!
zero_range = outer_range.replace(src=(UOp.const(dtypes.index, size),), arg=outer_range.arg[:-1]+(AxisType.LOOP,))
buf = buf.after(buf.index(zero_range).store(0).end(zero_range))
bufi = buf.index(idx, dtype=sdtype)
do_store = bufi.store(bufi.load() + x.src[0].src[0], tag=x.tag).end(*rngs).end(outer_range)
return buf.after(do_store)
# NOTE: the DEFINE_LOCAL needs to be disambiguated here
if sdtype.addrspace == AddrSpace.GLOBAL:
buf = UOp(Ops.BUFFER, x.dtype, (UOp(Ops.LUNIQUE, arg=next(ctx)), UOp(Ops.DEVICE, arg=x.arg.device)), size)
do_store = buf.index(idx, dtype=sdtype).store(x.src[0], tag=x.tag).end(*rngs)
return buf.after(do_store)
if allow_locals:
# handle locals
buf = UOp(Ops.DEFINE_LOCAL, sdtype, arg=next(ctx))
do_store = buf.broadcast(x.src[1].dtype.count).index(idx, dtype=sdtype).store(x.src[0]).end(*rngs)
return buf.after(do_store.barrier())
# collapse any BUFFERIZE to single input BUFFERIZE. move the tag to a reshape
def flatten_bufferize(x:UOp):
if x.tag is None and len(x.src) == 2: return None
ret = x.replace(tag=None, src=(x.src[0], get_single_element(apply_movement_op(Ops.RESHAPE, (prod(x.shape),), x.shape, x.src[1:]))))
rngs = x.src[1:]
ret = ret.forced_reshape(x.shape)
if any(r.op is Ops.RANGE and r.src[0].op is not Ops.CONST for r in rngs):
sym_shape = tuple([r.src[0] if r.op is not Ops.CONST else 1 for r in rngs])
ret = ret.shrink(tuple([(0,x) for x in sym_shape]))
return ret.rtag(x.tag)
pm_flatten_bufferize = PatternMatcher([(UPat(Ops.BUFFERIZE, name="x"), flatten_bufferize)])
pm_add_buffers = pm_mops+pm_flatten_bufferize+to_bufferview+PatternMatcher([
(UPat(Ops.BUFFERIZE, src=(UPat(), UPat(name="idx")), name="x"), lambda ctx,x,idx: bufferize_to_store(ctx, x, idx, allow_locals=False)),
# move RESHAPEs through MSELECT/MSTACK
(UPat((Ops.MSELECT, Ops.MSTACK), src=UPat(Ops.RESHAPE), name="m"),
lambda m: m.replace(src=tuple([x.src[0].base for x in m.src]), tag=None).reshape(m.shape).rtag(m.tag)),
# remove any RESHAPEs on KERNEL
(UPat(Ops.CALL, name="k"), lambda k: k.replace(src=tuple(x.src[0] if x.op is Ops.RESHAPE else x for x in k.src))),
])
pm_add_buffers_local = pm_mops+pm_flatten_bufferize+to_bufferview+PatternMatcher([
(UPat(Ops.BUFFERIZE, src=(UPat(), UPat(name="idx")), name="x"), bufferize_to_store),
])
# *****************
# 5. split into kernels
@dataclass
class LocalAddBufferContext:
dg:int = 0
map:dict = field(default_factory=dict)
vars:dict = field(default_factory=dict)
range:int = 0
parent_tags:list = field(default_factory=list)
opts:tuple|None = None
def debuf(ctx:LocalAddBufferContext, buf:UOp):
ret = UOp(Ops.PARAM, buf.dtype.ptr(buf.size), arg=ctx.dg)
if buf not in ctx.map: ctx.map[buf] = buf
ctx.dg += 1
return ret
def unbind_kernel(ctx:LocalAddBufferContext, b:UOp):
ctx.vars[b] = None
return b.src[0]
def handle_after(ctx:LocalAddBufferContext, after:UOp):
if isinstance(after.dtype, PtrDType) and after.ptrdtype.addrspace == AddrSpace.LOCAL: return None
buf = after.buf_uop
# HACK to put the buffer in the MAP instead of MSTACK/MSELECT
if buf.op in {Ops.MSTACK, Ops.MSELECT}: buf = buf.src[0]
assert buf not in ctx.map
ctx.map[buf] = after
return buf
def renumber_range(ctx:LocalAddBufferContext, r:UOp):
if r.tag != (): return None
if r.arg[-1] == AxisType.OUTER:
# for outer range, we replace with a bound variable
return UOp.variable("range_"+range_str(r), r.vmin, r.vmax).bind(r.replace(tag=None))
ret = r.replace(arg=(ctx.range,)+r.arg[1:], tag=None)
ctx.range += 1
return ret
def find_bufs(x:UOp):
idxs = [s for s in x.toposort(gate=lambda x: x.op is not Ops.AFTER) if s.op is Ops.INDEX]
read_from: dict[UOp, Ops] = {}
if any((buf:=idx.buf_uop).op in {Ops.BUFFER, Ops.PARAM} and read_from.setdefault(buf, op:=idx.src[0].op) is not op for idx in idxs):
raise RuntimeError(f"cycle detected while indexing {buf}")
to_define_global = PatternMatcher([
(UPat(Ops.STORE, name="x"), find_bufs),
(UPat(Ops.BUFFER, name="buf"), debuf),
(UPat(Ops.PARAM, src=(UPat(), UPat(Ops.DEVICE)), name="buf"), debuf),
(UPat(Ops.BIND, name="b"), unbind_kernel),
(UPat((Ops.MSTACK, Ops.MSELECT, Ops.AFTER), name="after"), handle_after),
# remove device from local BUFFERIZE
(UPat(Ops.BUFFERIZE, name="b"), lambda b: b.replace(arg=replace(b.arg, device=None))),
# remove UNIQUE/DEVICE to dedup CONST
(UPat(Ops.CONST, name="c"), lambda c: c.replace(src=()) if len(c.src) else None),
# renumber the ranges starting with 0 so that kernel deduping works
(UPat(Ops.RANGE, name="r"), renumber_range),
])
def get_contiguous(ctx:LocalAddBufferContext, x:UOp):
if isinstance(x.arg, tuple) and all(isinstance(y, Opt) for y in x.arg): ctx.opts = x.arg
return x.src[0]
rangeify_codegen = PatternMatcher([
(UPat(Ops.CONTIGUOUS, name="x"), get_contiguous),
# no NOOP in the kernel graph
# TODO: this can be moved into codegen?
(UPat(Ops.NOOP, name="x"), lambda x: x.src[0]),
# add loads to non ptr indexes
# TODO: this can be moved into codegen?
#(UPat.any(UPat(Ops.DEFINE_GLOBAL, name="dg"), UPat(Ops.DEFINE_LOCAL).f(Ops.AFTER, allow_any_len=True, name="dg"))
# .f(Ops.INDEX, name="idx", allow_any_len=True),
# lambda dg,idx: None if isinstance(idx.dtype, (PtrDType, ImageDType)) else idx.replace(dtype=dg.dtype, arg=None).load()),
# fix broadcast dtype
(UPat(Ops.AFTER, name="a").broadcast(name="b"), lambda a,b: a.broadcast(len(b.src))),
(UPat(Ops.DEFINE_LOCAL).f(Ops.AFTER, allow_any_len=True).broadcast(name="dg").f(Ops.INDEX, name="idx", allow_any_len=True),
lambda dg,idx: None if isinstance(idx.dtype, (PtrDType, ImageDType)) else
idx.replace(dtype=dg.dtype, arg=None).load(dtype=dg.dtype.base.scalar().vec(dg.dtype.vcount))),
(UPat(Ops.AFTER, name="a").gep(name="b"), lambda a,b: a.gep(b.arg)),
(UPat(Ops.DEFINE_LOCAL).f(Ops.AFTER, allow_any_len=True).gep(name="dg").f(Ops.INDEX, name="idx", allow_any_len=True),
lambda dg,idx: None if isinstance(idx.dtype, (PtrDType, ImageDType)) else
idx.replace(dtype=dg.dtype, arg=None).load(dtype=dg.dtype.base.scalar().vec(dg.dtype.vcount))),
])
def remove_metadata_tags(ctx:LocalAddBufferContext, x:UOp):
if x.tag is None or x.tag == (): return None
if isinstance(x.tag, tuple): ctx.parent_tags += list(x.tag)
return x.replace(tag=None)
pm_remove_tags = PatternMatcher([
(UPat(GroupOp.All, name="x"), remove_metadata_tags),
])
pm_add_range_tags = PatternMatcher([
(UPat(Ops.RANGE, name="x"), lambda x: x.rtag(())),
])
def split_store(ctx:list[UOp], x:UOp) -> UOp|None:
# if we have any non-outer ranges open here, we don't split
if any(r.arg[-1] != AxisType.OUTER for r in x.ranges): return None
# ends of outer range don't go in kernels
if x.op is Ops.END and x.src[1].op is Ops.RANGE and x.src[1].arg[-1] == AxisType.OUTER: return None
# local kernel rewrite
lctx = LocalAddBufferContext()
ret = graph_rewrite(x, to_define_global+pm_flatten_range+rangeify_codegen+pm_remove_tags, ctx=lctx, name="kernel split", bottom_up=True)
# gather the metadata
metadatas = [ctx[y].metadata for y in lctx.parent_tags]
# SINK requires all buffers on the same device, but COPY/BUFFER_VIEW/ENCDEC are cross-device or special hardware ops
if ret.op is Ops.STORE: stored = ret.src[1]
elif ret.op is Ops.END and ret.src[0].op is Ops.STORE: stored = ret.src[0].src[1]
else: raise RuntimeError(f"unknown kernel type {ret.op}")
if stored.op in {Ops.COPY, Ops.BUFFER_VIEW, Ops.ENCDEC}: ret = stored
else: ret = ret.sink(arg=KernelInfo(opts_to_apply=lctx.opts))
metadata = tuple(dedup(flatten([x for x in metadatas if x is not None])))[::-1]
kernel = ret.call(*lctx.map.values(), *lctx.vars.keys(), metadata=metadata)
if ret.op is Ops.SINK and not all_same([x.device for x in kernel.src[1:] if x.op is not Ops.BIND]):
raise RuntimeError(f"all buffers must be on the same device: {tuple(b.buf_uop for b in kernel.src[1:])}")
return kernel
split_kernels = PatternMatcher([
(UPat((Ops.STORE, Ops.END), name="x"), split_store),
])
def tag_uop(ctx:tuple[list[UOp], set[UOp]], x:UOp):
if x.tag is not None or x in ctx[1]: return None
if x.tag is None and x.op is Ops.CALL:
# don't tag anything in a CALL
for u in x.src[0].toposort(): ctx[1].add(u)
if x.dtype.scalar() == dtypes.index: return None
ctx[0].append(x)
return x.replace(tag=(len(ctx[0])-1,))
add_tags = pm_gate_kernel_sink+PatternMatcher([
# don't tag BUFFERs, they are global
(UPat(GroupOp.All-{Ops.PARAM, Ops.CONST, Ops.DEVICE, Ops.UNIQUE, Ops.LUNIQUE, Ops.DEFINE_VAR, Ops.BIND, Ops.CALL, Ops.END,
Ops.MSTACK, Ops.MSELECT, Ops.RANGE}.union(GroupOp.Movement), name="x"), tag_uop),
(UPat({Ops.MSTACK, Ops.MSELECT}, name="x"), lambda ctx,x: None if all(s.op is Ops.PARAM for s in x.src) else tag_uop(ctx, x)),
])
# support for using a contiguous permuted view instead of the parent view if one exists
def found_contiguous(ctx:dict[UOp, UOp], contig:UOp, src:UOp):
x = src
while x is not src.base:
if x.op is Ops.PERMUTE: contig = contig.permute(argsort(x.marg))
elif x.op is Ops.RESHAPE: contig = contig.reshape(x.src[0].shape)
else: return None
x = x.src[0]
ctx[src.base] = contig
replace_contiguous = PatternMatcher([
(UPat(Ops.CONTIGUOUS, src=(UPat(GroupOp.Movement, name="src"),), name="contig"), found_contiguous),
(UPat(GroupOp.ALU, name="alu"), lambda ctx,alu: alu.replace(src=new_src) if (new_src:=tuple(ctx.get(s, s) for s in alu.src)) != alu.src else None),
])
def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
if VIZ: graph_rewrite(sink, PatternMatcher([]), name="View Input Graph")
uop_list: list[UOp] = []
tsink = graph_rewrite(sink, add_tags, ctx=(uop_list, set()), bottom_up=True, name="number the uops")
tsink = graph_rewrite(tsink, pm_syntactic_sugar+pm_mops+earliest_rewrites+replace_contiguous, ctx={}, bottom_up=True, name="earliest rewrites")
# convert movement ops to ranges
tsink, rctx = run_rangeify(tsink, bool(DEBUG_RANGEIFY))
tsink = graph_rewrite(tsink, symbolic+pm_reduce_simplify+pm_const_buffer_folding+pm_remove_bufferize, name="symbolic+reduce_collapse+debuf")
tsink = graph_rewrite(tsink, pm_limit_bufs, ctx=rctx, name="limit buffers")
# rebuild the sink with all the BUFFERIZEs with tags, this is what's ending up in the tensor graph
# MSTACK stacks multiple BUFFERIZEs in one tagged tensor
# if it's not tagged by here, it's out
tsink = UOp.sink(*[x for x in tsink.backward_slice if x.base.op in {Ops.BUFFERIZE, Ops.MSTACK, Ops.CONST, Ops.PARAM, Ops.AFTER} and \
x.tag is not None and len(x.tag)])
if VIZ: graph_rewrite(tsink, PatternMatcher([]), name="View Tagged Rangeify")
# bufferize -> store
lunique_start: int = max([-1]+[x.arg for x in tsink.toposort() if x.op is Ops.LUNIQUE]) + 1
tsink = graph_rewrite(tsink, pm_gate_kernel_sink+pm_add_buffers+pm_add_range_tags, ctx=itertools.count(lunique_start), bottom_up=True,
name="bufferize to store")
tsink = graph_rewrite(tsink, pm_gate_kernel_sink+split_kernels, ctx=uop_list, bottom_up=True, name="split kernels")
# if a kernel depends on a buffer, and that buffer is later assigned to, make the assign depend on the kernel's assign
kernel_assign: dict[UOp, UOp] = {}
assign_rep: dict[UOp, UOp] = {}
for u in tsink.toposort():
if u.op is not Ops.AFTER: continue
kernel_assign[u.buf_uop] = u
for s in u.src[1].src:
# TODO: this is probably broken for MSELECT/MSTACK
if s.op not in {Ops.BUFFER, Ops.PARAM} or s is u.buf_uop or (a:=kernel_assign.get(s)) is None: continue
if any(x.op is Ops.AFTER and x.buf_uop is s for x in u.toposort()):
raise RuntimeError(f"cycle detected in graph, kernel for {u.buf_uop} must either depend on AFTER or BUFFER")
assign_rep[a] = kernel_assign[s] = a.replace(src=a.src+(u,))
if assign_rep: tsink = graph_rewrite(tsink, _substitute, ctx=assign_rep, bottom_up=True, name="fix_assign")
# TODO: we can probably get this earlier
sink_tags = [s.tag for s in tsink.src]
tsink = graph_rewrite(tsink, _remove_all_tags, name="remove all tags")
if VIZ: graph_rewrite(tsink, PatternMatcher([]), name="View Kernel Graph")
becomes_map: dict[UOp, UOp] = {}
for tag, s in zip(sink_tags, tsink.src):
assert tag is not None
for a in tag:
if a is None: continue
becomes_map[uop_list[int(a)]] = s
return becomes_map